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CONFERENCE PROCEEDINGS

Novi Sad, 2008

1938 INSTITUTE OF FIELD AND VEGETABLE CROPS 2008

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CONFERENCE PROCEEDINGS

CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008

CONTENTS PLENARY LECTURES Wheat research to serve the future needs of the developing world Preliminary results of growing oilseed rape and other brassicas for forage Hans-Joachim Braun, John Dixon, Jonathan Crouch and Thomas Payne ...................................28 Breeding and Agronomy: Interactions Genotypes * Environment with oilseeds André Pouzet ........................................................................................................................................33 The impact of genomics on conventional and molecular breeding in pea Thomas Henry Noel Ellis ....................................................................................................................39 Association Breeding Strategies for Improvement of Self-Pollinated Crops Mark E. Sorrells....................................................................................................................................43 How can levels of Sclerotinia resistance in sunflower be improved? Felicity Vear..........................................................................................................................................47 Breeding for protein stability and amino acid content in soybean James H. Orf, Maria A. Larriera, Eliza-Jane M. Anderson............................................................53 Sorghum Breeding: New and Old Technologies Working Together to Move the Crop into the Future Jeff Dahlberg, Janos Berenji, Robert R. Klein, Peter Beetham.....................................................59 Quantitative genetics in soybean: Is dominance important? Joseph W. Burton .................................................................................................................................65 Use of wild Helianthus species in sunflower breeding Gerald J. Seiler, Chao-Chien Jan, Thomas Gulya............................................................................71 Germplasm collections as an important tool for breeding - examples on wheat Andreas Börner, Kerstin Neumann, Ulrike Lohwasser, Marion S. Röder, Elena K. Khlestkina, Oxana Dobrovolskaya, Tatyana A. Pshenichnikova, Petr Martinek, Maria Rosa Simon, Borislav Kobiljski ....................................................................77 Qualitative genetics-examples from soybean and other crops Reid G. Palmer, Paola T. Perez ..........................................................................................................83 Ecological approaches in breeding of forage crops Paolo Annicchiarico .............................................................................................................................88 Increasing the genetic diversity of northern U.S. maize hybrids: Integrating pre-breeding with cultivar development Marcelo J. Carena.................................................................................................................................95 Biotechnology and molecular markers: Tools in creating and exploiting genetic variation for crop improvement Rita H. Mumm and Stephen P. Moose1abc ....................................................................................101 Utilizing Genetic Resources for Prebreeding of Stress Resistant Sugar Beet Germplasm: Using Molecular Tools Lee Panella..........................................................................................................................................107 Self-pollinated crops Genetic Resources and Prebreeding Oral Presentation Change in genetic diversity at gliadin loci in Triticum aestivum L. cultivars bred in two South European countries during four decades Alexandra Dragovich, Alexandra Imasheva, Srbislav Dencic and Borislav Kobiljski ..............113 18


Characteristic of bread wheat analogue-lines that differs in plant height by using molecular markers Chebotar Sabina, Chebotar Galyna, Motsnyy Ivan, Lobanova Ekaterina, Sivolap Yuriy.................................................................................................117 Genetic resources of vetches (Vicia spp.) in Serbia Aleksandar Miki}, Vojislav Mihailovi}, Branko ]upina, \or|e Krsti}, Pavol Hauptvogel, René Hauptvogel, Mirjana Vasi}, Gérard Duc, Judith Burstin...............................................................................................................121 Genetic resources of minor crops for healthy human nutrition Tomas Vymyslicky, Dagmar Janovska, Jana Rysova, Jan Hofbauer, Petr Smahel, Jan Pelikan ...................................................................................................................128 Self-pollinated crops Genetic Resources and Prebreeding Poster Presentation Microsatellite mapping of the mutant gene (mrs) for multirow spike in wheat (T. aestivum) Oxana Dobrovolskaya, Petr Martinek, Marion S. Röder, Andreas Börner ...............................133 Differentiation of seed quality characteristics and comparison between indigenous landraces and commercial wheat cultivars Ioannis G. Mylonas, Athanasios L. Tsivelikas, Elisabeth Ninou, Ioannis Sarakatsianos, Parthenopi Ralli, Eleni Panou-Filotheou ................................................137 Evaluation of rice genotypes by morphologic characters Konstantin Kamishev.........................................................................................................................141 Variation, heterosis and inheritance in F1 rice hybrids: Number of the full grains in the panicle of the central stem Konstantin Kamishev.........................................................................................................................145 DNA fingerprinting of wheat (Triticum aestivum L.) varieties using microsatellite markers Ankica Kondi}-[pika, Borislav Kobiljski, Srbislav Den~i}, Novica Mladenov, Nikola Hristov, Dragana Ka~avenda, Ljiljana Brbakli}................................................................149 Interspecies polymorphism analysis of EST-SSR markers in wheat and rye Dragana Obreht, Dragan Perovic, Mihajla Djan, Goran Barac, Ljiljana Vapa .........................153 Cross-pollinated crops Genetic Resources and Prebreeding Oral Presentation Sunflower lines and forms, obtained from the intergeneric hybridization M. Hristova-Cherbadzi and Michail Christov.................................................................................158 Enhancement of pepper biodiversity through remote hybridization Rumiana Pandeva, Mimi Petkova, Rossitza Rodeva.....................................................................161 Within-varieties and among-varieties variability of some characters in the collection of purple tansy Phacelia tanacetifolia Benth. Helena Marková, Pavlína Gottwaldová, Daniela Knotová, Jan Pelikán ....................................165

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Cross-pollinated crops Genetic Resources and Prebreeding Poster Presentation Mode of inheritance and genetic variance components for some root characteristics of sugar beet @ivko ]ur~i}, Lazar Kova~ev, Dario Danojevi}, Nevena Nagl ....................................................170 RAPD analysis of cultivated sunflower Helianthus annuus L. and its wild types Andrea Popovic, Nevena Nagl, Ksenija Taski-Ajdukovic ............................................................174 Application of recurrent selection in the development and maintenance of sugarbeet pollinator lines Nikola â~i}, Lazar Kova~ev, Sneàna Mezei, Nevena Nagl, Milorad Raji}, @eljka Stojakovi}......................................................................................................177 Use of biochemical markers for identification of melon (Cucumis melo L.) cultivars Rumyana Vladova, Miroslava Zamfirova, Tihomir Andreev, Lilia Krasteva ............................180 Changes in sunflower morphology as a result of applying of the experimental mutagenesis Michail Christov .................................................................................................................................184 Seed component diversity of wild Helianthus annuus L. accessions Daniela Valkova, Miroslava Hristova-Cherbadzi, Veselina Nikolova, Emil Penchev ..............187 New sunflower restorer lines developed by g-induced parthenogenesis from Helianthus annuus hybrids - disease resistance, combining ability. I. Disease resistance. Miglena Drumeva, Peter Yankov, Nina Nenova, Pepa Shindrova and Valentina Encheva .........................................................................................192 Cytogenetic studies of cytoplasmatic male sterility and fertility restoration in rapeseed Jovanka Atlagi}, Ana Marjanovi}-Jeromela, Radovan Marinkovi}, Sreten Terzi}...................197 Utilization of wild sunflower species in Novi Sad breeding program Jovanka Atlagi}, Sreten Terzi} .........................................................................................................201 Divergence of experimental alfalfa populations as affected by the objective and method of breeding S. Kati}, D. Mili}, V. Mihailovi} and \. Karagi}............................................................................207 Genetic diversity, combining ability and heterosis in maize inbred lines Sneàna Mladenovi} Drini}, Aleksandar Radoj~i}, Goran Drini}, Milomir Filipovi} ..............212 Core collection of broomcorn (Sorghum bicolor (L.) Moench) Vladimir Sikora, Jano{ Berenji.........................................................................................................216 Study of amino acid composition of winter vetch (V.villosa Roth.) depending on some major cultural factors Nataliya Georgieva, Todor Kertikov ...............................................................................................220 Self-pollinated crops Breeding for Resistance to Biotic and Abiotic Stresses Oral Presentation Use of marker-assisted selection (MAS) for pyramiding two leaf rust resistance genes, (Lr9 and Lr24) in wheat Odile Moullet, Dario Fossati, Fabio Mascher, Roberto Guadagnolo, Arnold Schori ..............225 Photosynthetic techniques in screening of wheat (Triticum aestivum L.) genotypes for improved drought and heat stress tolerance Marek @iv~ák, Jana Repková, Katarína Ol{ovská, Marian Bresti~.............................................229 20


Importance of diagnostic markers for the management of soil-borne viral diseases of barley and wheat Dragan Perovic, Miros³aw Tyrka, Jutta Förster, Pierre Devaux, Djabbar Hariri, Morgane Guilleroux, Kostya Kanyuka, Rebecca Lyons, Jens Weyen, David Feuerhelm, Ute Kastirr, Pierre Sourdille, Marion Röder and Frank Ordon ..................233 Estimation of grain yield and its components in winter wheat ad vanced lines under favorable and drought field environments Nikolay Tsenov, Tatiana Petrova, Elena Tsenova .........................................................................238 Self-pollinated crops Breeding for Resistance to Biotic and Abiotic Stresses Poster Presentation Investigation on the response of CIMMYT common winter wheat lines to brown rust Puccinia recondita F. sp. tritici Vanya Kiryakova................................................................................................................................243 The use of MAS for development of multi-pathogen resistant lines of barley Tibor Sedlá~ek, Lenka Stemberková, Martina Hanusová ............................................................246 Barley yellow dwarf virus - Breeding for tolerance Ondrej Veskrna, Pavel Horcicka, Jana Chrpova, Vaclav Sip, Lucie Slamova ...........................248 Yield components in wheat exposed to high concentrations of soil boron Milka Brdar, Ivana Maksimovi}, Borislav Kobiljski, Marija Kraljevi}-Balali} ..........................252 Effects of FHB tolerant winter wheat varieties (Petrus, Sakura, Simila) on yield and quality parameters under high pathogen pressure K. Rehorova, O. Veskrna, P. Horcicka, T. Sedlacek .....................................................................256 Possibilitie strategy for durable resistance to Puccinia recondita tritici of wheat Mom~ilo Bo{kovi}, Jelena Bo{kovi}................................................................................................260 Classification of Turkish Wheat and Wild Relatives for Their Rust Disease (Puccinia spp.) Resistance Gene Profile Mahmut Can Hiz, Yeliz Yilmaz ,Balkan Canher, Alptekin Karagoz and Muge Turet Sayar .......................................................................................264 Evaluation of common wheat cultivars of different geographic origin for resistance to leaf rust and powdery mildew in the conditions of Non-Chernozem zone of Russia Inna Lapochkina, Maria Rudenko, Nail Gajnullin, Irina Makarova, Vasiliy Kuzlasov, Irina Iordanskaya, Elizavetta Kovalenko, Albina Zemchuzhina, Harold Bockelman..............270 Identification of wheat germplasm resistant to Puccinia recondita using genetic and molecular markers Alma Kokhmetova, Shymbolat Rsaliev ..........................................................................................273 Variety-specific model of parasite development and effects of wheat parasites in semiarid regions Zoran Jerkovi}....................................................................................................................................277 Evaluation of Mutant Lines and Varieties of Common Winter Wheat Regarding their Drought Tolerance G. Rachovska, R. Chipilski ...............................................................................................................282 Heritability of some agronomic traits in diallel crossing of durum wheat under two different water regimes Dechko Dechev, Violeta Bozhanova, Elena Todorovska.............................................................286 Latent period and infection frequency as components of partial resistance to powdery mildew in some winter wheat varieties Mirjana Tele~ki, Radivoje Jevti}, Nikola Hristov, Novica Mladenov, Marija Kalenti} ............290 21


Study of some preparations for presowing treatment of the seeds of spring forage pea (Pisum arvense) for controlling insect pests Ivelina Nikolova .................................................................................................................................294 Cross-pollinated crops Breeding for Resistance to Biotic and Abiotic Stresses Oral Presentation Investigation on some fungal diseases of pepper Rossitza Rodeva, Rumiana Pandeva, Zornitza Stoyanova ...........................................................299 Ecophysiology of Hemp (Cannabis sativa L.) Anne-Michelle Faux, Pierre Bertin..................................................................................................303 Obtaining homozygous lines tolerant to sulfonylurea by in vitro culture of unfertilized sunflower ovules and preliminary studies on the progeny of gynogenetic plant. Elena Badea, Sorina Mihacea, Georgeta Dicu, Mariana Gheorghe, Cerasela Petolescu, Alexandru Lazar, Sorin Ciulca .........................................................................................................307 Evaluation of molecular markers for downy mildew resistance in sunflower Dejana Safti}-Pankovi}, Nata{a Radovanovi}, Vladimir Mikli~, Sini{a Joci} ............................311 Cross-pollinated crops Breeding for Resistance to Biotic and Abiotic Stresses Poster Presentation Effects of drought stress on gene expression in the apical and basal parts of maize kernel Violeta Andjelkovic, Snezana Mladenovic Drinic and M. Babic .................................................316 Study on tolerance of Ukrainian pea varieties to attack by pea weevil Bruchus pisi L. (Coleoptera: Bruchidae) Ivelina Nikolova, Ivan Pachev ..........................................................................................................320 Response of callus cultures of eggplant (Solanum melongena L.) to drought tolerance Violeta Nikova, Lilia Krasteva, Rumiana Pandeva, Philip Philipov, Veneta Kapchina, Detelina Petrova, Anka Petkova .....................................................................325 New sunflower forms and hybrids, resistant to herbicides Michail Christov, Georgi Sabev, Daniela Valkova and Miroslava Hristova-Cherbadzi ...........329 Physiological parameters as indicators of drought tolerance in sugar beet Marina Putnik-Deli}, Ivana Maksimovi}, Nevena Nagl, Ivana Gani, Lazar Kova~ev...............332 Resistance of interspecific sunflower progenies to head rot caused by Sclerotinia sclerotiorum (Lib.) de Bary Bo{ko Dedi}, Sreten Terzi}, Jovanka Atlagi}.................................................................................336 Estimation of Adaptive Ability and Stability of Perennial Ryegrass (Lolium perenne L.) Genotypes and Differentiative Ability of Environment Aneliya Katova ...................................................................................................................................340 The Effect of Insecticide Treatment on Sunflower (Helianthus annuus L.) Seed Germination Jelena Mr|a, Vladimir Mikli~, Milka Vujakovi}, Jovan Crnobarac, Goran Ja}imovi}, Velimir Radi}, Branislav Ostoji}, Ilija Radeka ...............................................344 Stress Factors and Their Effects on Seed Germination Velimir Radi}, Vladimir Mikli~, Nenad Du{ani}, Jelena Mr|a, Ana Marjanovi} Jeromela, Radovan Marinkovi} ..........................................................................347 22


Breeding for tolerance to corn reddening Goran Bekavac, Boàna Purar, \or|e Jockovi}, Laszlo Kálmán................................................351 Corn reddening Boàna Purar, Goran Bekavac, \or|e Jockovi}, Éva Toldi Tóth ...............................................355 Response of maize inbred lines to sulfonylurea herbicides in the field and greenhouse conditions Goran Malidà, Goran Bekavac, Aleksandra Nastasi} .................................................................359 In vitro antagonistic effect of Serratia liquefaciens to maize pathogenic fungi Sneàna Gosic Dondo, Sneàna Mladenovi} Drinic Kosana Konstantinov, Slavica Stojkov Stankovi} and Jelena Levic....................................................................................363 Self-pollinated crops Breeding for Yield and Quality Oral Presentation Research Toward Adaptation of Fall-sown Legumes in Northern Climates Kevin McPhee, Perry Miller and Chengci Chen.............................................................................368 Field pea genetic improvement at the University of Saskatchewan Tom Warkentin, Albert Vandenberg, Bunyamin Tar’an, Sabine Banniza, and Kirstin Bett .....................................................................................................372 New Achievements of Cotton Breeding in Bulgaria Ana Stoilova, Neli Valkova...............................................................................................................373 Results of half a century of wheat breeding at Institute of Field and Vegetable Crops in Novi Sad Srbislav Den~i} and Borislav Kobiljski............................................................................................377 Self-pollinated crops Breeding for Yield and Quality Poster Presentation A Comparison of Breeding Effectiveness for Productivity in Hybrid and Hybrid-Mutant Population of Common Bread Wheat Ginka Rachovska ...............................................................................................................................384 Audit of the Evaluation System of Triticum aestivum ssp. Vulgare on the Basis of Statistical Parameters Marija [ari}, Katarina ôbanovi}, Nada Hladni, Nada Gute{a ...................................................389 Grain Yield Response to Selection from F6 to F7 Generation in Pea Ranko Gantner, Mirko Stjepanovi}, Svetislav Popovi}, Tihomir ûpi} .....................................393 Influence of HMW glutenin subunits on rheological properties of the wheat dough Zuzana Kocourková, Pavel Hor~i~ka ..............................................................................................397 Studying inheritance of quantitative indices of group of varieties winter common wheat Elena Nikolova, Ivan Panayotov, Emil Penchev............................................................................401 Assessment of wet gluten rheological properties using sensory and instrumental methods Veselinka \uri}, Maria Mangova, S. Den~i}, N. Mladenov, N. Hristov, Marija Raci}.............406 Effect of inoculation with Azotobacter chroococcum on wheat yield and seed quality Nada Milosevic, Branislava Tintor and Gorica Cvijanovic ...........................................................410 Ecological stability of extensograph parameters in wheat cultivars M. Bodroà-Solarov, N. Mladenov, J. Mastilovi}, S. Deli} ...........................................................414 23


Cultivar x year interaction for winter malting barley quality traits Novo Prùlj, Vojislava Mom~ilovi} ..................................................................................................418 Spring malting barley quality in semiarid conditions Vojislava Mom~ilovi}, Novo Prùlj ..................................................................................................422 Study of productive capacities of Ukrainian cultivars of spring forage pea in the conditions of Bulgaria Ivan Pachev, Todor Kertikov, Daniela Kertikova .........................................................................426 Bread-making quality of winter wheat in a long-term crop rotation experiment Veselinka \uri}, Dragi{a Milo{ev, Sr|an [ereme{ic, Goran Ja}imovi}......................................430 Effect of Inoculation on Symbiotic Association Effectiveness in Bean Jelena Marinkovi}, Mirjana Vasi}, Mirjana Jarak..........................................................................435 Future challenges in breeding annual forage legumes at the Institute of Field and Vegetable Crops in Novi Sad, Serbia Vojislav Mihailovi}, Aleksandar Miki}, Slobodan Kati}, Sanja Vasiljevi}, Imre Pataki, Dragan Mili}, \ura Karagi}..........................................................438 Grain yield in winter and spring protein pea cultivars (Pisum sativum L.) with normal and afila leaf types Vojislav Mihailovi}, T. H. Noel Ellis, Gérard Duc, Isabelle Lejeune-Hénaut, Gérard Étévé, Siyka Angelova, Aleksandar Miki}, Branko ]upina ..................................................................................................443 Agronomic characteristics of Canadian and Serbian varieties of dry pea (Pisum sativum L.) Aleksandar Miki}, Tom Warkentin, Vojislav Mihailovi}, \or|e Krsti}, Svetko Vojin...............................................................................................................447 First selection of cultivar Phaseolus coccinus var. nanus in Bosna and Hercegovina Josip ]ota, Mustafa \elilovi}, Mirjana Vasi}, Jelica Gvozdanovi}-Varga .................................452 Seventy years of wheat breeding in Serbia: I. Improvement of yield Novica Mladenov, Nikola Hristov, Srbislav Den~i}, Borislav Kobiljski......................................456 Seventy years of wheat breeding in Serbia: II. Improvement of quality Nikola Hristov, Novica Mladenov, Veselinka \uri}, Ankica Kond}-[pika, Srbislav Den~i}, Borislav Kobiljski, Branka Ljevnai} ...................................................................460 Work on soybean breeding at the Institute of Field and Vegetable Crops in Novi Sad Jegor Miladinovi}, Milica Hrusti}, Milo{ Vidi}, Vuk \or|evi}, Svetlana Bale{evi}-Tubi}...................................................................................................................464 Cross-pollinated crops Breeding for Yield and Quality Oral Presentation Use of SRAP and RAPD Markers in Sugar Beet DNA Polymorphism Analysis Nevena Nagl, Dragana Vidovi}, Maja Kiti}, Lazar Kova~ev........................................................469 Combining Abilities for Grain Yield of Several B73 x Mo17 Maize Hybrids M.Stojakovi}, M. Ivanovi}, \. Jockovi}, G. Bekavac, B. Purar, A. Nastasi}, @. Stojakovi}.................................................................................................473

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Cross-pollinated crops Breeding for Yield and Quality Poster Presentation Correlation analysis of morphological traits in association to heterosis for yield at Helianthus annuus L. Maria Duca, Alexei Levitchi, Tudor Rotaru ..................................................................................478 Genotype specificity of rapeseed (Brassica napus L.) seed quality Milka Vujakovi}, Ana Marjanovi} Jeromela, Radovan Marinkovi}, Zorica Nikoli}, Velimir Radi}, Mladen Tati} .................................................................................483 Combining ability for stem diameter and plant height in sunflower (Helianthus annuus L.) Nada Hladni, Sini{a Joci}, Vladimir Mikli~, Marija Kraljevi}-Balali}, Dragan [kori}..........................................................................................487 Direct and indirect effects of morphophysiological traits on oil yield of sunflower (Helianthus annuus L.) Nada Hladni, Sini{a Joci}, Vladimir Mikli~, Anto Miji}, Dejana Safti} Pankovi}, Marija Kraljevi}-Balali} ..........................................................................491 Genotype x environment influence on aftercrop dry matter yield stability of annual ryegrass cultivars V. Kemesyte, J. Kanapeckas .............................................................................................................495 Spectral NIR approaches in forage perennial grass breeding Yordanka Naydenova ........................................................................................................................499 Effect of environments on in vitro dry matter digestibility evaluation in perennial ryegrass (Lolium perenne L.) Yordanka Naydenova, Aneliya Katova...........................................................................................504 The newest achievements in Lucerne breeding in Bulgaria Daniela Kertikova ..............................................................................................................................509 Sugar beet breeding in Serbia Lazar Kova~ev, Nikola â~i}, Ivica Stan~i}, Sneàna Mezei ........................................................513 Forage quality of a new winter vetch variety Asko 1 under a twofold harvesting regime Nataliya Georgieva, Todor Kertikov, Anna Ilieva ........................................................................517 Influence of roasting on oxidative stability of naked Olinka variety pumpkin seed oil Etelka Dimi}, Ranko Romani}, Vesna Vujasinovi}, Jano{ Berenji.............................................521 Oxidative stability of oleic sunflower kernel with altered tocopherol composition Ranko Romani}, Vesna Vujasinovi}, Dragan [kori}, Etelka Dimi} ...........................................525 Agronomic and chemical traits of ZP sunflower hybrids grown under different environmental conditions Miodrag Tolimir, Sla|ana @ili}, @ivota Jovanovi}, Branka Kresovi}, Goran Saratli} ..............529 Quality and the utility value of ZP maize hybrids Marija Mila{inovi}, Du{anka Terzi}, Milica Radosavljevi}, Sla|ana @ili}..................................533 Variability of amino acid content in rapeseed (Brassica napus L.) Ana Marjanovi} Jeromela, Aleksandar Miki}, Radovan Marinkovi}, Nikola Hristov, Aleksandra Bauer, Biljana Maro{anovi}.............................................................538 Genetics of head diameter and 1000-seed weight in sunflower: heritability, number of effective factors and correlations Radovan Marinkovi}, Ana Marjanovi}-Jeromela and Velimir Radi} .........................................541 25


The Dry Matter Yield Productivity of Late Red Clover (Trifolium pratense) Varieties Vil~inskas Egidijus .............................................................................................................................546 Mode of inheritance and combining ability for seed yield in sunflower Sandra Gvozdenovi}, Ilija Radeka, Sini{a Joci} .............................................................................550 A Biofertilizer for Sugar Beet Nastasija Mrkova~ki, Nikola â~i}, Sneàna Mezei, Lazar Kova~ev, Nevena Nagl..................554 Previous and future directions of perennial legumes selection in Serbia S. Kati}, Sanja Vasiljevi}, Z. Lugi}, Jasmina Radovi}, D. Mili} ...................................................557 Effect on planting date on yields and quality of spring garlic cultivar Labud Vida Todorovi}, Jelica Gvozdanovi}-Varga, Nata{a ]eji}-Balaban, Mirjana Vasi} .................564 Effect of different proportions of exotic germplasm on grain yield and grain moisture in maize Aleksandra Nastasi}, Mile Ivanovi}, Milisav Stojakovi}, \or|e Jockovi}, Du{an Stanisavljevi}, Zorana Sre}kov and G. Malidà.................................................................567 Correlation and path analysis of oil content and morphological traits of maize (Zea Mays L.) in the high-oil population NSU1 Zorana Sre}kov, Aleksandra Nastasi}, Jan Bo}anski, Mile Ivanovi} ..........................................571 Performace of NS Rapeseed Genotypes in France Ana Marjanovi} Jeromela, Radovan Marinkovi}, Dragana Miladinovi}, Olivier Ladsous, Olivier Maes ..........................................................................................................575 Moisture content changes of maize kernels and other plant organs after full ripening Géza Hadi, Ferenc Rácz, Tamás Spitkó, Csaba L. Marton, Emil Bodnár, Dénes Oross................................................................................................................579 Directions and achievements in breeding forage brassicas in Serbia Vojislav Mihailovi}, Aleksandar Miki}, Slobodan Kati}, Sanja Vasiljevi}, Ana Marjanovi}-Jeromela, Radovan Marinkovi}, Branko ]upina, Pero Eri}...........................582 General Topics and Round Table Oral Presentation Integration of conventional and molecular wheat breeding strategies Borislav Kobiljski, Srbislav Den~i} and Ankica Kondi}-[pika ....................................................587 Organic plant breeding and seed production - theory and practice Jano{ Berenji.......................................................................................................................................590 Bioethical aspects of scientific results application in food production Kosana Konstantinov, Sneàna Mladenovi} Drini}.......................................................................594 Possibilities for Development of Plant Breeding Sectors in the Future Nazimi Acikgoz...................................................................................................................................598 General Topics and Round Table Poster Presentation Effect of primary soil tillage on sugarbeet growth dynamics, stand density and root yield Milorad Raji}, Branko Marinkovi}, Jovan Crnobarac, Goran Ja}imovi} ...................................605 The effect of mineral nutrition on the chemical composition of the sugar beet root Janja Kuzevski, Sa{a Krstanovi}, Gordana [urlan-Momirovi}, Tomislav @ivanovi}, Zora Jeli~i}......................................................................................................609 Contact list...........................................................................................................................................613 26


PLENARY LECTURES

Plenary lectures


WHEAT RESEARCH TO SERVE THE FUTURE NEEDS OF THE DEVELOPING WORLD PRELIMINARY RESULTS OF GROWING OILSEED RAPE AND OTHER BRASSICAS FOR FORAGE Hans-Joachim Braun, John Dixon, Jonathan Crouch and Thomas Payne CIMMYT, Apdo Postal 6-641, 06600 Mexico-City, Mexico E-mail:[email protected]

Wheat production in developing countries has increased dramatically over the last 50 years from around 1 t/ha to now 2.8 t/ha, which is nearly the same as in developed countries (2.9t/ha in developed countries). Increases were obtained by providing farmers input-efficient and input-responsive disease resistant semi-dwarf cultivars. As impressive as the achievements were, wheat production needs to increase by 1.5% annually to reach 850 million tons in 2030. The required growth will need to come from increased yield, as area expansion is unlikely. Whether the target of 850 mlln tons will be achieved will depend on various factors. Factors that will strengthen productivity are identified, as is a set of key dampeners that will tend to depress productivity and production. The potential facilitators include “synthetic” wheat and exploitation of genetic stocks; better management of genotype x system interactions; increased breeding efficiency through MAB; Hybrid and GM wheat would also lead to increasing private sector investment. Factors contributing to below expected increase are shortage of fresh water for irrigation; soil degradation; emerging new biotic stresses; high energy prices; shift of a substantial proportion of the wheat production area from intensive irrigated to extensive rainfed production, though climate change may also lead to the expansion of wheat into new rainfed production areas; and climate change with respect to the negative effects of heat stress, and increased pest and disease pressure. Stagnating yield growth has become a concern for major wheat producing regions worldwide (see Reynolds et al. 2007 and Nagarajan 2005). However, since the underlying reasons for this stagnation are highly complex, the solutions are not likely to be straightforward. Investments in wheat breeding have declined in absolute terms along with the general reduction in agricultural research funding (Pardey 2006). Furthermore, the impact of non-sustainable agronomic practices and consequent declining soil fertility and decreasing response to inputs is channeling more and more breeding efforts and wheat improvement resources in LDCs (less developed countries) towards traits related to declining soil fertility (e.g., tolerance to micro-nutrient deficiency, tolerance to soil-borne diseases, tolerance to drought and salinity). Farmers cannot, therefore, utilize the increased yield potential of improved varieties and technologies, and their net income may even decline, as more inputs are applied to compensate for declining soil fertility (Sayre 2004). A concerted effort by farmers, agronomists, breeders, and policy makers is needed to improve soil fertility and input use efficiency through sustainable and low-cost practices, so that the higher yield potential of improved cultivars can be exploited in all production environments and provide farmers with a stronger incentive to replace old cultivars. Historically, wheat production has made a major contribution to global food security for millennia. Given the steady increases in wheat productivity during the past 40 years underpinned by better varieties, improved crop management, inputs, and markets, wheat has continued to play a major role in global food security and poverty reduction. Today wheat contributes around one-quarter of the global human consumption of calories, for which there are no easy substitutes in many major wheat consuming countries. The economic returns to productivity enhancing wheat research have been consistently high, as have the returns to maintenance research to defend those gains against a dynamic profile of environmental and biotic stresses. Managers of wheat research in the first quarter of the 21st century confront a completely new context of slowing wheat productivity, growing demand for biofuels, strong productivity growth in competing food and cash crops, changing agricultural markets and prices, evolving input and service institutions, and climate change. The analysis of wheat systems improvement over the next two decades can be framed around factors that either strengthen or diminish the growth 28

Plenary lectures


of wheat productivity and production along the annual 1.6% growth required to meet expected demand in 2020. Achievements in global wheat production during the second half of the 20th century were substantially fuelled by the collective efforts the free exchange of germplasm and data. Several hundred wheat researchers annually participated in global evaluation networks distributed through focal points from CIMMYT, ICARDA, USDA, Europe (including COMECON) and the TURKEY-CIMMYT-ICARDA Winter Wheat program. The germplasm distributed through regional and international nurseries were targeted to specific agro-ecological environments and consisted of segregating populations, screening nurseries, and advanced yield trials (Dixon et al. 2006). CIMMYT’s International Wheat Improvement Network (IWIN) is a prime example of the long-term reinforcing benefits of collective action, where the motivation of scientists and breeders across the world to share germplasm and information benefits everyone and provides an important foundation for global wheat improvement in the future. A two-way flow of information empowers NARSs while strengthening the relevance of products from international breeding programs (Byerlee and Moya (1993). Policy makers, researchers, and farmers generally depend on different types of information from different sources. Recent advances in information and communication technologies are enabling the creation of knowledge platforms. To address global challenges in wheat science and production, the exchange of both wheat genetic material and the associated knowledge through existing networks and new partnerships (e.g., IWIN) will be a critically important international public good (IPG) that must remain freely available to all if it is to achieve its full impact. Most wheat research in developing countries is currently conducted by public institutions, a situation similar to that of rice and sorghum, among the major global field crops. This is in contrast to other commodities such as maize, soybeans, rapeseed, and cotton, where the private sector is the major driver. In the absence of hybrids and GM technologies, there is a need for royalty or other value capture or incentive systems to increase private sector investments in wheat improvement (Pardey 2006). Funds for wheat research, in particular in less developed countries (LDC), are derived mostly from public donors and often spread over many research programs, making each investment relatively small and often less efficient. Average aggregate yield increases in the USA during the 1990s rose 15.5% for maize but only 6.3% for wheat (National Association of Wheat Growers et al. 2006), although the lower productivity of wheat growing areas compared to those for maize should be noted. Moreover, Pardey (2004) showed that public agricultural R&D spending declined from 7% annual growth for the period 1976-81 to below 4% for the period 1991-96. While a strong public sector working cooperatively with the private sector is essential to ensure benefits from the gene revolution (Pingali and Raney 2005), the key challenge is to attract private sector investment in agricultural research in developing countries. Thus, a major challenge in the coming decades is the development of technologies or mechanisms that can synergize private sector investment in wheat breeding across the world. Weeds, insects, and diseases reduce actual world wheat production by an estimated 28% (Oerke 2006), and the loss could be as high as 50% without effective plant protection. Though actual production losses are already high, it is anticipated that they will rise due to increased abiotic stresses caused by global climate change; however, diseases and pests may also become significant constraints in regions where they have not been observed before or were not previously economically important. The potential of new threats is exemplified by wheat blast, caused by Magnaporthe grisea, which in 1986 was reported for the first time on wheat, in-situ, in Paraná, Brazil (Igarashi et al. 1986). Within a few years, it spread to major wheat growing areas of Brazil, Bolivia, and Paraguay, and became a limiting factor on more than 3 m ha in the region. In the Bolivian lowlands, wheat blast led to a 50% decline in the area sown to wheat (Condori, pers. com., 2007). Though tolerance was found in wheat by EMBRAPA (Brazil) researchers, the majority of germplasm 29

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tested proved to be susceptible. The potential threat of wheat blast cannot be overstated; the disease represents a serious risk to wheat production and food security should it spread to neighboring Argentina and more dramatically if it spread to Asia, which is feasible since seed transmission has been reported. Once its epidemiology is better understood, spatial modeling could identify areas of potential risk. With the effect of climate change on pest and disease populations, situations such as this are likely to be increasingly common. Stem rust (Puccinia graminis) is historically the most feared and widespread disease of wheat. Controlled for decades by genetic resistance, it has recently re-emerged as the most serious biotic threat to global wheat production. A new race of stem rust was identified in 1999 in Uganda (therefore named Ug99) and now threatens 120 million tons, or 20%, of the world’s wheat in Central and North Africa, the Middle East and Asia, with a population of more than one billion people. The best known pandemic of stem rust in the United States occurred in 1953-54 and caused a 40% loss in spring wheat yields that would be worth $1 billion or more today; this led to the establishment of a response system comprising a) a robust collaborative international network of wheat improvement institutions, germplasm sharing, and strong human capacity and infrastructure dedicated to stem rust research; b) increasing frequency of resistant cultivar releases. As a result, there have been no stem rust pandemics over the last five decades. Unfortunately, over the years this response system has atrophied; consequently, the emergence and spread of Ug 99 represents a major threat to global wheat production. A concerted emergency global research effort under the umbrella of CIMMYT and ICARDA has been established: the Global Rust Initiative (GRI) (www.globalrust.org), initiated by Dr. Norman E. Borlaug in 2005. More than 20,000 wheat accessions, including major cultivars, have now been evaluated in Kenya and Ethiopia, and results indicate that as many as 90% of the world’s commercial wheat varieties are susceptible. Fortunately, new resistant high-yielding wheat lines have also been identified and are now being distributed globally. Maintaining and expanding wheat production is critically dependent on land and water resources that are being degraded in many irrigated and marginal wheat producing areas. Evenson and Gollin (2003a) estimated that one-third of the increase in food production in Asia between 1961 and 1981 (the main Green Revolution period) was attributable to crop improvement; the other two-thirds arose from a variety of crop management and institutional factors, in particular increased fertilizer use and better weed control, water management, and market access. Furthermore, there is scope for exploiting the positive interactions between genotype and cropping systems management (G x S). One of the proven crop management routes for improving the productivity of sustainable agriculture is the application of conservation agriculture systems (including reduced tillage, which saves resources, slashes costs, reduces greenhouse gases, and stabilizes production), while creating the management conditions for the expression of a greater proportion of genetic yield potential than in degraded, infertile conditions (Ekboir 2002). Key elements of such an approach include effective weed control, using herbicides as appropriate, and soil fertility management. Thus, without improved and profitable crop management, the full benefits of improved wheat germplasm will not be realized. Consumer preferences are evolving with increasing incomes, and the demands for specific quality attributes are changing. The industrialization of wheat processing that has occurred for bread will also take place for other products, including chapatis. This will result in increased demand for specific and consistent qualities of wheat. The differentiation of wheat products, whether by visible or indirect characteristics, opens the possibility of adding value to the wheat industry, creating extra employment along value chains, and increasing farm gate prices. This, in turn, may improve incentives for farmers to adopt new varieties with enhanced grain quality characteristics (supported by the necessary crop management practices). This presents a major challenge for wheat breeders to develop new varieties with stable novel quality profiles (irrespective of stresses during cultivation) while maintaining adequate yield potential. 30

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Few observers are aware of the speed with which new uses are being developed for cereal grains. Following a recent assessment by GRDC (2004), the projected growth in Australian wheat exports as a consequence of these new uses exceeds by far the growth in domestic demand. For example, the projected growth in industrial uses for starch, bioplastics, and high molecular weight ingredients is enormous–as much as 45% of Australian wheat exports by 2020 may be destined for advanced industrial uses (GRDC 2004). A second use, “first generation” bioethanol production from grain and “second generation” bioethanol production from cellulose in biomass, including straw, is emerging. This is driven by growing energy demands, especially for transportation, and by finite fossil fuel reserves. New foods such as low carb wheat or non-allergenic (low glycemic index) wheat also represent substantial potential niche markets, as do new uses for animal feed. Finally, potential nutri- or agriceutical and cosmetic uses of wheat are also under discussion, though these may not become major markets for wheat for many years. Naturally, the increasing diversity of uses is a major challenge for breeders and crop management researchers, as many of these niche market targets will require specifically tailored breeding programs in producer countries. Picket and Galwey (1997) evaluated 40 years of attempts to generate hybrid wheat cultivars and concluded that hybrid wheat production is not economically feasible because: a) limited heterotic advantage: historically only about a 10% advantage is commonly found, though introducing new genetic diversity (e.g., through synthetics) may increase heterosis; b) lack of advantage in terms of agronomic, quality, or disease resistance traits; c) seed production costs higher than heterotic yield advantage; and, probably most importantly, d) heterosis can be “fixed” and consequently hybrids would have no biological advantage over inbred lines. This is reflected in the small investments in hybrid wheat development globally as of 2007, as well as the small acreage under hybrid wheat. Functioning royalty collection systems in most OECD countries may also have reduced the incentives for breeding companies to produce hybrid wheat seeds. Though biotechnological methods now allow the capture of increased heterosis by direct selection of favorable alleles and new genetically based systems to control male sterility, which are not based on CMS that also may reduce the costs of commercial hybrid seed production, it remains to be seen whether hybrid wheat production will generate more interest in the future, in particular when functioning royalty collection systems are in place. If GM wheat is accepted, hybrid wheat may become economically viable. On the other side, increasing knowledge of the wheat genome and subsequent gene discovery will make MAS more efficient and more important, since new improved wheat cultivars will be developed more efficiently and faster. Considering the currently limited heterosis, high seed production costs, and the limited global investments in hybrid wheat on one side, and on the other side emerging options from biotechnology, need to raise yield potential and looking at the the success of hybrid rice, we refrain making a prediction about the future of hybrid wheat, but we tend towards an optimistic view for chances of hybrid wheat over the next two decades. References Byerlee, D., and Moya, P. 1993. Impacts of International Wheat Breeding Research in the Developing World 1966-1990. Mexico, D.F.: CIMMYT. Dixon, J., Nally, L., Aquino, P., Kosina, P., la Rovere, R., and Hellin, J. 2006. Centenary Review: Adoption and economic impact of improved wheat varieties in developing countries. Journal of Agricultural Science 144: 489-502. Ekboir, J. (ed.) 2002. CIMMYT 2000-2001 CIMMYT World Wheat Overview and Outlook: Developing No-Till Packages for Small-Scale Farmers. Mexico, D.F: CIMMYT. European Commission. 2002. Opinion of the scientific committee on food on Fusarium toxins. http://ec.europa.eu/food/fs/sc/scf/out123_en.pdf. Evenson, R.E., and Gollin, D. (eds.). 2003a. Crop Variety Improvement and Its Effect on Productivity: The Impact of International Agricultural Research. Wallingford: CABI. GRDC. 2004. Towards a single vision for the Australian grains industry. Grain Research and Development Corporation and Grains Council of Australia, Canberra, Australia. Igarishi, S., Utlamada, C.M., Igarishi, L.C., Kazuma, A.H., and Lopez, R.S. 1986. Pyriculariain wheat. 1. Occurrence of Pyricularia sp. in Paraná State. Fitopatol. Bras. 11: 351-352. Nagarajan, S. 2005: Can India produce enough wheat even by 2020? Science 89:9. 1467-1471.

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CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008 Oerke, E.C. 2006. Crop losses to pests. Journal of Agricultural Science 144:31-43. Pardey, P.G, J.M. Alston, C. Chan-Kang, E.C. Magalhnes, and S.A.Vosti. 2004. Assessing and Attributing the Benefits from Varietal Improvement Research in Brazil. Research Report 136. Washington, D.C.: IFPRI. Pardey, P.G., N. Beintema, S. Dehmer, and S. Wood. 2006. Agricultural Research: A Growing Global Divide? Agricultural Science and Technology Indicators Initiative, International Food Policy Research Institute. Washington, D.C.: IFPRI. Pickett, A.A., and N.W. Galwey 1997. A further evaluation of hybrid wheat. Plant Varieties Seeds 10:15-32. Pingali, P., and Raney, T. 2005. From the Green Revolution to the Gene Revolution: How Will the Poor Fare? ESA Working Paper 05-09. Agricultural and Development Economics Division. Rome, Italy: FAO. Reynolds, M.P., Braun, H.-J., Pietragalla, J., and Ortiz, R. 2007. Challenges to international wheat breeding. Proceedings of the Symposium on Increasing Wheat Yield Potential. Euphytica, Special issue, 2007. Sayre, K.D., and Hobbs, P.R. 2004. The raised bed system of cultivation for irrigated production conditions. In: Lal, R., Hobbs, P.R., Uphoff, N., and Hansen, D.O. (eds.). Sustainable Agriculture and the International Rice-Wheat System. New York: Marcel Decker. pp. 337-355.

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BREEDING AND AGRONOMY: INTERACTIONS GENOTYPES * ENVIRONMENT WITH OILSEEDS André Pouzet CETIOM 12 avenue George V 75008 Paris ‡ France E-mail: [email protected]

Abstract During the last 20 years in France, we tried to characterize the behavior of new oilseeds cultivars at the field scale with the multiplicative interaction model. Several groups of genotypes with an homogeneous behavior could be identified. The extra cost for the characterization of different cultivars and of different environments has not allowed the generalisation of such an approach. Recently, the development of new crop models has been very efficient to make sensitivity studies easier compared to field experiments. With sunflower, we could show that the parameters governing phenology (ant not only flowering or maturity date), photosynthetic activity (and not only LAI), plant architecture (and not only plant height) can explain the behaviour of one cultivar under different environments. Different strategies are possible for breeders and agronomists. Farmers will probably choose the maximisation of varietal performance if they are given the keys to choose the good cultivar(s) under changing environmental conditions. Key words: Brassica napus, crop management, France, Glycine max., Helianthus annuus, modelling, oilseed rape, soybean, sunflower Introduction Interactions between plant genotypes and the environnement (IGE) have been studied for a long time (Yates & Cochran 1938, cited by Leflon et al. 2005) for plants. The objective of such studies is to have a better understanding of the phenotypic variability for one (or several) genotype(s) in different spatio-temporal environments. This question is also of interest for animal sciences: for example, the adaptation of different poultry lines to high temperatures or to light or to feedstuff are important for egg-laying performance (Mérat & Bordas 1992). Even with humans, the relations between food and health are studied from a genetic point of view (Junien C. 2003). In the field of crop sciences, the questions about IGE are different from one stakeholder to the other: · For the breeder: which characteristics should be included in one cultivar to get a high and reliable performance under different edaphic (places or years) or management (e.g. irrigation or fertilisation or sowing date) conditions? or, which characteristics are desirable in a very specific environment? · For the farmers: which cultivar could be the best one in one field or the other? after choosing the cultivar, which is the best crop management according to the local conditions (specially weather) to optimize the production? and symmetrically, what is the most fitted cultivar for a given crop management system (e.g. minimum tillage.)? · For extension services (e.g. CETIOM), the objective is to give farmers pieces of information as accurate as possible on crop management (of course including cultivars), and to optimize networks for the evaluation of cultivars. Those questions do not have the same temporal horizon: for the breeder it is a long-term question whereas for the farmer, it is a mid-term (choice of one cultivar) or very short term (amount of nitrogen fertilization). This is probably the reason why the question of IGE has been studied mainly from the breeder point of view and why, at that time, nearly no tool is available for farmers to help them in their strategic and tactical decisions. In the first part of this review, we shall present why IGE studies are so important for Institutes like CETIOM, in a second part we shall discuss the attempts that have been made during the last twenty years to adapt methods to 33

1 0 3 ,5

1 0 5 ,9

9 8 ,7

9 2 ,8

9 4 ,3

9 6 ,4

1 0 2 ,4

9 1 ,1

8 8 ,7

3 ,1 7

LORELEY

GALILEO

ARCADIA

ES ALIENOR

BURMA

AV IS O

GRIZZLY

SERUGA

ES ALICIA

Average yield (T/ha)

1 0 1 ,5

DK CABERNET

1 0 9 ,8

1 0 8 ,4

EXAGONE

NK SILIC

1 0 5 ,7

R IC C O

97

1 0 5 ,2

ALPAGA

EPURE

9 8 ,7

GOYA

89017

34

3 ,2 4

8 8 ,7

9 3 ,6

9 1 ,4

9 6 ,3

9 4 ,8

101

9 9 ,1

1 0 1 ,3

1 0 6 ,9

1 0 4 ,9

1 0 1 ,3

9 8 ,4

1 0 3 ,8

1 0 8 ,8

1 0 1 ,1

1 0 8 ,5

45031

3 ,2 6

6 8 ,6

9 2 ,6

1 0 6 ,6

96

9 9 ,1

1 0 4 ,6

8 9 ,1

1 0 5 ,6

9 9 ,1

1 0 9 ,5

1 0 4 ,7

9 8 ,1

1 1 1 ,9

9 8 ,7

1 0 8 ,3

1 0 7 ,5

37022

3 ,3 2

9 4 ,8

1 0 8 ,9

8 7 ,3

9 4 ,1

9 4 ,9

87

9 8 ,6

1 0 5 ,3

8 6 ,3

9 7 ,4

108

1 0 6 ,1

1 0 1 ,5

3 ,5 3

8 3 ,2

9 4 ,5

9 3 ,8

9 4 ,6

9 7 ,3

1 0 6 ,6

1 0 0 ,1

9 8 ,8

1 0 6 ,2

1 0 4 ,7

1 0 6 ,2

9 8 ,6

1 0 1 ,6

1 0 3 ,2

1 0 2 ,6

1 0 6 ,7 1 0 7 ,7

1 0 8 ,1

36015

1 1 5 ,5

89013

3 ,8 2

9 9 ,9

9 4 ,2

9 3 ,3

1 0 3 ,3

9 4 ,1

1 0 6 ,8

1 0 3 ,6

9 5 ,2

1 1 4 ,9

90

8 6 ,5

8 7 ,4

1 1 3 ,1

1 1 4 ,8

110

9 2 ,9

58010

4 ,1 7

89

9 8 ,5

9 9 ,9

9 4 ,8

9 7 ,8

9 8 ,2

1 0 1 ,2

9 7 ,8

1 0 2 ,1

1 0 3 ,8

1 0 5 ,2

1 0 3 ,8

1 0 6 ,6

1 0 1 ,8

9 6 ,2

1 0 3 ,2

18033

4 ,3 0

9 0 ,5

9 3 ,2

100

9 9 ,1

9 9 ,8

8 9 ,1

9 9 ,9

101

109

105

9 7 ,8

103

106

100

105

101

3002

4 ,6 1

9 4 ,7

9 5 ,5

1 0 1 ,6

9 1 ,3

1 0 1 ,1

9 6 ,7

9 9 ,3

9 0 ,4

9 4 ,2

95

1 0 7 ,3

1 0 3 ,6

1 0 3 ,9

1 0 8 ,3

1 0 8 ,1

1 0 8 ,9

21044

4 ,6 7

9 3 ,9

9 5 ,5

9 7 ,3

1 0 1 ,7

1 0 4 ,8

9 8 ,5

9 3 ,2

1 0 2 ,1

99

1 0 6 ,1

9 9 ,1

102

8 6 ,6

100

1 1 1 ,4

1 0 8 ,7

28039

4 ,7 5

8 4 ,8

8 9 ,9

9 5 ,8

9 6 ,1

1 0 1 ,3

9 8 ,5

9 9 ,6

1 0 0 ,3

1 0 0 ,9

1 0 1 ,9

1 0 4 ,7

1 0 7 ,1

1 0 0 ,7

1 0 3 ,6

1 0 6 ,7

108

91048

5 ,1 6

87

1 0 2 ,6

9 3 ,7

9 6 ,8

9 3 ,5

9 6 ,4

9 9 ,2

1 0 0 ,8

1 0 2 ,7

9 4 ,5

1 0 5 ,3

1 0 3 ,6

114

1 0 0 ,4

1 0 4 ,2

1 0 5 ,5

27050

5 ,3 3

9 6 ,1

9 5 ,2

93

9 6 ,7

9 6 ,8

9 8 ,8

1 0 0 ,4

9 9 ,5

9 8 ,9

1 0 3 ,8

1 0 5 ,7

1 0 6 ,4

9 8 ,3

1 0 0 ,9

1 0 3 ,2

1 0 6 ,3

38009

5 ,6 0

1 0 1 ,2

97

1 0 0 ,6

9 9 ,9

9 9 ,6

9 9 ,1

9 7 ,1

1 0 0 ,5

1 0 3 ,6

9 9 ,4

1 0 6 ,6

9 6 ,5

1 0 0 ,7

9 8 ,6

9 9 ,6

58011

4 ,2 1

9 0 ,8

9 5 ,9

9 6 ,9

9 7 ,1

9 8 ,0

9 8 ,1

9 8 ,6

1 0 0 ,1

1 0 1 ,8

1 0 1 ,9

1 0 2 ,1

1 0 2 ,3

1 0 3 ,3

1 0 3 ,6

1 0 4 ,7

1 0 5 ,1

Indice M oy e nne

Table 1: Performance of 16 cultivars in 14 experiments in 2008 ‡ Centre-East of France. Experiments are in columns (Codes 89017 to 58011) and sorted by increasing average yield from left to right. Cultivars are in line and sorted by decreasing average yield from top to bottom. The yield performance of each cultivar in each experiment is in percentage of the average yield in each experiment. The coloured cases indicate the experiments where one cultivar appears in the five first rows of the ranking.


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study IGE from the breeding area to the crop management area and in a third part we shall discuss perspectives to improve the valorization of IGE studies for crop management. Importance of IGE for extension services. To argue this point, we shall use the results of CETIOM network for the evaluation of oilseed rape (OSR) commercial cultivars. Cultivars are registered in France after two years of official evaluation. The cultivars that show a better performance than controls are registered and may be commercialised. The official test has a limited number of experiments (generally less than 20 per year all over France) which does not permit to have an idea of the fitness of registered cultivars to different environments. So, CETIOM makes post-registration evaluation, with 15 to 20 experiments for each of the four ecozones we are using in France (North-East, Centre-East, West, and South). Unfortunately, yield performance of cultivars remains very variable and it is not possible to identify a limited number of outstanding cultivars well adapted all over one ecozone. For example, Table 1 gives the results of the experiments in 2008 for the Centre-East ecozone. In average over the 14 experiments, the best cultivar performs 105,1 % but its performance within experiments varies from 92,9 up to 115,5 %. As a consequence, the best advice to farmers would be to recommend avoiding cultivars which seldom appear in the 4 or 5 first rows in the experimental tests (Table 2). For example, after the data in tables 1 and 2, we could tell farmers not to grow the 8 cultivars that do not appear at least twice in the top 4 ranks of the 14 experiments. Table 2: Frequency of appearance of cultivars in the top ranks of each experiment (e.g. 11 cultivars appear at least twice in the top five or 12 cultivars appear at least once in the top three over 14 experiments). 0/14 1/14 2/14 3/14

1st 9 7 4 2

1st or 2nd 7 9 6 6

1st, 2nd or 3rd 4 12 8 8

1st, 2nd, 3rd or 4th 3 13 8 8

1st, 2nd, 3rd, 4th or 5th 2 14 11 8

This could be a good strategy from a breeder point of view, but the remaining variability of the performance of selected cultivars from one experiment to the other does not prevent farmers from getting results lower than what they may expect from such a selection. Trying to identify the best performing cultivars in different environmental conditions is an important challenge for farmers themselves, but also for the whole supply chain of OSR: whereas the average yield of the 14 experiments is 4,21 T/ha, the average yield becomes as high as 4,62 T/ha if we are able to choose the best cultivar in each experiment. Farmers have interest in growing several cultivars (and not only one) to secure yield at the farm level. Studies are also going on to identify the interest of mixing cultivars in the fields to increase yield stability at the field level (Pellet et al. 2005). It is important to remind that there are also IGE with quality parameters of the seeds (Oil content and fatty acids: Luquez et al. 2002, Möllers & Schierholt 2002, Si et al. 2003, Shi et al. 2003, Zhang et al. 2004, MacCartney et al. 2004 ; Tocopherols: Ayerdi Gotor et al. 2006 ; Hullability: Denis & Vear 1994 ). Generally speaking, they are not as high as with yield, but they should not be ignored when quality is taken into account in the economic value of the seeds. Studies about IGE during the last decades. With sunflower (SF) many results are available from Argentina, under the view of breeders to adapt cultivars to the wide diversity of crop conditions in Argentina. Different methods have been used, with an important use of multivariate analyses (De la Vega & Chapman 2001, De la Vega et al. 2001). The same group (De la Vega & Chapman 2006) has also studied the components of the variability to conclude on the importance of General or Specific Combining Abilities (GCA or SCA): GCA*E an SCA*E can influence breeding strategies to exploit broad and/or 35

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specific adaptation. More generally they distinguish predictable vs unpredictable IGE, and they conclude (De la Vega & Chapman, 2005) that predictable interactions should involve specific adaptation breeding, when unpredictable IGE should involve broad adaptation breeding. These studies have been completed with ecophysiological discussions for the interpretation of IGE and to identify heritable components to valorize or minimize IGE (Chapman & de la Vega 2002, De la Vega & Hall 2002a, De la Vega & Hall 2002 b, De la Vega et al. 2002). They concluded that the behaviour of genotypes in tropical environments could be anticipated by delaying sowing dates in temperate environments. They also suggested a number of phenotypic characteristics (mainly the canopy stay green character and the seed set in the central part of the head) to anticipate the performance of a new cultivar in one region or the other. As far as the agronomic purposes are concerned, we have mainly used the Additive Main Effects and Multiplicative Interaction (AMMI) model (Denis 1993) to study IGE with OSR or sunflower (SF). This model has an additive part and a multiplicative one. The results can be presented under the graphic form of biplots. Two interesting results have been observed with OSR: i)- it is possible to mix results from different countries and ii) – it is possible to anticipate the behaviour of one cultivar from one country to the other when several common checks are used (Riboud & Messéan 1994). The same method has been used with SF and with soybean (SB), and its potential for the description of the IGE has been confirmed (Foucteau et al. 2001, Riboud 1993). Another method derived from social choice theory has been tested with OSR (Guénoche et al. 1994), but despite its interest to identify components of the mean performance, it has not been developed on a wide basis. Generally speaking, the interpretation of IGE with agronomic purposes has been limited by the cost of the characterization of both genotypes and environments in a very accurate way. Some attempts have been made (Leterme et al. 1992), but the added value of sophisticated methods remain low for local advisers as earliness and lodging sensitivity of cultivars were the main contributors to IGE. One of the most interesting ideas is to use well known cultivars to characterize the environment. In France, this has been tested with SB (Desclaux & Roumet 1993). Results were very promising: with two or three checks of different maturity groups and measurements of yield components (number of pods, number of seeds per pod and mean seed weight), it is possible to have a very good characterisation of the environment (soil and climate) and to evaluate the origin of IGE for new cultivars. This method is labour intensive, and it is probably difficult to use it for winter crops due to the length of the vegetative period and the diversity of limiting factors that can contribute to IGE. Perspectives to improve the valorization of IGE studies for crop management Following the two previous parts of this review, it is clear that there is a need to improve our capacity to characterize the phenotypic adaptation of genotypes under different environmental conditions. If we can do that with a limited amount of labour, it will also be possible to characterize the environments by well known cultivars as mentioned previously. Three main directions appear from recent studies to improve our capacity for this characterisation: historical and ecophysiological reviews of cultivars, the valorization of genomic studies and the develoment of new modelling tools. Historical reviews: with SF, such reviews have been made in France (Vear et al. 2003, Vear et al. 2004) and in Argentina (De la Vega et al. 2007). Both of them show the importance of phenology (e.g. the evolution toward an intermediate maturity in Argentina) and of the parameters linked to seed filling (e.g. the evolution of the mean seed weight in France). From the french study, it was also concluded (Debaeke et al. 2004) that a large leaf area index at anthesis and its maintenance with only a limited decrease of leaf nitrogen during grain filling appear to be the main characteristics of high-performance cultivars. More over, it appears that these characteristics are heritable, even though the residual leaf area is more sensitive to environmental effects (TriboV et al. 2004). Valorization of genomic studies: up to now, there are only limited data available with SF or OSR. With winter wheat, a very comprehensive study (Leflon et al. 2005) concludes that IGE 36

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studies may shift from genotype to gene level. As breeders are looking for QTL with stable effects in several environments, QTL*environment interactions are merely detected, in spite of their interest as anticipated for wheat (Brancourt-Hulmel 2000) and shown with maize (Reymond et al. 2003, Reymond et al. 2004). Crop modelling: with the development of new algorithms (Fourcaud et al. 2008) and the capacity of computers, models are more and more interesting to integrate available knowledge. With SF and OSR, new models become available to take into account physiological basis of plant growth and development, the interactions between organogenesis and photosynthesis and also the scaling up from one plant to plant populations (Rey et al. 2008). Applications of these architectural models to OSR are under development (Allirand et al. 2007) while they are already available for SF. In a first study (Poire-Lassus 2005), 26 SF genotypes have been compared and it is remarkable that the six high-yielding genotypes do not have the same route of yield elaboration: two of them have both a high photosynthetic activity and a long duration of LAI, one has a large LAI but a low photosynthetic activity and three others are short with a very high photosynthetic activity. The second study (Casadebaig 2008) confirms the interest of models to predict the performance of SF genotypes in a wide range of environmental conditions. Of course, there is always a lot of work to improve the efficiency of such models, but now an important effort should be made on the characterisation of the environments to improve the valorization of IGE for crop management. Conclusions The study of IGE has a long history, but up to now only breeders could take advantage of research in this field. The development of new technologies can help extension services and farmers to improve their understanding of IGE and optimize crop management, but such an objective will be possible only with a very close collaboration between plant breeders and geneticists, ecophysiologists and agronomists, extensionists and farmers. References Allirand J.M., Jullien A., Fortineau A., Savin A., Ney B. (2007): Parametrizing a simple model of photosynthetic active radiation absorption by complex aerial structures of oilseed rape resulting from genotype*nitrogen interactions. Proceedings of the 12th International Rapeseed Congress, Wuhan, China, March 26-30 2007, III, 261-264 Ayerdi Gotor A., Berger M., Labalette F., Centis S., Daydé J., Calmon A. (2006): Variabilité des teneurs et compositions des composés mineurs dans l’huile de tournesol au cours du développement du capitule. Partie I – Tocophérols. OCL, 13, 206-212 Brancourt-Hulmel M. (2000): Sélection pour l’adaptation au milieu et prise en compte des interactions génotype / milieu. OCL, 7, 504-511 Casadebaig P. (2008): Analyse et modélisation des interactions génotype – environnement – conduite de culture: application au tournesol. Th~se Université de Toulouse/INPT 195 Chapman S.C., de la Vega A.J. (2002): Spatial and seasonal effects confunding interpretation of sunflower yields in Argentina. Field Crops Research, 73, 107-120 Debaeke P., TriboV A.M., Vear F., Lecoeur J. (2004): Crop physiological determinants of yield in old and modern sunflower hybrids. Proc. 16th International Sunflower Conference, Fargo, North Dakota, USA August 29 – September 2, 267-274 De la Vega A.J., Chapman S.C., Hall A.J. (2001): Genotype by environment interaction and indirect selection for yield in sunflower I - Two-mode pattern analysis of oil and biomass yield across environments in Argentina. Field Crops Research, 72, 1, 17-38 De la Vega A.J., Chapman S.C. (2001): Genotype by environment interaction and indirect selection for yield in sunflower II. Three-mode principal component analysis of oil and biomass yield across environments in Argentina. Field Crops Research, 72, 1, 39-50. De la Vega A.J., Chapman S.C. (2005): Defining sunflower selection strategies for a highly heterogeneous target population of environments. Crop Sience, 46, 136-144 De la Vega A.J., Chapman S.C. (2006): Multivariate analyses to display interactions between environment and generals or specific combining ability in hybrid crops. Crop Science, 46, 957-967. De la Vega A.J. , Hall A.J. (2002a): Effects of planting date, genotype and their interactions on sunflower yield – 1- Determinants of oil-corrected grain yield. Crop Science, 42, 1191-1201 De la Vega A.J. , Hall A.J. (2002b): Effects of planting date, genotype and their interactions on sunflower yield – 2Components of oil grain yield. Crop Science, 42, 1202-1210

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CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008 De la Vega A.J. , Hall A.J., Kroonenberg P.M. (2002): Investigating the physiological bases of predictable and unpredictable genotype by environment interactions using three-mode pattern analysis. Field Crops Research, 78, 2, 165-183 De la Vega A.J., DeLacy I.H., Chapman S.C. (2007): Changes in agronomic traits of sunflower hybrids over 20 years of breeding in Central Argentina. Field Crops Research, 100, 1, 73-81 Denis J. B. (1993): Modélisation de l’interaction génotype*milieu. Séminaire du CTPS Techniques d’expérimentation en vue de l’évaluation des variétés. Paris 05/05/1993, 67-73. Denis L, Vear F. (1994): Environmental effects on hullability of sunflower hybrids. Agronomie, 14, 589-597 Desclaux D., Roumet P. (1993): Recherche des caractéristiques variétales et environnementales expliquant les interactions génotype*milieu chez le soja. Séminaire du CTPS Techniques d’expérimentation en vue de l’évaluation des variétés. Paris 05/05/1993, 105-119 Foucteau V., El Daouk M., Baril C. (2001) Interpretation of genotype by environment interaction in two sunflower experimental networks. Theoretical and applied genetics, 102, 327-334. Fourcaud T., Zhang X., Stokes A., Lambers H., Körner C. (2008): Plant growth modelling and applications: the increasing importance of plant architecture in growth models. Annals of Botany, 101, 1053-1063 Guénoche A., Vandeputte-Riboud B., Denis J.B. (1994): Selecting varieties using a series of trials and a combinatorial ordering method. Agronomie, 14, 363-375 Junien C. (2003): Dialogues g~nes-nutriments d’hier et d’aujourd’hui: comment la nutrigénétique et la nutrigénomique pourraient contribuer B contrôler l’épidémie d’obésité. Comptes Rendus de la Séance commune de l’Académie d’Agriculture de France et de l’Académie des Sciences – Mercredi 5 novembre 2003 Leflon M., Brancourt-Hulmel M., Lecomte C., Barbottin A., Jeuffroy M.H., Robert N. (2005) Characterization of environments and genotypes for analyzing genotype * environment interaction: some recent advances in winter wheat and prospects for QTL detection. Journal of crop improvement, 14, 1/2, 249-298 Leterme P., Riboud B., Lancesseur (1992): Colza: Interactions “Variétés*Milieux”. Dossier Technique CETIOM, 17 Luquez J.E., Aguirrezabal L.A.N., Aguero M.E., Pereyra V.R. (2002): Stability and adaptability of cultivars in non-balanced yield trials. Comparison of methods for grain yield and quality in “high oleic” sunflower. Journal of Agronomy and Crop Science, 188, 225-234 MacCartney C.A., Scarth R., MacVetty P.B.E. (2004): Genotypic and environmental effects on saturated fatty acid concentration of canola grown in Manitoba. Canadian Journal of Plant Science, 84, 3, 749-756 Mérat P. et A. Bordas (1992): Les objectifs et crit~res de sélection: Interactions génotype * Environnement et adaptation au milieu chez les volailles. INRA Productions Animales, 1992, hors série «Eléments de génétique quantitative et application aux populations animales», 175-178. Mollers C. , Schierholt A. (2002): Genetic variation of palmitate and oil content in a winter oilseed rape doubled haploVd population segregating for oleate content. Crop Science, 42, 379-384. Pellet D., Hebeisen Th., Accola A., Heiniger U., Voegeli U., Zürcher J. (2005): Colza d’automne: mélanges de variétés pour améliorer la stabilité du rendement. Revue Suisse d’Agriculture, 37, 3, 125-129. Poire-Lassus R. (2005): Analyse et modélisation de la variabilité phénotypique du rendement en graines chez un panel de 26 génotypes de tournesol: IntérLt et apports des mod~les biophysiques. Mémoire DEA ENSAM, 21 Rey H., Dauzat J., Chenu K., Barczi J.F., Dosio G.A., Lecoeur J. (2008): Using a 3-D virtual sunflower to simulate light capture at organ, plant and plot levels: contribution of organ interception, impact of heliotropism and anlysis of genetic differences. Annals of Botany, 101, 1139-1151 Reymond M., Muller B., Leonardi A., Charcosset A., Tardieu F. (2003): Combining QTL analysis and an ecophysiological model to analyse the genetic variability of the responses of maize leaf growth to temperature and water deficit. Plant Physiology, 131, 664-675 Reymond M., Muller B., Tardieu F. (2004): Dealing with the genotype*environment interaction via a modelling approach: a comparison of QTLs of maize leaf length or width with QTLs of model parameters. Journal of Experimental Botany, 55, 2461-2472 Riboud B. (1993): Etude des interactions entre les facteurs variété et milieu chez le soja utilisant un réseau d’essais multilocal de 1991. Séminaire du CTPS Techniques d’expérimentation en vue de l’évaluation des variétés. Paris 05/05/1993, 120-138 Riboud B. Messéan A. (1994): Méthodologie de l’évaluation variétale: une nouvelle approche. GCIRC Bulletin, 10, 86-93 Shi C.H., Zhang H.Z., Wu J.G., Li C.T., Ren Y.L. (2003): Genetic and genotype * environment interaction effects analysis for erucic acid content in rapeseed (Brassica napus L.). Euphytica, 130, 2, 249-254. Si P., Mailer R.J., Galway N., Turner D.W. (2003): Influence of genotype and environment on oil and protein concentrations of canola (Brassica napus L.) grown across southern Australia. Australian Journal of Agricultural Research, 54, 4, 397-407 TriboV A.M., Messaoud J., Debaeke P., Lecoeur J., Vear F. (2004): Heredity of sunflower leaf characters useable as yield predictors. Proc. 16th International Sunflower Conference, Fargo, North Dakota, USA August 29 – September 2, 517-524 Vear F., Bony H., Joubert G., Tourvieille de Labrouhe D., Pauchet I., Pinochet X. (2003): 30 years of sunflower breeding in France. OCL, 10, 1, 66-73 Yates F., Cochran W.G. (1938): The analysis of groups of experiments. Journal Agricultural Sci., 28, 556-580 Zhang H.Z., Shi C.H., Wu J.G. (2004): Analysis of genetic and genotype * environment interaction effects from embryo, cytoplasm and maternal plant for oleic acid content of Brassica napus L. . Plant Sci. 167, 1, 43-48

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THE IMPACT OF GENOMICS ON CONVENTIONAL AND MOLECULAR BREEDING IN PEA Thomas Henry Noel Ellis John Innes Centre, Department of Crop Genetics, Colney Lane, Norwich NR4 7UH, United Kingdom E-mail: [email protected]

Abstract Although pea is an important legume break crop in Europe, it ranks relatively low on the world scale. The pea genome is large, the number of seeds set per plant is low compared to many crops and the generation of transgenic plants is difficult. These factors have prevented the adoption of pea as a model species for genetics and genomics, accordingly the arrival of genetic and genomic tools for pea has been late compared to other species, however many resources are now available and the pea genome is well characterized in comparison to that of Medicago truncatula. Here I will discuss the opportunities and constraints for using these resources in the context of plant breeding. Key words: breeding, genomics, pea The pea crop In the UK the vining pea crop (for freezing and vegetable use) and the combining crop (mainly for animal feed) have a similar total economic value, but of course the combining (or field pea) crop grown for dry seed has the larger area and so has the larger potential for the provision of public goods. The impact of this crop is essentially to lower the input cost and environmental footprint of agriculture. However public goods are necessarily independent of market driven factors, but it is the market that determines farmers' choice of crop. Figure 1 shows the way the UK pea and bean area has changed over that last few years.

Figure 1. Field pea (pod symbol) and faba bean (seed symbol) areas in the UK since 1996. Data taken from www.ukagriculture.com. It seems clear that the rise of genomics has not been correlated with an increase in the competitivity of the pea crop. We should ask what underlies the declining trend in the pea crop area. Presumably there are many factors. Typically the pea price is about twice that of wheat, and 39

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the yields are about 45% of wheat and have remained (on average) stable for several years. These economic factors will certainly guide farmers' choices but a 50-fold preference for wheat seems remarkable. Seeding rates are high (pea seeds are bigger than wheat grains) so the initial outlay for a farmer is high and the management regime for the crop is different. A farmer therefore needs a significant investment in order to plant a pea crop successfully. Peas still have a reputation for yield loss and crop failure, mainly due to lodging in the UK conditions, however yield stability year on year suggests either that this is simply a problem of perception, or that catastrophic yield losses are not recorded. These are typical gloomy expressions for those interested in legumes, however we should see in this that there are some real opportunities. Pea yields are nearly 50% that of wheat and the crop value is about twice. The cost of input nitrogen is rising because of rising energy costs. The environmental impact if nitrogen fertiliser is large - and can be more than 50% of the energy cost of some crops. What then do we need to do to improve the position of the pea crop: 1. We need to improve its yield stability and overcome the perception of its yield instability due to lodging. 2. We need a modest increase in pea yield potential. 3. We should reduce the investment needed for a farmer to plant a field of peas. These combine to suggest that a smaller seed with lower protein content coupled to a robust growth habit is an option that should be considered. Pea is widely supposed to be a 'protein' crop, but in fact the starch component of the seed is also important in feed formulation. We know that seed nitrogen content is correlated with reduced yield, so all of these objectives seem achievable. What do we know in general about pea genomics? The pea genome is large, about the same size as the human genome and much of the genome is comprised of repetitive sequences (Macas et al., 2007) with nearly 50% identified as LTR retrotransposons from a 454 sequencing strategy. Presumably these authors have not been able to identify low copy and diverged classes of retrotransposon, so this is likely to be an underestimate. Studies of the genetics and diversity of the insertion sites for these elements (Ellis et al., 1998; Pearce et al., 2000; Vershinin et al., 2003; Jing et al., 2005; Smýkal et al., 2008) have shown that in general these are highly polymorphic, with few insertion sites fixed in Pisum as a whole or indeed within sub taxa of Pisum. This can be interpreted in two complimentary ways: 1. The pea genome, on average, contains relatively fey retrotransposon insertions: most sites are empty in most individuals. 2. The pea genome is vast with an interminable number of insertion sites: if we included all occupied sites then the genome would be very much larger than the genome of a single individual. These may seem strangely contradictory statements, but they are in fact consistent with one another and are a consequence of the abundance and polymorphism of these elements. Interestingly the former view suggests that the pea genome, on average (but in no particular instance) looks something like the model for the genome of Medicago truncatula (Kulikova et al., 2001). This view is in turn consistent with the observed syntenic relationship between the gene content of pea and especially Medicago truncatula (Choi et al., 2004; Kaló et al., 2004; Zhu et al., 2005). All this suggests that despite the relatively small amount of publically available DNA sequence for pea there are many resources to draw upon, and the good news is that within Pisum there is an abundance of polymorphism for both molecular markers and the genes that underlie phenotypic variation. How is genetic variation partitioned in Pisum? We know that retrotransposon insertion site polymorphism can be used as a system of genetic markers to infer patterns of relationship among Pisum accessions (Vershinin et al., 2003; Smýkal et al., 2008). The main message from these studies is that Pisum is relatively poorly differ40

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entiated with a great deal of mixing of alleles between diverse types, and this has been borne out by a more recent analysis of nucleotide polymorphism within genes (Jing et al., 2007). There is therefore an abundance of genetic diversity available in Pisum as a resource for breeders, but accessing useful alleles from non-adapted material is problematic for breeders. Accordingly a search among adapted material for contrasting lines with respect to (neutral) molecular markers, and the establishment of recombinant inbred populations from this material would seem worthwhile. Novel genetic variation For breeders, it is not always feasible to find suitable genetic variation within accessible germplasm. In pea the search for sources of resistance to Aphanomyces has been a notorious case in point. The generation of transgenic plants has been touted as one possible approach to overcome this type of limitation, and methods for pea transformation are available (Bean et al., 1997), but this general approach has not (yet) led to the development of varieties that can be used in agriculture (Schroeder et al., 1995; de Sousa-Majer et al., 2007), in part for technical reasons, but sadly also because of non-scientific difficulties. The more traditional source of induced variation was called 'mutation breeding'(Blixt, 1972) and this has recently seen a resurgence with the advent of systematic mutant populations such as Fast Neutron induced deletions (Sainsbury et al., 2006) that can be used in forward genetic screens or TILLING (http://urgv.evry.inra.fr/UTILLdb) for which a platform has been established in pea (Dalmais et al., 2008) that allows a reverse genetic screen. We can anticipate therefore that the studies of the many model systems will identify candidate genes which are expected, when mutant, to confer an interesting or useful phenotype, and access to resources such as that developed by Bendahmane and colleagues will provide direct access to the corresponding plant types. Conclusion The pea crop requires some improvement, and the targets such as disease resistance or standing ability are relatively clear. The application of genomic resources to partition genetic variation in germplasm or breeding material is a viable approach as is the use of both forward and reverse genetic tools to access novel variation. Marker assisted selection could be feasible because of the abundant molecular marker diversity in pea. What is needed though is a low cost procedure to incorporate such approaches in breeding programmes. References Bean S. J., Gooding P. S., Mullineaux P. M., Davies D. R. (1997): A simple system for pea transformation. Plant Cell Reports, 16, 513-519. Blixt S. (1972): Mutation Genetics in Pisum. Agri Hortique Genetica, 30, 1-293. Choi H.-K., Kim D.-J., Zhu H., Mun J.-H., Baek J.-M., Roe B., Ellis N., Young N. D., Doyle J., Kiss G., Cook D. R. (2004): Conserved gene order between crop and model legume species. Proceedings of the National Academy of Science of the United States of America, 101, 15289-15294. Dalmais M., Schmidt J., Le Signor C., Moussy M., Burstin J., Savois V., Aubert G., Brunaud V., de Oliveira Y., Guichard C. R. T., Bendahmane A. (2008): UTILLdb, a Pisum sativum in silico forward and reverse genetics tool. Genome Biology, 9, R43. de Sousa-Majer M. J., Hardie D. C., Turner N. C., Higgins T. J. V. (2007): Bean ?-amylase inhibitors in transgenic peas inhibit the development of pea weevil larvae. J. Econ. Entomol., 100, 1416-1422. Ellis T. H. N., Poyser S. J., Knox M. R., Vershinin A. V., Ambrose M. J. (1998): Polymorphism of insertion sites of Ty1-copia class retrotransposons and its use for linkage and diversity analysis in pea. Molecular and General Genetics, 260, 9-19. Jing R., Knox M. R., Lee J. M., Vershinin A. V., Ambrose M., Ellis T. H. N., Flavell A. J. (2005): Insertional polymorphism and antiquity of PDR1 retrotransposon insertions in Pisum species. Genetics, 171, 741-752. Jing R., Johnson R., Seres A., Kiss G., Ambrose M. J., Knox M. R., Ellis T. H. N., Flavell A. J. (2007): Gene-Based Sequence Diversity Analysis of Field Pea (Pisum). Genetics, 177, 1-13. Kaló P., Seres A., Taylor S. A., Jakab J., Kevei Z., Kereszt A., Endre G., Ellis T. H. N., Kiss G. B. (2004). Comparative mapping between Medicago sativa and Pisum sativum. Molecular Genetics and Genomics, 272, 235-246. Kulikova O., Gualtieri G., Geurts R., Kim D.-J., Cook D., Huguet T., Jong J. H. d., Fransz P. F., Bisseling T. (2001): Integration of the FISH pachytene and genetic maps of Medicago truncatula. The Plant Journal 27, 49-58.

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CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008 Macas J., Neumann P., Navrátilová A. (2007): Repetitive DNA in the pea (Pisum sativum L.) genome: comprehensive characterization using 454 sequencing and comparison to soybean and Medicago truncatula. BMC Genomics, 8, 427. Pearce S. R., Knox M., Ellis T. H. N., Flavell A. J., Kumar A. (2000): Pea Ty1-copia group retrotransposons: transpositional activity and use as markers to study genetic diversity in Pisum. Molecular and General Genetics, 263, 898-907. Sainsbury F., Tattersall A. D., Ambrose M. J., Turner L., Ellis T. H. N., Hofer J. M. I. (2006): A crispa null mutant facilitates identification of a crispa-like pseudogene in pea. Functional Plant Biology, 33, 757-763. Schroeder H. E., Gollasch S., Moore A., Tabe L. M., Craig S., Hardie D. C., Chrispeels M. J., Spencer D., Higgins T. J. V. (1995): Bean a-amylase inhibitor confers resistance to the pea weevil (Bruchus pisorum) in Transgenic Peas (Pisum sativum). Plant Physiology, 107, 1233-1239. Smýkal P., Hýbl M., Corander J., Jarkovský J., Flavell A. J., Griga M. (2008): Genetic diversity and population structure of pea (Pisum sativum L.) varieties derived from combined retrotransposon, microsatellite and morphological marker analysis. Theoretical and Applied Genetics, 117, 413-424. Vershinin A. V., Allnutt T. R., Knox M. R., Ambrose M. J., Ellis T. H. N. (2003): Transposable elements reveal the impact of introgression, rather than transposition, in Pisum diversity, evolution and domestication. Molecular Biology and Evolution, 20, 2067-2075. Zhu H., Choi H.-K., Cook D.R., Shoemaker R. C. (2005): Bridging model and crop legumes through comparative genomics. Plant Physiology, 137, 1189-1196.

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ASSOCIATION BREEDING STRATEGIES FOR IMPROVEMENT OF SELF-POLLINATED CROPS Mark E. Sorrells Department of Plant Breeding & Genetics, Cornell University, Ithaca, NY USA E-mail: [email protected]

Abstract Association breeding strategies utilize phenotypic and genotypic information to increase gain from selection and reduce selection cycle time. Plant breeding programs are dynamic, complex genetic entities that require frequent evaluation of marker / phenotype relationships. In comparison to QTL mapping in a biparental-cross population, association mapping is usually conducted directly on relevant breeding germplasm, thus facilitating the practical use of information in a crop improvement program. Also, there is more genetic variation in a breeding program than in a biparental cross; consequently, phenotypic variation and marker polymorphism are much higher. Genotypic data can be combined with phenotypic data from routine screening and variety trial evaluations to facilitate selection for low heritability traits. Novel alleles can be identified and the relative allelic value can be assessed as often as necessary. To minimize statistical error, correction for population structure is critical in a collection of genotypes, especially in a breeding program where relationships are highly variable. Multiple selection cycles without phenotyping can be used to increase selection gain per unit time. Three approaches will be elaborated that utilize molecular marker information for crop improvement: 1) association breeding: crossing/ selection/ testing program, 2) marker-assisted recurrent selection (MARS), and 3) genomic (genome-wide) selection. Increasingly efficient molecular breeding methods will continue to be developed for identifying and evaluating allelic effects on a large scale so that breeders can assemble desirable alleles in superior varieties. Key words: Recurrent selection, genomic selection, marker assisted breeding. Introduction Plant breeding methodologies evolve with new knowledge and technological advances that increase the efficiency of accurately selecting unique phenotypes and genotypes for target environments. Molecular markers have enhanced the resolution of genome mapping in many crop species and contributed to our understanding of the genetic control of important traits. With the dramatic improvements in genotyping technologies, phenotyping has become a bottleneck and new methods and technologies that increase the efficiency of phenotyping and data analysis will contribute significantly to crop improvement. This report will cover strategies and approaches for effectively exploiting association analyses for crop improvement and expand on earlier information in the maize and Triticeae literature. Recent reviews include Jannink et al. (2001), Gupta et al. (2005), Breseghello and Sorrells (2006a), Ersoz et al. (2007), MacKay and Powell (2007) or Yu and Buckler (2006). Linkage Disequilibrium Linkage disequilibrium (LD), or non-random association of alleles at adjacent loci throughout the genome within a population is the basis for association mapping (AM) strategies. Genetic diversity and historical relationship estimates among germplasms are very useful for AM and the exploitation of genetic variation in cultivated species. In biparental crosses between inbred lines, LD is maximized. The power of association analysis is affected by the patterns of LD, the extent of LD in the genome, and the variation in LD from one population to another. Factors affecting LD include mating system, recombination rate, population structure, population history, genetic drift, directional selection and gene fixation (reviewed by Gaut and Long 2003). Reports of linkage disequilibrium estimates for self-pollinated crops such as wheat and barley range from 5 to 40 cM, much lower than reported for outcrossing species such as maize. A commonly used statistic for measuring LD is the squared value of the Pearson’s (product moment) correlation coefficient, r2, that is a measure of the proportion of the variance of a response variable ex43

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plained by a predictor variable (Hill and Robertson 1968). The intuitive nature of r2 facilitates the interpretation of marker densities and association analyses. If a causative DNA polymorphism, or quantitative trait nucleotide (QTN), is assumed to contribute a fraction of the total variation in a quantitative trait, we can estimate the fraction of the variance explained by a marker in LD. For example, if the QTN has a heritability of h2Q (i.e., it explains that fraction of the phenotypic variance), then the fraction of the phenotypic variance explained by a marker in LD is r2*h2Q. Numerous reports have shown that LD varies widely within a genome, among different populations, and among species (e.g. Remington et al. 2001; Flint-Garcia et al. 2003; Breseghello and Sorrells 2006b; Maccaferri et al. 2006; Rostoks et al. 2006; Ersoz et al. 2007). However, the genome-wide LD is useful as a general guide to marker density that may be required for whole-genome AM and each population must be evaluated on a case-by-case basis. Typically, r2 values for all pairwise linked or syntenic markers are plotted against either map distance or physical distance. Values of r2 = 0.1-0.2 are sometimes chosen arbitrarily as an indicator of statistically significant LD. This level of LD, however, would indicate that the closest marker only captures 10 to 20% of the phenotypic variation resulting from a causal polymorphism. Association Breeding and Genomic Selection Breeding progress depends on i) the discovery and generation of genetic variation for agronomic traits, ii) development of genotypes with new or improved attributes due to superior combinations of alleles at multiple loci, and iii) accurate selection of rare genotypes that possess new improved characteristics.

Figure 1. Flow of germplasm and information in a breeding program. There are three basic approaches elaborated in Figure 1 that utilize molecular marker information for crop improvement: 1) association breeding: crossing/ selection/ testing program, 2) marker-assisted recurrent selection (MARS), and 3) genomic (genome-wide) selection. In a typical breeding program, selected genotypes are crossed to produce new populations that are subject to phenotypic and/or genotypic selection. Those materials are either intermated or inbred to produce new populations or inbred lines that are evaluated in replicated, multi-environment trials. The breeder uses the trial information to select elite parents that re-enter the hybridization program. In association breeding, genotypic data (preferably whole genome coverage) and the appropriate analyses are incorporated to validate previously mapped marker/trait associations and potentially identify new ones. This information is used to estimate allelic value at selected loci (or all loci in genome-wide selection) and then create a genotypic value index for each genotype and trait (Lande and Thompson 1990; Christopher et al. 2007). The marker assisted recur44

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rent selection method involves the improvement of an F2 or F1-derived doubled haploid (DH) population using one generation of phenotypic and genotypic evaluation to identify marker/trait associations followed by multiple cycles of recurrent selection using only allelic values at the selected marker loci (Johnson 2001 2004; Bernardo and Yu 2007). The genetic gain of MARS over phenotypic selection has been studied through computer simulation in maize (Bernardo and Charcosset 2006; Bernardo et al. 2006). The genome-wide selection method involves marker-assisted selection in which selections are based on all markers across the entire genome rather than just those showing significant effects. Phenotypic and genotypic information is combined to produce breeding values of all the markers that are then fitted as random effects in a linear model. Individuals in subsequent recurrent selection generations are then selected based on the sum of those breeding values (Meuwissen et al. 2001, 2002). Bernardo and Yu (2007) compared MARS to genome-wide selection in simulations involving a population of 144 individuals from which 4 individuals were selected in cycles 1 and 2. For MARS, a selection index based on all selected markers was calculated as suggested by Lande and Thompson (1990). For genome-wide selection, the best linear unbiased predictor (BLUP) of breeding values was estimated by fitting all the markers as random effects and imposing an assumption of equal variances based on cycle 0 performance. Genome-wide selection resulted in a larger response to selection than MARS. Depending on the number of QTL and the heritability, the response to genome-wide selection was 6-18% higher than MARS with the biggest advantage for complex traits with low heritability. Conclusions More efficient methods will continue to be developed for identifying and evaluating allelic effects on a large scale so that breeders can assemble desirable alleles in superior varieties. As we expand our knowledge of how genes evolve and interact to produce the nearly infinite range of phenotypes, new opportunities to manipulate genetic variation to the benefit of humankind will arise. References Bernardo R, Charcosset A (2006) Usefulness of Gene Information in Marker-Assisted Recurrent Selection: A Simulation Appraisal. Crop Science 46: 614-621 Bernardo R, Yu J (2007) Prospects for Genomewide Selection for Quantitative Traits in Maize. Crop Science 47: 1082 Breseghello F, Sorrells ME (2006a) Association Analysis as a Strategy for Improvement of Quantitative Traits in Plants. Crop Science 46: 1323 Breseghello F, Sorrells ME (2006b) Association Mapping of Kernel Size and Milling Quality in Wheat (Triticum aestivum L.) Cultivars. Genetics 172: 1165-1177 Christopher M, Mace E, Jordan D, Rodgers D, McGowan P, Delacy I, Banks P, Sheppard J, Butler D, Poulsen D (2007) Applications of pedigree-based genome mapping in wheat and barley breeding programs. Euphytica 154: 307-316 Ersoz ES, Yu J, Buckler E (2007) Applications of linkage disequilibrium and association mapping in crop plants. In Genomics-assisted Crop Improvement. In ‘Genomics-assisted Crop Improvement’. (Eds R Varshney, R Tuberosa). (Springer. Flint-Garcia S, Thornsberry J, Buckler E (2003) Structure of linkage disequilibrium in plants. Annual review of plant biology 54: 357-374 Gaut BS, Long AD (2003) The Lowdown on Linkage Disequilibrium pp. 1502-1506. (Am Soc Plant Biol. Gupta P, Rustgi S, Kulwal P (2005) Linkage disequilibrium and association studies in higher plants: present status and future prospects. Plant Mol Biol 57: 461-485 Hill WG, Robertson A (1968) Linkage disequilibrium in finite populations. Theor Appl Genet 38: 226-231 Jannink JL, Bink M, Jansen RC (2001) Using complex plant pedigrees to map valuable genes. Trends in Plant Science 6: 337-342 Johnson L (2001) Marker assisted sweet corn breeding: A model for specialty crops. p. 25-30. In Proc. Annu. Corn Sorghum Ind. Res. Conf., 56th, Chicago, IL. 5-7 Dec. 2001. Am. Seed Trade Assoc., Washington, DC. Johnson R (2004) Marker-assisted selection. Plant Breed. Rev. 24(1):293-309. Lande R, Thompson R (1990) Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124: 743-756 Maccaferri M, Sanguineti MC, Natoli V, Ortega JLA, Salem MB, Bort J, Chenenaoui C, De Ambrogio E, del Moral LG, De Montis A (2006) A panel of elite accessions of durum wheat (Triticum durum Desf.) suitable for association mapping studies. Plant Genetic Resources: characterization and utilization 4: 79-85 Mackay I, Powell W (2007) Methods for linkage disequilibrium mapping in crops. Trends in Plant Science 12: 57-63

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CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008 Meuwissen TH, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157: 1819-1829 Meuwissen TH, Karlsen A, Lien S, Olsaker I, Goddard ME (2002) Fine mapping of a quantitative trait locus for twinning rate using combined linkage and linkage disequilibrium mapping. Genetics 161: 373-379 Remington DL, Thornsberry JM, Matsuoka Y, Wilson LM, Whitt SR, Doebley J, Kresovich S, Goodman MM, Buckler ES (2001) Structure of linkage disequilibrium and phenotypic associations in the maize genome. Proc Natl Acad Sci U S A 98: 11479-11484 Rostoks N, Ramsay L, MacKenzie K, Cardle L, Bhat P, Roose M, Svensson J, Stein N, Varshney R, Marshall D, et al. (2006) Recent history of artificial outcrossing facilitates whole-genome association mapping in elite inbred crop varieties. Proc Natl Acad Sci USA 103: 18656-18661 Yu J, Buckler E (2006) Genetic association mapping and genome organization of maize. Curr Opin Biotechnol 17: 155-160

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HOW CAN LEVELS OF SCLEROTINIA RESISTANCE IN SUNFLOWER BE IMPROVED? Felicity Vear INRA, UMR INRA-Université Clermont II 1095, Domaine de Crouelle, 234 Ave du Brezet, 63000 Clermont-Ferrand, France E-mail: [email protected]

Abstract Sclerotinia sclerotiorum can attack most crop species except cereals. The roots, stems, leaves, terminal buds and capitula of sunflower can be infected. No complete resistance is known in cultivated sunflower but different levels of partial resistance exist, and many field tests concerning each plant part have been developed. There do not appear to be any host genotype-pathogen isolate interactions, so resistance should be durable. Heritability is moderate, with both additive and interaction effects. Many QTL have been mapped, a few are widely found, but many are limited to certain F2/RIL populations and additional QTL have been found for hybrids under natural attack. Most QTL each explain only about 10% of the phenotypic variability observed. Resistance thus appears truly polygenic and recurrent selection has been efficient in improving resistance levels. To obtain further increases in resistance, two subjects appear of importance. Firstly improving knowledge on the characters involved in resistance, both to define which origins and QTL already known in cultivated sunflower, are complimentary and useful to combine in breeding programmes, and secondly to identify new sources of resistance. Wild Helianthus species, especially perennials, have been suggested as good sources of resistance, but interspecific hybridisation is a difficult procedure and it would be a great help to define the characters which can be incorporated in cultivated sunflower and to be able to follow them over several generations of introgression. Key words: breeding, inheritance, introgression, quantitative resistance, QTL, tests Introduction Sclerotinia sclerotiorum, white rot or wilt, appears to be able to attack all crops except cereals and grasses and causes economic losses when weather conditions are favourable for infection. Recent research papers on resistance to this disease have concerned not only sunflower, soybean and rapeseed, but also peanut, haricot bean, pea, chickpea, potato, pepper, tomato, ornamentals, carrot, lettuce and satsuma! So do research results on one crop help in research on other crops? Since cereals are not hosts, could knowledge of why they are not attacked help in the search for resistance in susceptible crops? Resistance tests Compared with other susceptible crops, sunflower has the particularity that not just one plant part can be infected; roots and stem bases, adult leaves and stems, terminal buds and capitula can all be attacked by Sclerotinia. The resistances to each type of attack generally appear to be different, some sunflower varieties widely grown in France have been observed to be particularly susceptible to one form of the disease but quite satisfactory for other forms. Examples were Vidoc for terminal bud attack, and Albena for mid-stem attack. This made it necessary to develop tests to determine resistance levels for each type of attack. Most of these tests used inoculum in the form of mycelium, either on agar, toothpicks or cereal grains (Gulya et al, 2008) (which means that, in the right conditions, cereals can be infected) but for capitulum attack, we use suspensions of ascospores sprayed on open florets to repeat quite closely the natural cycle (Vear and Tourvieille, 1988). There is still no satisfactory test for terminal bud attack, it appears difficult to dampen artificially the apex of small plants to make infection possible without washing off any ascospores which have been deposited. Results concerning this type of attack have all been obtained from observations of natural attack (Achbani et al, 1996). These tests were developed from 1975 to 1990 and are applied on plants at their naturally most susceptible stage, generally in the field, except for one in the greenhouse for root attack (Grezes-Besset et al, 1993) and 47

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one measuring mycelium extension on harvested capitula in a growth chamber (CastaZo et al, 1993). We found that the tests we tried on seedlings were not correlated with field reaction. Many similar tests, especially with mycelium, have been developed for other crops, but use of ascospores appears to be rather rare. However, it is striking that research on Sclerotinia resistance still continues to search for tests, mainly on seedlings, that would be cheaper and easier to apply. The need for this research shows that there is not yet enough knowledge on the underlying control of reaction to Sclerotinia to know exactly what should be measured. For mycelium tests, to have quite rapid growth on leaves or capitula, it is best to use a Sclerotinia isolate derived directly from sunflower plants rather than one grown since the previous season on artificial medium. Ascospores are produced from sclerotia harvested in previous years, in the field or from capitula infected with mycelium. When 16 inbred sunflower lines were infected with 10 different Sclerotinia isolates, although differences in isolate aggressiveness were observed there were no significant sunflower genotype - Sclerotinia isolate interactions, (Vear et al, 2004). Thus, resistance can be considered as truly “horizontal” and although only partial, it should be durable. Inheritance of resistance As might be expected for reaction to a pathogen without specific host-parasite interactions, resistance to Sclerotinia is generally partial and quantitative, showing a continuous range of reaction levels. One possible exception could be in runner beans, but results published for this species are quite comparable with those we have obtained for terminal bud attack on sunflower. Schwartz et al (2006) report a single gene for resistance in Phaseolus coccineus, for rate of mycelium extension on the stem. The 3:1 segregations in F2 progeny were obtained by dividing disease levels (1-9) into resistant (1-5) and susceptible (6-9) according to parental values. Concerning sunflower, we observed natural terminal bud attack on a population of 150 F3 progenies. The resistant parent showed less than 5% attack, the susceptible parent 30% and 39/150 F3 families as much or more symptoms than the susceptible parent, not different from a quarter. It could thus be suggested that resistance was dominant with a single gene segregation but the distribution was not bimodal (Figure 1) and when QTL were calculated, 6 different linkage groups showed significant QTL (Bert et al, 2004). Apart from these exceptions, at present in the main crop species, the quantitative resistance model appears most applicable. For most of the major crops, tests or observations of natural attack have been used to measure heritability and then to search for QTL controlling reaction. For sunflower, both additive and dominance effects are observed and highest levels of heredity for tests that are rapid and do not depend much on environmental factors. Bert et al (2004) presented a summary of QTL for capitulum resistance observed on 6 different F3 populations. Most QTL, especially those calculated for two or more years of results, explained less than 20% of phenotypic variability. Fourteen of the 17 linkage groups of sunflower appear involved, providing evidence for a polygenic basis for resistance. The strongest QTL, with the favourable allele from the INRA line PAC1, explaining 50% of variation in a cross with a very susceptible line and 15% in a cross with a different highly resistant line, mapped close to a Protein-Kinase gene which could have been a good candidate for control of resistance (Gentzbittel et al, 1998). However, this QTL has not been found in other populations, even when the resistance source came from recurrent selection of a population for which PAC1 was one of the constituents and when the parents showed polymorphism for the PK gene. Why this should be is not clear. The most common QTL is found linked to a recessive branching gene b1 (Putt, 1974), which is present in most sunflower restorer lines in order to give pollen production over a long period but when crossed with unbranched “female” lines gives unbranched hybrids. For some years, it appeared possible that the apparent resistance was due to the branching phenotype, since branched plants have small capitula which dry more quickly than the unbranched lines. However, Jouan et al (2000) and Hahn (2002) found that some branched lines showed more rapid mycelium extension than some unbranched lines and, in a study involving both ascospore infections of an RIL population, with 50% branched lines, and field observations of their unbranched hybrids, 48

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the QTL linked to branching showed its effects in the hybrids (Figure 2, Vear et al, 2008). The existence of a genetic effect linked to the branching gene has further been confirmed by a study in progress on introgression lines, which have shown both highly resistant and highly susceptible branched genotypes.

Figure 1. Distributions of (FU x PAZ2)F3 progenies for latency index after ascospore infections and for natural terminal bud attack (square root of %). From Bert et al, 2004. The QTL found depend on the resistance measurement used, in sunflower and in other crops. Often this is rate of mycelium extension, which CastaZo et al (1993) found to be correlated significantly in different sunflower plant parts. The ascospore test on capitula repeats more closely natural attack and more factors are likely to be involved, concerning both the probability that the spores will be able to form a colony, with or without tissue penetration, and then changes in the capitulum during maturation which allow mycelium to spread and symptoms to appear only from 2 to 8 weeks after infection. At first, it appeared possible to distinguish percentage infection and delay in symptom appearance, but all the mapping studies gave similar QTL for the two observations. Susceptible genotypes show a high percentage attack with symptoms that appear quickly (Gentzbittel et al, 1998, Bert et al, 2004). For the hybrids observed under natural attack, in addition to the QTL found for RIL, some QTL were mapped on other linkage groups. One of these was on the same LG as a QTL for maturity date but there no were co-locations with QTL for plant height, which Leclercq (1975) suggested to have a favourable effect on capitulum attack in the field, perhaps because of the distribution of ascospores above the ground. Breeding for Sclerotinia resistance For sunflower, conventional breeding, mostly by pedigree selection, has shown considerable success, with 60% less attack of modern varieties compared with those of 1970 (Vear et al, 2003). Recurrent selection increased latency index by 100 % and reduced field attack of hybrids by 45% (Vear et al, 2007). Present research comparing a sunflower core collection and lines bred for their resistance confirms this improvement. It could be that, the absence of any chemical control for sunflower has resulted in effort on genetic control, and therefore more improvement than, for example rapeseed, where crops have been protected by spraying. In the USA and Canada there is a multi-crop Sclerotinia initiative (http://www.whitemoldresearch.com/) and also considerable research in Argentina, especially on sunflower. However, in spite of these improvements, for most forms of attack, if conditions are very favourable, Sclerotinia rot appears. So, what should we be looking for? Possible bases of resistance and molecular research There remains the question of whether complete resistance exists and whether we should be looking for it.. The examples taken for possible major gene resistance again apply. One of the 49

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aims of the bean research project is incorporating the complete resistance of runner bean into French bean. Although the test method used, with direct inoculation by mycelium, showed that runner bean are not immune to Sclerotinia, it may be that, in the field, they are never attacked. Many cultivated sunflower genotypes never show terminal bud attack, so it could also be considered as complete resistance. It could be that testing methods, which jump some infection stages make infection possible when it would not be naturally. However, complete resistance appears unlikely in the case of types of Sclerotinia attack which depend on the presence of senescent tissues to give the pathogen a nutrient base on which to produce mycelium. One example is rapeseed , where Sclerotinia infects senescent petals fallen onto leaves and then the disease spreads from infected leaves to the main stem. Capitulum rot of sunflower is intermediate, infection occurs during flowering, when there is generally pollen, nectar or rapidly necrosing florets but, according to resistance level, symptoms only appear from 2 to 8 weeks later. It could be said that sunflower capitula are not susceptible to Sclerotinia at flowering, but become so as plants mature, perhaps because the enzyme pathways become less active.

Figure 2. QTL for sunflower capitulum resistance to Sclerotinia in (XRQ x PSC8) RIL population and hybrids with tester lines. b1 gene : ramif on LG10. (from Vear et al, 2008) 50

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The most successful use of molecular techniques is the transfer of a QTL from runner bean into French bean by marker assisted selection (MAS) (Ender et al, 2008) In all other cases, mapping has not yet been precise enough and percentage explanation of variability too small for MAS to be efficient. For sunflower, soybean, lettuce, tomato and oilseed rape, an oxalate oxidase (OXO) gene has been introduced from barley, wheat or another fungal species by genetic engineering. It gave reductions of symptoms in every crop (Lu, 2000; Hu et al. 2003; Dias et al 2006, Walz et al., 2008, Dong et al, 2008). However, since GMO sunflowers are not, or very little developed, it would be interesting to know whether variation for this gene or its regulation occurs in sunflower or its wild relatives. It is not clear whether this OXO gene is the reason for no Sclerotinia attack on cereals. It would be useful to have information on whether there are definite pathways which make attack impossible in Poaceae or whether it is a question of absence of susceptible tissues (although a soft young maize cob and the senescing silks would appear as ideal entry points for Sclerotinia). Work in progress on the reaction of Arabidopsis mutants to Sclerotinia infection should provide some answers about the genes and enzyme pathways involved (Guo and Stotz, 2007) and whether the quantitative basis of resistance depends on several genes affecting different parts of the same pathway or whether several different pathways are involved. Fine mapping of the strongest QTL in crop species should make it possible to determine which of these genes could be possible candidates for the resistance at present available and what polymorphism exists. Association studies should also provide some information on the genes underlying the differences between more resistant and more susceptible genotypes among cultivated lines. In addition, knowledge of pathways involved in Arabidopsis could give some ideas for research on variability for other, different genes, in wild relatives of crops. Introgression from related species Sunflower geneticists and breeders are lucky in the potential resource of about 40 wild Helianthus species, including wild H.annuus. The annual species have not shown any particular resistance to Sclerotinia, but some perennial species have been found quite difficult to infect. The best resistance to mycelium growth varies between species according to plant part involved: for leaves some cultivated Jerusalem artichoke (H.tuberosus) clones were the best (Tourvieille et al, 1997), for mid-stem, Cerboncini et al (2002) found H.maximiliani to be the most resistant, whereas for capitulum attack, H.resinous and H.rigidus were the most difficult to infect (Serieys 1987), their small capitula drying before symptoms appeared. Before undertaking large scale introgression programmes, it will be important to determine which factors could be transferred to cultivated sunflower, the resistance of small capitula must be transferable to large heads of hybrid varieties. Rönicke et al (2004) reported following fragments of H.maximiliani genome during an introgression programme by AFLP, but without knowing whether interesting genes from the wild species were being retained. For greatest efficiency, it will be necessary to know whether the wild species in question can provide almost complete resistance or different mechanisms which can be combined with resistances in cultivated sunflower and to identify markers for these genes, to be able to select them during the introgression process. Conclusions All these questions add up to a lot of research, but there are two points that could speed up success. One is that perhaps we are going to find that the same underlying mechanisms are involved in Arabidopsis and in many crops, so that effort on one species will help for others. The second is that plant breeders always try to make improvements without waiting until they understand the processes involved, and there could be a breakthrough somewhere simply from studying many plants infected with Sclerotinia. Acknowledgements I would like to thank P.Vincourt for helpful comments on this paper. 51

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References Achbani EH, Vear F, Tourvieille De Labrouhe D. (1996) Resistance of sunflower (Helianthus annuus L.) to terminal bud attack by Sclerotinia sclerotiorum (Lib.) de Bary. E J Plant Pathol,102: 421-429. Bert PF, Deschamp-Guillaume G, Serre F, Jouan I, Tourvieille de Labrouhe D, Nicolas P, Vear F. (2004) Comparative genetic analysis of quantitative traits in sunflower 3. Characterisation of QTL involved in resistance to Sclerotinia sclerotiorum and Phoma macdonaldii Theor Appl Genet 109: 865-874 Castaño F, Vear F, Tourvieille de Labrouhe D. (1993) Resistance of sunflowers to different forms of attack by Sclerotinia sclerotiorum and relations with some morphological characters. Euphytica 68: 85-98 Cerboncini C, Beine G, Binsfeld P, Dresen B, Peisker H, Zerwas A, Schnabl H. (2002) Sources of resistance to Sclerotinia sclerotiorum (Lib) de Bary in a natural Helianthus gene pool. Helia 25:167-176. Dias, BBA, Cunha WG, Morais LS, Vianna G.R, Rech E L, De Capdeville G, Aragao F JL.(2006) Expression of an oxalate decarboxylase gene from Flammulina sp in transgenic lettuce (Lactuca sativa) plants and resistance to Sclerotinia sclerotiorum Plant Pathology 55: 187-193 Dai, FM, Xu T, Wolf GA, Hai ZH. (2006) Physiological and molecular features of the pathosystem Arabidopsis thaliana L.-Sclerotinia sclerotiorum Libert. J Integrative Plant Biology 48: 44-52 Dong,XB, Ji RQ, Guo XL,Foster SJ, Chen H, Dong C, Liu Y, Hu Q, Liu S. (2008)Expressing a gene encoding wheat oxalate oxidase enhances resistance to Sclerotinia sclerotiorum in oilseed rape Planta 228: 331-340 Ender M, Terpstra K, Kelly JD.(2008) Marker-assisted selection for white mold resistance in common bean. Molecular Breeding, 21: 149-157 Gentzbittel L, Mouzeyar S, Badoui S, Mestries E, Vear F, Tourvieille de Labrouhe D, Nicolas P.(1998) Cloning molecular markers for disease resistance in sunflower, Helianthus annuus L. Theor Appl Genet 96: 519-525 Grezes-Besset B, Tournade G, Arnauld O, Urs R, George P, Castellanet P, Toppan A (1993)A greenhouse method to assess sunflower resistance to Sclerotinia root and basal stem infections Plant Breeding112:215-222 Guo XM, Stotz H. (2007) Defense against Sclerotinia sclerotiorum in Arabidopsis is dependent on jasmonic acid, salicylic acid, and ethylene signaling. Molecular Plant-Microbe Interactions 20: 1384-1395 Gulya T, Radi S, Balbyshev N. (2008) Large scale field evaluations for Sclerotinia stalk rot resistance in cultivated sunflower. Proc 17th Int Sunflower Conf, 8-12/6/2008 Cordoba, Spain: 175-179. Hahn V.(2002) Genetic variation for resistance to Sclerotinia head rot in sunflower lines FCR 77:153-159 Hu X, Bidney D, Yalpani N, Duvick J, Castra O, Folkerts O, Lu G. (2003) Overexpression of a gene encoding hydrogen peroxide-generating oxalate oxidase evokes defense responses in sunflower Plant Phys 133:170-181 Jouan I, Bert PF, Perrault A, Tourvieille de Labrouhe D, Nicolas P, Vear F. (2000) The relations between the recessive gene for apical branching (b1) and some disease resistance and agronomic characters Proc.15th Int. Sunflower Conf., Toulouse, France , 12/16/06/2000, K54 - K59 Lu G (2002) Engineering Sclerotinia sclerotiorum resistance in oilseed crops. Afric J Biotechnology 2:509-516 Lerclercq (1973) Influence des facteurs héréditaires sur la résistance apparente du tournesol à Sclerotinia sclerotiorum. Ann Amel Pl 23:279-286 Putt ED. (1964) Recessive branching in sunflowers. Crop Sci 4: 444-445 Rönicke S, Hahn V, Horn R, Gröne I, Brahm L, Schabl H, Friedt W. (2004) Interspecific hybrids of sunflower as a source of Sclerotinia resistance Plant Breeding 123:152-157 Serieys H (1987) FAO sunflower subnetwork report 1984-1986. In Skoric D ed Genetic evaluation and use of Helianthus wild species and their use in breeding programmes. FAO Rome Italy:1-23. Schwartz HF, Otto K, Teran H, Lema M, Singh SP. (2006) Inheritance of white mold resistance in Phaseolus vulgaris x P-coccineus crosses Plant Disease 90: 1167-1170 Tourvieille D, Mondolot-Cosson L, Walser P, Andary C, Serieys H. (1997) Relations entre teneurs en composées caféolyquiniques de feuilles et résistances de Helianthus spp. à Sclerotinia Helia 20:39-50 Vear F, Tourvieille de Labrouhe D. (1988) Heredity of resistance to Sclerotinia sclerotiorum in sunflower. II. Study of capitulum resistance to natural and artificial ascospore infections. Agronomie 8: 503-508 Vear F, Willefert D, Walser P, Serre F, Tourvieille de Labrouhe D.(2004) Reaction of sunflower lines to a series of Sclerotinia sclerotiorum isolates. Proc. 16thInt Sunflower Conf., Fargo, USA. 1: 135-140. Vear F, Bony H, Joubert G, Tourvieille de Labrouhe D, Pauchet I, Pinochet X. (2003) 30 years of sunflower breeding in France. OCL 10: 66-73 Vear F, Serre F, Roche S, Walser P, Tourvieille de Labrouhe D. (2007) Improvement of Sclerotinia sclerotiorum head rot resistance by recurrent selection of a restorer population. Helia 30: 1-12 Vear F, Jouan-Dufournel I, Bert PF, Serre F, Cambon F, Pont C, Walser P, Roche S, Tourvieille de Labrouhe D, Vincourt P (2008) QTL for capitulum resistance to Sclerotinia sclerotiorum in sunflower. Proc 17th Int Sunflower Conf, 8-12/6/2008 Cordoba, Spain: 605-610 Walz AN, Zingen-Sell I, Loeffler M, Sauer M. (2008) Expression of an oxalate oxidase gene in tomato and severity of disease caused by Botrytis cinerea and Sclerotinia sclerotiorum Plant Pathology, 57: 453-458

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BREEDING FOR PROTEIN STABILITY AND AMINO ACID CONTENT IN SOYBEAN James H. Orf1, Maria A. Larriera2, Eliza-Jane M. Anderson2 1

University of Minnesota, Department of Agronomy and Plant Genetics, 411 Borlaug Hall, St. Paul, MN 55108 USA 2 Monsanto Company, 700 Chesterfield Parkway North, St. Louis, MO 63198 USA E-mail: [email protected]

Abstract Protein content and the amino acid composition of protein in soybean make it a valuable crop throughout the world. The stability of protein and oil concentration was determined using two populations (a total of 192 lines) grown in 2005 and 2006 at five locations in the upper Midwest. Site regression analysis (SREG), as well as several other models were used to determine the stability of protein, oil, protein plus oil and grain yield. The environmental and genotypic main effects were the most important sources of variation for the traits studied. A considerable portion of the lines outperformed the check cultivars for stability across years and locations. A second study used three populations (a total of 240 lines) grown in 2000 and 2001 to estimate the heritability of 9 amino acid levels in soybean. Realized heritability estimates ranged from low to moderate while narrow sense heritability ranged from low to high. The results of these studies suggest that plant breeders can make progress in selecting for protein stability as well as increasing amino acid levels in soybean. Key words: amino acids, heritability, protein, site regression analysis, soybean, stability. Introduction Soybean [Glycine max (L.) Merrill] is a very important crop on a world-wide basis. The amount of protein and oil in soybean seed accounts for most of the economic value of the crop. Greater than 95% of all soybeans produced are processed. The main products obtained from soybean seed are soybean meal and soybean oil. Soybean oil is mainly used for various human food products, although recently it has also been used to produce biodiesel. Soybean meal is generally used as feed for animal production. Even though soybean is classified as an oilseed, it is really a major source of protein. In fact from 100 kg of soybean seed the processor obtains about 18 kg of soybean oil and 80 kg of soybean meal. This meal generally contains 44% to 48% protein. From a nutritional point of view soybean seed (and thus the soybean meal) has an amino acid content that is fairly well balanced for humans and most animal species. Breeding for protein quantity (concentration) has been a consideration in many public and private soybean breeding programs in the U.S. for many years, especially in the more northern soybean growing areas. It has been reported that lower temperatures and greater climate fluctuations may contribute to the low and inconsistent seed protein concentrations (Hurburgh et al., 1990; Pazdernik et al., 1997). Over the years soybeans from Minnesota have been reported to be 15 to 20 g kg-1 lower in protein than states located to the south and east and have a standard deviation of about 10g kg-1 (Hurburgh et al., 1990; Piper & Boote, 1999; Yaklich et al., 2002). Thus soybean breeders not only need to have a goal of higher protein content but also protein concentration that is more stable across years and locations. The concept of stability has more than one interpretation (Lin et al., 1986; Becker & Leon, 1988). From a breeding perspective (and for the sake of this discussion) the dynamic concept of stability will be used; that is where stable genotypes show little deviations from the mean response of all genotypes to the environments (Lin et al., 1986; Becker & Leon, 1988). Thus the dynamic concept of stability is a relative measure of stability that depends not only on the environment but also on the other genotypes included in the evaluation. No studies on protein stability in soybean have been reported. Breeding for protein quality, that is the amino acid content (and really only the essential amino acid content), is only beginning in soybeans since until recently there has not been an inexpensive, rapid method available to evaluate large numbers of breeding lines. A good quality pro53

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tein has a good balance of essential amino acids and a poor quality protein is deficient in one or more of the essential amino acids. The essential amino acids are generally considered as arginine (ARG), cysteine (CYS), histadine (HIS), isoleucine (ILE), leucine (LEU), lysine (LYS), methionine (MET), phenylalanine (PHE), threonine (THR), tryptophan (TRP) and valanine (VAL). The most important amino acids, as far as soybean is concerned, are CYS, LYS, MET and THR (Singh et al., 1992). There have been only a few reports of studies investigating the heritability or other genetic effects of amino acids in soybean (Burton et al., 1982; Serretti et al., 1994; Panthee et al., 2005). Burton et al. (1982) reported that increasing protein concentration using recurrent selection did not change methionine levels. The research study by Serretti et al. (1994) showed that there were amino acid differences between high protein and normal protein lines but only modest differences among normal protein lines. Panthee et al. (2005) identified QTL’s associated with methionine and cysteine. The objectives of this research were to i) determine the stability of seed protein concentration in two recombinant inbred populations across a wide range of Minnesota and Iowa locations and ii) to obtain parent-offspring estimates and broad sense heritability estimates for the essential amino acids in three soybean populations. Materials and Methods The two populations used for the stability research were ‘Lambert’ x PI132217 (L-PI) and ‘Proto’ x PI132217 (P-PI) (Orf & Kennedy, 1994a; Orf et al., 1991). There were 98 recombinant inbred lines in the L-PI population and 94 in the P-PI population. PI132217 is a determinate maturity group 00 plant accession identified as having good seed protein stability (Zhou & Westgate, 2002). The F1 crosses were made in 1999 and plants were advanced from the F1 to the F4 generation by single seed descent (Brim, 1966). A total of 561 F4 plants were randomly selected in 2002, individually threshed, and planted in 2003 in single row at Rosemount, MN. In 2004 192 F4:5 lines with adequate seed for further studies were increased in single rows at Rosemount and Waseca, MN. The 192 F4:6 lines were divided into four sets of 48 lines based on maturity. They were evaluated in 2005 with eight check cultivars [Lambert, Proto, PI132217, ‘MN0201’ (Orf & Denny, 2004), ‘Surge’ (Scott & Orf, 1998), ‘Toyopro’ (Orf et al., 1997), ‘Parker’ (Orf & Kennedy, 1994b) and ‘MN2001SP’] in a randomized incomplete block design (IBD) (Federer, 1955) with three replicates in four blocks at five locations: Lamberton, Rosemount, St. Paul, Waseca, MN and Humboldt, IA. In 2006 all F4:7 lines plus check cultivars were evaluated in an IBD with three replicates in four blocks at Lamberton, Rosemount and Waseca, MN. Plots were 2.7 m2 with two rows, each 1.8 m long with 0.76 m between rows. The planting rate was 33 seeds m-1 row-1. Planting dates in 2005 were 2 June at Lamberton, 7 June at Rosemount, 3 June at St. Paul, 31 May at Waseca and 26 May at Humboldt. In 2006 the planting dates were 12 May at Lamberton, 9 June at Rosemount, and 23 May at Waseca. The end-trimmed plots were machine harvested and weighed (weight adjusted to 130 g kg-1 moisture). Protein was measured on a 250g whole seed sample by near infrared spectroscopy (NIRS) on a PERTEN 7200 diode array instrument and expressed as g kg-1 after adjustment to 130 g kg-1 moisture. Variance components were estimated for protein concentration and seed yield to investigate the relative contribution to the total variability of genotype, environment and genotype-environment interaction. We used the Restricted Maximum Liklihood (REML) method using the Average Information algorithm implemented as ASReml (Gilmour et al., 2002). Environments were defined as location-year combinations. All factors were considered random effects. Site regression analysis SREG (Cornelius et al., 1996; Crossa & Cornelius, 1997) was used to estimate stability. SREG is a linear-bilinear model that uses analysis of variance for the environmental main effects and principal component analysis for the main effect of genotype plus G x E interaction (Crossa et al., 2002). The biplot technique developed by Gabriel (1971) was used to show the inter-unit distances and clustering of units as well as variances, co-variances and correlations of the variables. In the SREG biplot markers for genotypes and environments were plotted on a 54

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graph for the first principal component term (PC1 or primary effects) on the x-axis and the second principal component term (PC2 or secondary effect) on the y-axis. The genotypes and environments are represented as vectors from the origin to the end points as indicated by their markers. The angle between the genotypic vector and the environmental vector represents the genotypic response (Crossa et al., 2002). The phenotypic correlation of the performance of two genotypes (or environments) is approximated by the cosine of the angle between the two vectors (Yan et al., 2001; Yan et al., 2007). The SREG analysis and the biplots were performed in SAS (SAS, 2003) using the programs developed by Burgueno et al. (2000) and Vargas & Crossa (2000). Three crosses were used for the heritability study. They were M91-198009 x C1937 (designated 181) ‘Lambert’ x M91-198014 (designated 184) and M93-401031 x M92-988 (designated 187). M91-198009, M91-198014, M93-401031 and M92-988 were breeding lines from the University of Minnesota soybean breeding project and C1937 was a breeding line from the USDA-ARS soybean project located at Purdue University. From each population 80 F2 plants were randomly selected and harvested (1999). The seed from each plant was planted in a 2m row in Chile for seed increase. The F2:4 seed was planted (2000) at four Minnesota locations, Lamberton on 24 May, Morris on 23 May, Rosemount on 12 June and Waseca on 26 May in single row plots 3.5m long with 0.76 m row spacing with three replications in a randomized complete block design (RCBD). The plots were machine harvested. Seed was sent to Chile and planted in a RCBD with 2m single rows with 0.76m between rows and three replicates. The seed in Chile was threshed with a stationary plot thresher. The F2:6 seed was planted in 2001 on May 15 at Lamberton, 18 May at Morris, 5 May at Rosemount, and 30 May at Waseca in 3.5 m single rows, spaced 0.76 m apart in an RCBD with 3 replications and again machine harvested. The seed from all harvests (1999/2000 Chile, 2000 Minnesota, 2000/2001 Chile, 2001 Minnesota) was ground using a Kinfetec 1095 sample mill and analyzed for protein content and amino acid content using a Foss 6500 near infrared reflectance spectrometer. The levels of cysteine were not predicted due to the lack of a robust NIRS equation. Parent-offspring regression estimates for protein and the essential amino acids were calculated using SAS (SAS, 2003). Estimation of variance components for protein and essential amino acids for each population were calculated using the Proc Varcomp procedure of SAS (SAS, 2003). Broad sense heritability estimates were calculated using the equation reported by Halluner & Miranda (1988). Results and Discussion In the stability study the environmental (year-location combinations) and genotypic main effects were the most important sources of variation for the traits under study (data not shown). Genotype accounted for 38% and 13% of the total variation for protein concentration and yield, respectively. While environment explained 48% and 41% for protein and yield and genotype-environment explained 6% and 9% of the variation for protein concentration and yield, respectively. Other interactions were relatively small. The relative contributions of the genotypic main effect and its interactions is reflected in the heritability on an entry mean basis which was 68% for protein concentration and 21% for yield. These values are similar to those reported by Brim (1973) and indicate that the environment had a greater influence on yield than on protein concentration. As expected, protein concentration had a negative phenotypic correlation with yield (r = -0.43, p < 0.0001). The SREG analysis provided information on stability and adaptation of lines with regard to protein concentration. Principal component 1 (PC1) explained 83.4% of the G+GxE variation and was highly correlated (r=0.996) with the protein concentration genotypic mean. This allows the identification of superior genotypes using the SREG biplot (Crossa & Cornelius, 1997). Principal component 2 (PC2) accounted for 5.6% of the G+GxE variation and represents the genotypes protein stability and adaptation. Genotypes having a PC2 near zero are stable (Yan et al., 2001). The environmental PC1 scores had the same sign indicating no significant crossover interaction (Cornelius et al., 1996). The environmental PC2 scores had both positive and negative values indicating GxE interaction due to the disproportionality of genotypes response across envi55

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ronments (Yan et al., 2007). From the analysis 19 lines from each population were identified as stable. The stable genotypes had a wide range of seed protein concentration (343 to 404 g kg-1) which indicates that protein stability is not associated with protein concentration per se (Table 1). Thus it should be possible to select stable genotypes for protein concentration regardless of the level of protein in the seed. Table 1. Mean, standard deviation (SD), minimum (Min) and maximum (Max) of protein concentration and yield of the populations, averaged over reps, locations and years. Trait

Unit

Protein Yield

kg-1

L-PI

g kg ha-1

Mean 371.77 2926

SD 13.49 325

P-PI

Min 343.13 2150

Max 405.75 3622

Mean 386.70 2683

SD 16.89 324

Min 346.70 1898

Max 424.38 3533

In general SREG analysis effectively captured the genotypic main effects, the genotype-year and the genotype-location interaction patterns. Thus this analysis provided information that could be used in a plant breeding program to select for stable genotypes for protein concentration with broad adaptation. The fact that lines from both populations gave stable protein concentrations indicates that genes for conferring protein stability in PI132217 were able to be transferred to both genetic backgrounds: Lambert (high oil and yield, average protein) and Proto (average oil and yield, high protein). The study on amino acid concentration using three populations had differing means and ranges for the different essential amino acids (Table 2). Significant line effects were seen in all three populations for protein content, ARG, ILE, LEU, LYS and THR and in populations 184 and 187 for HIS, PHE and VAL. There were no significant line effects for MET. Table 2. Population means and ranges (minimum (Min) and maximum (Max.)) for experimental lines for essential amino acids (g kg-1 total protein, protein and oil (g kg-1 of whole seed), averaged over replications, locations and years. Essential Amino Acids ARG HIS ILE LEU LYS MET PHE THR VAL Protein Oil

Population 181 Mean

Min.

Max.

8.09 2.66 4.49 8.55 8.06 1.31 4.62 3.51 3.42

7.84 2.55 4.39 8.39 7.87 1.24 4.48 3.36 3.29

8.44 2.76 4.61 8.60 8.12 1.37 4.78 3.65 3.53

442.63 199.09

424.81 188.98

466.46 211.19

Population 184 Mean

Min.

Max.

g kg-1 of total protein 7.67 7.51 7.88 2.72 2.66 2.80 4.62 4.54 4.70 8.67 8.54 8.79 8.38 8.24 8.42 1.32 1.27 1.38 4.43 4.29 4.55 3.69 3.53 3.84 3.28 3.18 3.38 -1 g kg of whole seed 428.67 410.39 445.56 207.26 198.42 216.57

Population 187 Mean

Min.

Max.

7.97 2.77 4.45 8.44 7.98 1.34 4.39 3.60 3.26

7.74 2.69 4.34 8.27 7.88 1.28 4.22 3.48 3.13

8.15 2.85 4.57 7.96 8.11 1.40 4.53 3.73 3.38

438.15 197.23

416.64 185.70

459.13 205.98

The parent-offspring regression values for the three populations are shown in Table 3. A wide range of estimates were observed for each amino acid. The parent-offspring estimates for protein and oil were similar to those reported in the literature (Brim & Burton, 1979; Helms & Orf, 1998; Johnson & Berin, 1963; Pazdernik et al., 1996; Shannon et al., 1972). Broad sense 56

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heritability estimates ranged from high to low (Table 4). Moderate to high estimates were obtained for ARG, ILE, LEU LYS, PHE, THR, and VAL. Low estimates were obtained for HIS and very low estimates for MET. The protein estimates were high as reported by others (Burton, 1987). Conclusions Protein concentration in soybean is of continuing interest and study by soybean researchers. In a two population study, soybean lines were identified that had stable protein concentrations over a wide range of protein and yield levels. In the amino acid study parent-offspring regressions and broad sense heritabilities were moderate to high for most essential amino acids except methionine. Breeding for stable protein concentration and/or improved essential amino acid levels is an achievable goal in soybean. Table 3. Parent (MN00)-offspring (MN01) regression values for essential amino acids, protein and oil for each population (averaged over replications and locations). Population 181 184

ARG 0.541‡ 0.436‡

187 Population 181 184 187

0.585‡ MET 0.091 0.240 0.366

Essential Amino Acids HIS ILE LEU 0.090 0.584‡ 0.447‡ 0.084 0.463‡ 0.322†

LYS 0.444‡

0.550‡ THR 0.231† 0.497‡ 0.392†

0.230t Protein 0.716‡ 0.715‡ 0.822‡

0.254t PHE 0.214 0.437‡ 0.233t

0.527‡ VAL 0.106 0.338‡ 0.324†

0.121t Oil 0.746‡ 0.665‡ 0.696‡

t, †, ‡ - Significant at P=0.05, P=0.01, and P=0.001 respectively.

Table 4. Broad sense heritability estimates for essential amino acids, protein and oil for each of the three populations (Pop.) analyzed individually. Essential Amino Acids ARG HIS ILE LEU LYS MET PHE THR VAL Protein Oil

Pop 181

Pop 184

Pop 187

0.890 0.301 0.697 0.591 0.691 0.308 0.413 0.580 0.330 0.954 0.932

0.721 0.152 0.605 0.479 0.442 0.288 0.706 0.652 0.626 0.943 0.879

0.829 0.323 0.673 0.620 0.270 0.591 0.709 0.520 0.614 0.968 0.921

References Becker H.C., Leon, J. (1988): Stability analysis in plant breeding. Plant Breeding, 101, 1-23. Brim C.A. (1966): A modified pedigree method of selection in soybeans. Crop Science, 6, 620. Brim C.A. (1973): Quantitative genetics and breeding. In: Caldwell B.E. (Ed.) Soybeans: Improvement, Production, and Uses. ASA, Madison, WI, 155-186. Brim C.A., Burton J.W. (1979): Recurrent selection in soybeans II: Selection for increased percent protein in seeds. Crop Science, 19, 494-498.

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CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008 Burgueno J., Crossa J., Vargas M. (2000): SAS Programs for Graphing GE and GGE Biplots. CIMMYT International, Mexico, 17. Burton J.W. (1987): Quantitative genetics: Results relevant to soybean breeding. In: Schrader L.E. (Ed.) Soybeans: Improvement, Production and Uses, 2nd Ed. American Society of Agronomy, Inc., Crop Science Society of America, Inc. and Soil Science Society of America, Inc., Madison, Wisconsin, 211-247. Burton J.W., Purcell A.E., Walter J.W.M. (1982): Methionine concentration in soybean protein from populations selection for increased percent protein. Crop Science, 22, 430-432. Cornelius P.L., Crossa J., Seyedsadr M.S. (1996): Statistical tests and estimators for multiplicative models for genotype-by-environment interaction. In: Kang M.S., Gauch H.G. Jr. (Ed.) Genotype-by-Environment Interaction. CRC Press, Boca Raton, FL, 199-234. Crossa J., Cornelius P.L. (1997): Sites regression and shifted multiplicative model clustering of cultivar trial sites under heterogeneity of error variances. Crop Science, 37, 406-415. Crossa J., Cornelius P.L., Yan W. (2002): Biplots of linear-bilinear models for studying crossover genotype x environment interaction. Crop Science, 42, 619-633. Federer W.T. (1955): Experimental Design: Theory and Application. MacMillan, New York. Gabriel K.R. (1971): The biplot graphic display of matrices with application to principal component analysis. Biometrika, 58, 453-467. Gilmour A.R., Gogel B.J., Cullis B.R., Welham S.J., Thompson R. (2002): ASReml user guide release 1.0. VSN International Ltd., Hemel Hempsted, HP1 1ES, United Kingdom. Hallauer A.R., Miranda J.B. (1988): Quantitative Genetics in Maize Breeding, 2nd Ed. Iowa State University Press, Ames, IA. Helms T.C., Orf J.H. (1998): Protein, oil and yield of soybean lines selected for increased protein. Crop Science, 38, 707-711. Hurburgh C.R. Jr., Brumm T.J., Guinn J.M., Hartwig R.A. (1990): Protein and oil patterns in U.S. and world soybean markets. Journal of the American Oil Chemists’ Society, 67, 966-973. Johnson H.W., Berin R.L. (1963): Soybean Genetics and Breeding. Norman, A.G. (Ed.) Academic Press, New York. Lin C.S., Binns M.R., Lefkovitch L.P. (1986): Stability analysis: Where do we stand? Crop Science, 26, 894-900. Orf J.H., Denny R.L. (2004): Registration of ‘MN0201’ soybean. Crop Science, 44, 691-692. Orf J.H., Kennedy B.W. (1994a): Registration of ‘Lambert’ soybean. Crop Science, 34, 302. Orf J.H., Kennedy B.W. (1994b): Registration of ‘Parker’ soybean. Crop Science, 34, 302-303. Orf J.H., Lambert J.W., Kennedy B.W. (1991): Registration of ‘Proto’ soybean. Crop Science, 31, 486. Orf J.H., Schaus P.J., Kennedy B.W. (1997): Registration of ‘Toyopro’ soybean. Crop Science, 37, 44. Panthee D.R., Pantalone V.R., Sams C.E., Saxton A.M., West D.R., Orf J.H., Killam A.S. (2005): Quantitative trait loci controlling sulfur containing amino acids, methionine and cysteine, in soybean seeds. Theoretical and Applied Genetics, 122, 161-166. Pazdernik D.L., Hardman L.L., Orf J.H. (1997): Agronomic performance and stability of soybean varieties grown in three maturity zones of Minnesota. Journal of Production Agriculture, 10, 425-430. Pazdernik D.L., Hardman L.L., Orf J.H., Clotaire F. (1996): Comparison of field methods for selection of protein and oil content in soybean. Canadian Journal of Plant Science, 76, 721-725. Piper E.L., Boote K.J. (1999): Temperature and cultivar effect on soybean seed oil and protein concentration. Journal of the American Oil Chemists’ Society, 76, 1233-1241. SAS Institute Inc. (2003): SAS/STAT User’s Guide, Version 9.1. SAS Institute, Cary, NC. Scott R.A., Orf J.H. (1998): Registration of ‘Surge’ soybean. Crop Science, 38, 893. Serretti C., Schapaugh J.W.T., Leffel R.C. (1994): Amino acid profile of high seed protein soybean. Crop Science, 34, 207-209. Shannon J.G., Wilcox J.R., Probst A.H. (1972): Estimated gains from selection for protein and yield in the F4 generation of six soybean populations. Crop Science, 12, 824-826. Singh B.K., Flores H.E., Shannon J.C. (1992): Biosynthesis and molecular regulation of amino acids in plants. America Society of Plant Physiologists, Rockville, MD. Vargas M., Crossa J. (2000): The AMMI Analysis and the Graph of the Biplot in SAS. CIMMYT International, Mexico, 39. Yaklich E.W., Vinyard B., Camp M., Douglass S. (2002): Analysis of seed protein and oil from soybean northern and southern region uniform tests. Crop Science, 42, 1504-1515. Yan W., Cornelius P.L., Crossa J., Hunt L.A. (2001): Two types of GGE biplot for analyzing multi-environment trial data. Crop Science, 41, 656-663. Yan W., Kang M.S., Ma B., Woods S., Cornelius P.L. (2007): GGE Biplot vs. AMMI analysis of genotype-by-environment data. Crop Science, 47, 641-653. Zhou R., Westgate M.E. (2002): Partitioning of sucrose into protein, oil and starch in soybean cotyledons cultured in plants and in vitro. Agronomy Abstract, 112.

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SORGHUM BREEDING: NEW AND OLD TECHNOLOGIES WORKING TOGETHER TO MOVE THE CROP INTO THE FUTURE Jeff Dahlberg1, Janos Berenji2, Robert R. Klein3, Peter Beetham4 1

2

National Sorghum Producers, 4201 N. Interstate 27, Lubbock, Texas, 79403, USA Institute of Field and Vegetable Crops, Maksima Gorkog 30, 21000 Novi Sad, Serbia 3 USDA-ARS, 2881 F&B Road, College Station, Texas, 77845, USA 4 Cibus LLC, 4025 Sorrento Valley Blvd., San Diego, California, 92121, USA E-mail: [email protected]

Abstract Sorghum [Sorghum bicolor (L.) Moench] is an ancient cereal grain. Early crop improvement efforts in sorghum were conducted by farmers, seedsmen, and some researchers who utilized individual plant selections from their heterogeneous populations as a method for maintaining desirable phenotypes. Dating to the late 1800s, the predominant tools for crop improvement in sorghum have been population improvement, inbred and pure-line development and improvement, and hybrid development. A modified marker-assisted selection pedigree program is being developed to greatly enhance the efficiency of converting sorghum from photoperiod sensitive tropical sorghums to sorghums that can be utilized in more temperate regions of the world. Another unique tool being used is a Rapid Trait Development System (RTDS™). The merging of these genomic technologies with traditional plant breeding tools offers great promise to further enhance sorghum and to potentially realize the tremendous yield potential that is inherent in sorghum, a record 24,000 kg ha-1. Key words: sorghum, diversity, hybrids, cytoplasmic-male sterility, genome, marker-assisted selection, RTDS. Introduction Several authors have discussed the systematics, origin, and evolution of Sorghum [Sorghum bicolor (L.) Moench] (de Wet & Harlan, 1971; de Wet & Huckabay, 1967; Harlan, 1975; Snowden, 1936). Dahlberg (2000) provides an excellent overview of the present-day classification. Mann et al. (1983) indicated that the origin and early domestication of sorghum took place in northeastern Africa north of the Equator and east of 10< E lat. approximately 5000 yrs ago. However, carbonized seeds of sorghum with consistent radiocarbon dates of 8000 yrs b. p. have been excavated at an early Holocene archaeological site at Nabta Playa near the Egyptian-Sudanese border (Wendorf et al., 1992). These sorghums are 3000 years older and 10 – 15< lat. further north than had been previously reported and suggests an early interest in sorghum by hunter and gathers and early agriculturalists. These early domestication events followed major trading and migratory paths of early Africans and Asians. As these early domesticated sorghum spread throughout Africa and Asia, plants were selected and dispersed throughout a broad range of environments and utilization giving rise to a widely adapted genetic base that has been further exploited throughout the agricultural process to create the current crop known as sorghum. Sorghum grain is used primarily for livestock feed and stems and foliage for green chop, hay, silage, and pasture (House, 1985) and more recently in the renewable fuels industry and into the food market as gluten-free food products. In Africa and India, it is an important part of the diet in the form of unleavened bread, boiled porridge or gruel, and specialty foods such as popped grain and beer. Syrup is made from sweet sorghum. Grain sorghum is becomming a perspective field crop in Europe for cattle feed (Berenji & Dahlberg, 2004). Broomcorn is a special type of sorghum recognizable by long panicles used for manufacture of corn brooms (Berenji & Ki{geci, 1996). This widespread utilization of sorghum was based upon its diverse genetic background. Direct Introduction The first recorded introduction of sorghum into the US was from March 24, 1757 in a letter from Benjamin Franklin to Samuel Ward. In it he describes broomcorn popular for use as hat brooms. It is clear, however, that sorghum was introduced much earlier into the Americas via the 59

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slave trade. China recorded the use of sorghum as far back as the third century in the “Records of Natural Science” by Zhanghua (Dahlberg, 2000). Painting of sorghum have been found in Farnesina, Italy in festoons dated back into the late to 1600s. These sorghums are examples of the use of a crop via direct introductions. Traditional Breeding Early crop improvement efforts in sorghum were conducted by farmers, seedsmen, and some researchers who utilized individual plant selections from their heterogeneous populations as a method for maintaining desirable phenotypes. These pure-line cultivars were selected, increased, and grown by farmers. Sorghum’s geographic and genetic variability allowed farmers to create a pool of germplasm that is one of the most diverse in all of the cereal crops. Though sorghum is essentially a self-pollinated crop, natural hybridization does occur and from these hybridizations, selections for short statured plants, sorghum with some drought tolerance, and chinch bug resistance took place in the late 1800s and early 1900s in the US. It can be argued that farmer selection of improved cultivars from naturally occurring hybridization is still the dominant “plant breeding” technique used for sorghum improvement world-wide. Hybrid Breeding Technologies It was not until 1914 when Vinall and Cron began deliberate hybridization of sorghum that sorghum improvement using scientific methods truly began (Vinall & Cron, 1921). Hand emasculation and later development of other sterile techniques, such as hot-water emasculation and plastic bag method, were the predominant methods by which these deliberate hybrids could be made. Several important cultivars were released in the US based upon deliberate crosses and selection of sorghums and this continued as the predominant form of sorghum improvement until the mid 1950s. Scientists understood the concept of heterosis through observations from these deliberate hybridizations and through work on maize. Though antherless (al) and genetic male-sterility (ms1, ms2, ms3) were reported in the 1930s, breeders such as Stephens, Quinby, and Holland understood that in order for sorghum hybrids to be commercially viable, a more robust and reliable sterility system needed to be identified (Karper & Stephens, 1936). Real gains were not realized until the discovery of cytoplasmic-male-sterility in 1954 (Stephens & Holland, 1954). Breeding technologies were forced to evolve from pure-line development to the development of hybrids using techniques described by corn breeders. The predominant plant breeding methods used in sorghum today are population improvement and inbred and pure-line development, which support the development of improved hybrids (Berenji et al., 2006). Farmers recognized the importance of hybrids and adoption was swift in the US. Hybrids moved the US national yield average from around 1.250 kg ha-1 to 2.500 kg ha-1 in just four years and were accepted on more than 90% of farms by 1960. It took only five years to reach the next plateau of 3.100 kg ha-1 or an increase of 25%. Most hybrids in the early years were of varietal crosses whereas the second plateau resulted from new germplasm specifically developed from inbreds and often containing recent plant introductions in their make-up. The advent of sorghum greenbugs in 1968 resulted in a backcross breeding program that was detrimental to new increases in yield, but it did stabilize yields from 1968-76 to approximately 3.300 kg ha-1. With the advent of biotype E greenbugs in 1980 another lag in yield gains resulted in a 15-year period, between 1985-99, which averaged 4.000 kg ha-1 (Smith & Frederiksen, 2000). Using 1930-39 as a yield base (790 kg ha-1) sorghum’s current US yield averages are now approaching 4.500 kg ha-1, which is approximately five times greater than those earlier years (USDA-NASS, 2008). These yield gains are similar to the increases seen in maize, double that of soybean and nearly double that of wheat and rice for the same time period. Motivated by the success of grain sorghum hybrids, attempts has been made to bred hybrid broomcorn (Berenji & Sikora, 2002a, 2202b) 60

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Sorghum Conversion Program By 1967 J.C. Stephens and others recognized the limits of the germplasm available in the US, especially for improving inbreds and hybrids, and formulated the Sorghum Conversion Program to introduce new germplasm sources into the US (Stephens et al., 1967). A backcrossing program, requiring fairly labor-intensive hand emasculations, was started to begin the process of conversion to photoperiod insensitive, short statured sorghums. Crosses were made during the winter months in Puerto Rico under short-day photoperiods and selection for early, short genotypes within segregating populations was undertaken under long-day, summer conditions at Chillicothe, Texas. All converted lines received four backcrosses to the original exotic variety and the nonrecurrent parent used in most cases was an early-maturing, 4-dwarf ‘Martin’ B-line, ‘BTx406’, although, ‘R3105’, ‘BTx3121’, or ‘BTx3122’ were also used in some cases. The exotic varieties were used as male parents until the third backcross when they were used as the female parent in order to recover the original cytoplasm in the converted line. The converted lines were non-sensitive to photoperiod, will mature normally in the United States, and are short statured, generally 3 or 4-dwarf in height, but occasionally 2-dwarf in height. From these converted and partially converted lines selections for drought tolerance, insect and disease resistance, and a broadening of the genetic base of the commercial hybrids developed in the US has taken place. However, this is a long, labor-intensive process that can in some cases take up to 10 years to fully convert an exotic germplasm source. Approximately 1.500 germplasm sources have been entered into the program with a full 702 accessions being converted. New Genetic Tools Marker marker systems and linkage maps. With the sequencing of the sorghum genome, the second cereal crop to be sequenced (Kresovich et al., 2005), new genomic tools are being developed to supplement traditional breeding methodologies. Initially, markers were developed using isozymes and RFLPs, but because of the ease of use and ability to generate more markers, PCR-based molecular markers are more commonly used, such as simple sequence repeats (SSR) and amplified fragment length polymorphisms (AFLP). These molecular marker systems have led to numerous linkage maps (Chittenden et al. 1994, Kong et al. 2000, Menz et al. 2002, Peng et al 1999, Rami et al. 1998). QTL markers have been published for drought resistance in sorghum and grain mold resistance (Sanchez et al. 2002, Klein et al. 2001). More recently, Casa et al. (2008) described the development of community resources and strategies for association mapping in sorghum, which attempts to link phenotypic and genotypic information using unique panels. Modified marker-assisted selection pedigree program. In an attempt to make the sorghum conversion program more efficient, a modified marker-assisted selection pedigree program is being developed to convert sorghum from photoperiod sensitive tropical sorghums to sorghums that can be utilized in more temperate regions of the world. One common concern of public and private sector sorghum scientists has been the number of generations, and thus years, required to fully convert tropical sorghums to short, photoperiod-insensitive genotypes by conventional methods. However, the number of generations required to introgress recessive photoperiod insensitive alleles can be markedly reduced by replacing phenotypic screening with molecular marker genotyping. Genotypic evaluation can be conducted at any stage of development and in any environment, which is especially useful when recessive alleles are targeted for introgression. To this end, research has been initiated in an effort to map at high resolution those genes in sorghum that are responsible for photoperiod sensitivity. Two major advantages of having access to the genome sequence of sorghum include; (a) the relative ease with which markers can be identified for high resolution mapping and (b) the speed with which candidate genes and functional mutations can be identified within a target locus. The intent of this marker-assisted selection conversion program is to use the actual functional mutation (e.g., the sequence polymorphism that conditions the photoperiod sensitive phenotype) for marker-assisted selection, or a series of tightly-linked markers flanking the gene of interest. Marker-assisted selection during the conversion process, therefore, should not be limited by the number of informative markers tagging 61

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photoperiod sensitivity, nor the recombination frequency between the molecular markers and the targeted loci. Genotypic screening for photoperiod-insensitive in the BCF2 generations. A series of activities will be conducted as a proof-of-concept study that replaces the phenotypic selection in the BCF2 generations with genotypic screening for photoperiod-insensitive. Thirty tropical accessions from Mali and the Sudan have been identified by the former leader of the Conversion Program (D.T. Rosenow) for conversion to temperate adaptation. Several major modifications in the original conversion program will be implemented in this pilot program. The most critical is that selection for introgression of recessive photoperiod insensitive alleles to be conducted in the backcross (BCF1) generation. Initially, F2 progeny from marker-selected F1 plants will be phenotyped for photoperiod sensitivity to confirm the efficacy of marker-based selection. In addition, research will test the practicality of inducing floral initiation in temperate environments using light-proof buckets to effectively reduce the day length to which photoperiod-sensitive germplasm is exposed, thereby reducing the cost associated with this program. This ‘bucket method’ has been effectively utilized by the sorghum seed industry in the past (Bruce Maunder, personnel communication), and early indications are that this methodology will permit crossing in temperate climates. Finally, with the advent of sequenced-based marker technology (e.g., genome-wide SNP arrays), the genome of converted material can be effectively characterized for recovery of the exotic parent after the final backcross generation. The former conversion program utilized four backcross generations in an attempt to recover as much of the exotic genome as possible, while retaining the photoperiod sensitivity (and dwarfism) from the temperate donor line. Recent work has indicated that despite four backcross generations, a significant percentage of the temperate donor genome remained in many converted lines (Klein et al., 2008). Hence, genome-wide genotyping, either at low (DarT arrays) or high resolution (Genome-wide SNP arrays), will allow for an assessment of the recovery of the exotic genome of material emerging from the conversion program. It is feasible that sufficient recovery of the exotic genome may be achieved in early backcross generations (BC2), and thereby expedites the release of converted materials to sorghum breeders. Rapid Trait Development System (RTDS™). RTDS is a unique technology designed to site-specifically target and induce repair of genomic DNA. It is now well documented that the molecular basis of many specific traits results from small genetic differences, or single nucleotide polymorphisms (SNPs), within critical genes. The conventional approach for developing new or improved traits involves inserting whole genes, containing these small differences, through transformation. In contrast, RTDS harnesses the cell’s inherent DNA repair system and directs a conversion (nucleotide change) at the desired location in the specified gene, restoring, removing and/or modifying normal function. This technology is not limited to manipulation of genes that code for proteins, but has demonstrated that any nucleotide sequence (regulatory, coding and non-coding) can be converted to enhance and/or reduce the function and activity of a gene product. RTDS in plant cells was initially demonstrated in a tobacco cell line known as Nt-1. The gene that was targeted and modified was the acetolactate synthase (ALS) gene (Beetham et al. 1999). In summary, by targeting the ALS gene the researchers were able to modify this gene causing the cells to become resistant to the sulfonylurea class of herbicide. This work was followed by a complementary study by researchers at Pioneer Hi-Bred International, Inc. Zhu converted a similar gene in maize (Zhu et al. 1999; Zhu et al. 2000). They also converted the tobacco ALS-equivalent gene in maize known as the acetohydroxyacid synthase (AHAS) gene, again making the cells herbicide tolerant. The subsequent progeny of these plants confirmed that the gene conversions were heritable and stable. Most modern classes of herbicide chemistry interact with important plant enzymes and in most cases these interactions have been studied in detail. The most important commercial herbicides have had their protein and substrate interactions well mapped and the underlying genetic sequences are well known that confer plants to be either susceptible of tolerant to a given herbicide. The RTDS tool is currently being applied to Sorghum targeting genes that will confer tolerance to a grass herbicide, known as SelectMax™. 62

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Summary It is clear that traditional plant breeding technologies will continue to dominate genetic improvement in sorghum. Much of the markers and/or QTLs identified in sorghum have proved to be problematic when attempting to use them outside of the populations from which they were developed (Franks 2006). Though the potential for markers is vast, there has been limited success of these technologies to applied breeding programs (Young 1999). Crops like maize and soybean are spending larges amounts of money on genomic tools and marker development; however, without greater private investment in enhancing sorghum, traditional programs utilizing inbred line selection and development will continue to drive most sorghum breeding programs worldwide. The successful merging of genomic technologies, such as the modified marker-assisted selection pedigree program and the RTDS technology, with traditional plant breeding tools offers great promise to further enhance sorghum and to realize the tremendous yield potential that is inherent in sorghum, a record 24,000 kg ha-1. References Beetham P. R., Kipp P. B., Sawycky X. L., Arntzen C. J., May G. D. (1999): A tool for functional plant genomics: Chimeric RNA/DNA oligonucleotides cause in vivo gene-specific mutations. Proceeding of the National Academy of Sciences. Plant Biology, 96, 8774–8778. Berenji, J., Dahlberg, J. (2004): Perspectives of Sorghum in Europe. Journal of Agronomy and Crop Science 1905: 332-338. Berenji, J., Dahlberg, J., Sikora, V. (2006): Celebrating 50 years of sorghum hybrids. Abstracts of the “20th International Conference of the EUCARPIA Maize and Sorghum Section”, p. 14, Budapest. Berenji, J., Ki{geci, J. (1996): Broomcorn-classical example of industrial use of sorghum. 1. European seminar on sorghum for energy and industry, p. 43-48, Toulouse. Berenji, J., Sikora, V. (2002a): Trends and achievements in broomcorn breeding. Cereal Research Communications, 30 (1-2): 81-88. Berenji, J., Sikora, V. (2002b): Utilization of hybrid vigor in broomcorn, Sorghum bicolor (L.) Moench. Cereal Research Communications, 30 (1-2): 89-94. Casa A. M., Pressoir G., Brown P. J., Mitchell S. E. Rooney W. L., Tuinstra M. R., Franks C. D., Kresovich S. (2008): Community resources and strategies for association mapping in sorghum. Crop Science, 48, 30–40. Chittenden L. M., Schertz K. F., Lin Y. R., Wing R. A., Paterson A. H. (1994): A detailed RFLP map of Sorghum bicolor x S. propinquum, suitable for high-density mapping, suggests ancestral duplication of Sorghum chromosomal segments. Theoretical Applied Genetics, 87, 925–933. Dahlberg J. A. (2000): Classification and characterization of sorghum. In: Smith, W. A., Frederiksen, R. A. (Ed.) Sorghum: origin, history, technology, and production. John Wiley & Sons, Inc. New York, New York, 99–130. de Wet J. M. J., Harlan J. R. (1971): The origin and domestication of Sorghum bicolor. Economic Botany, 25, 128–135. de Wet J. M. J., Huckabay, J. P. (1967): The origin of Sorghum bicolor. II. Distribution and domestication. Evolution, 21, 787–802. Franks C. D. (2006): The efficacy of marker-assisted selection for grain mold resistance in sorghum. A Ph.D. Dissertation, Department of Soil & Crop Science, Texas A&M University, College Station, Texas. Harlan J. R. (1975): Crops and man. Madison, Wisconsin: American Society of Agronomy. House L. R. (1985): A Guide to sorghum breeding. 2nd ed. Patancheru, A. P. 502324, India: ICRISAT. Karper R. E., Stephens, J. C. (1936): Floral abnormalities in sorghum. Journal of Hereditary, 27, 183. Klein R. R., Mullet J. E., Jordan D. R., Miller F. R., Rooney W. L., Menz M. A., Franks C. D., Klein P. E. (2008): The Effect of Tropical Sorghum Conversion and Inbred Development on Genome Diversity as Revealed by High-Resolution Genotyping. Plant Genome. doi:10.2135/cropsci2007.06.0319tpg. Klein R. R., Rodriguez-Herrera R., Schlueter J. A., Klein P. E., Yu Z. H., Rooney W. L. (2001): Identification of genomic regions that affect grain-mould incidence and other traits of agronomic importance in sorghum. Theoretical Applied Genetics, 102, 307–319. Kong L., Dong J., Hart G. E. (2000): Characteristics, linkage-map positions, and allelic differentiation of Sorghum bicolor (L.) Moench DNA simple-sequence repeats (SSRs). Theoretical Applied Genetics, 101, 438–448. Kresovich, S., Barbazuk, B., Bedell, J., Borrell, A., Buell, R., Burke, J.J., Clifton, S., Cordonnier-Pratt, M., Cox, S., Dahlberg, J., Erpelding, J.E., Fulton, T.M., Fulton, B., Fulton, L., Gingle, A., Goff, S., Hash, C., Huang, Y., Jordan, D., Klein, P., Klein, R.R., Magalhaes, J., McCombie, R., Moore, P.H., Mullet, J.E., Ozias-Akins, P., Paterson, A.H., Porter, K., Pratt, L., Roe, B., Rooney, W., Schnable, P., Steely, D.M., Tuinstra, M., Ware, D., Warek, U. (2005): Toward sequencing the sorghum genome: A US National Science Foundation-sponsored workshop report. Plant Physiology. 138(4): 1898-1902. Mann J. A., Kimber C. T., Miller F. R. (1983): The origin and early cultivation of sorghums in Africa. Texas Agricultural Experiment Station Bulletin, 1454.

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CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008 Menz M. A., Klein R. R., Mullet J. E., Obert J. A., Unruh N. C., Klein P. E. (2002): A high-density genetic map of Sorghum bicolor (L.) Moench based on 2926 AFLP, RFLP and SSR markers. Plant Molecular Biology, 48, 483–499. Peng Y., Schertz K. F., Cartinhour S., Hart G. E. (1999): Comparative genome mapping of Sorghum bicolor (L.) Moench using an RFLP map constructed in a population of recombinant inbred lines. Plant Breeding, 118, 225–235. Rami J. F., Dufour P., Trouche G., Fliedel G., Mestres C., Davrieux F., Blanchard P., Hamon P. (1999): Quantitative trait loci for grain quality, productivity, morphological and agronomical traits in sorghum (Sorghum bicolor L. Moench). Theoretical Applied Genetics, 97, 605–616. Sanchez A. C., Subudhi P. K., Rosenow D. T., Nguyen H. T. (2002): Mapping QTLs associated with drought resistance in sorghum (Sorghum bicolor L. Moench). Plant Molecular Biology, 48, 713–726. Smith C. W., Frederiksen R. A. (2000): History of cultivar development in the United States: From “memoirs of A. B. Maunder-Sorghum Breeder. In: Smith C. W., Frederiksen R. A. (Eds.) Sorghum: origin, history, technology, and production. John Wiley & Sons, Inc. New York, New York, 191–223. Snowden J. D. (1936): The cultivated races of sorghum. Adlard and Son, Ltd. London. Stephens J.C., Holland R. F. (1954): Cytoplasmic male-sterility for hybrid sorghum seed production. Agronomy Journal, 46, 20. Stephens J. C., Miller F. R., Rosenow D. T. (1967): Conversion of alien sorghums to early combine genotypes. Crop Sciences, 7, 396. USDA, National Agricultural Statistics Database (2003): Available at http://www.nass.usda.gov/ QuickStats/Create_Federal_All.jsp (verified 6 September, 2008 March, 2003). Vinall H. N., Cron A. B. (1921): Improvement of sorghum by hybridization. Journal Hereditary, 12, 435. Wendorf F, Close A. E., Schild R., Wasylikowa K., Housley R. A., Harlan J. R., Królik H. (1992): Saharan exploitation of plants 8,000 years bp. Nature, 359, 721–724. Young N. D. (1999): A cautiously optimistic vision for marker-assisted breeding. Molecular Breeding, 5, 505–510. Zhu T., Mettenburg K., Peterson D. J., Tagliani L., Baszczynski C. L. (2000): Engineering herbicide-resistant maize using chimeric RNA/DAN oligonucleotides. Nature Biotechnology, 18, 555558. Zhu T., Peterson D. J., Tagliani L., St. Clair G., Baszczynski C. L., Bowen B. (1999): Targeted manipulation of maize genes in vivo using chimeric RNA/DNA oligonucleotides. Proceeding of the National Academy of Sciences, Plant Biology, 96, 8768–8773.

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QUANTITATIVE GENETICS IN SOYBEAN: IS DOMINANCE IMPORTANT? Joseph W. Burton Soybean & Nitrogen Fixation Unit, USDA, 3127 Ligon St., Raleigh, NC 27607 Email: [email protected]

Abstract In soybeans, dominance is generally considered to be non-existent or of little importance. Because genetic variation due to dominance dissipates rapidly with inbreeding, dominance would presumably not be useful in breeding soybean cultivars which are highly inbred. Yet, there is evidence for heterosis in soybean, and inbreeding depression (evidence for dominance) has also been reported. Heterosis can have several genetic causes. These include a greater number of favorable (dominant) alleles in the F1 hybrid then in the two parents singly; linked dominant alleles that complement each other by masking less favorable alleles, and/or through duplicate gene interaction; and alleles that produce similar effects as homozygotes, but interact when heterozygous or heterologous. All of the above can be fixed in pure-lines except heterosis due to single locus allelic interaction. Thus, heterosis measured in F2 bulk performance may be a useful way to predict the value of a cross. Early generation testing may also be useful if it can be economically incorporated in a practical breeding program. Key words: dominance, epistasis, heterosis, inbreeding depression, soybean, yield Introduction Classical quantitative genetic studies with soybeans (Glycine max (L.) merr.) have tended to show that most genetic variation for seed yield to be due to additive effects and additive x additive epistasis (Brim & Cockerham, 1961; Hansen, et al., 1967). Much soybean breeding practice including single seed descent (Brim, 1966) and recurrent selection (Kenworthy & Brim, 1979; Burton et al., 1990; Rose et al., 1992) has been predicated on the theory that the preponderance of genetic variance in soybean breeding populations is additive which increases rapidly with selfing. These and related breeding methods are responsible for much of the improvement in soybean yield potential in the modern era. Genetic variation due to dominance has been generally disregarded in soybean breeding. There are several reasons for this. Foremost may be that soybean cultivars are highly inbred and to date, F1 hybrids are not produced commercially. Producing F1 seeds requires laborious hand pollinations that produce too few seeds for standard yield tests. So plant breeders rarely observe heterosis in their normal activities. And inbreeding depression, good evidence of dominance, is also rarely observed. Finally, soybean is a self-pollinated species and genetic variation due to dominance diminishes rapidly with each generation of self-pollination. Knowing that, a plant breeder probably finds dominance of little interest, seeing no obvious way to use it to advantage. It is my intention in what follows to present evidence for dominance in soybean breeding literature, focusing only on seed yield. Briefly, I will present genetic explanations that have been proposed for the presence of dominance in an autogamous species like soybean and explore ways that dominance might be useful in soybean breeding. Results from self-fertilization designs Hand pollinations are laborious. Rates of success, average about 35% of pollination attempts and each successful pollination results in only 1 to 3 seeds. Because of this, quantitative genetic experiments that provide good estimates of additive and dominance variance have not been conducted. Instead, nested self-fertilization designs were used which typically provide limited information on dominance (Cockerham, 1983). Three of these studies were published involving a total of 5 biparental populations and an analysis that considered the F2 population as the reference population for the estimates of genetic variance. Gates et al (1960) and Croissant and Torrie (1971) found only additive variance and no evidence for significant dominance in the three populations they worked with. A reanalysis of the Gates et al. (1960) data with a population of derived homozygous lines as the reference population, showed additive x additive variance to 65

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be greater than the additive variance, but standard errors on the estimates were large (Hanson and Weber, 1961). In addition to progenies of selfed generations (F3, F4 and F5) of two biparental populations, Brim & Cockerham (1961) included selfed progeny of paired F2:3 family matings in their yield tests. In both populations, estimates of additive variance for yield were larger than dominance variance estimates in both populations, estimates of dominance variance were smaller than their standard errors. Estimates of additive x additive variance were negative. So epistasis was assumed to be negligible. Diallel experiments A somewhat different analysis of gene action in soybean has emerged from studies of diallel crosses. While there are several ways to analyze and interpret data from a diallel cross, according to Griffing (1956), significant estimates of general combining ability (GCA) indicate additive and additive types of epistasis and significant specific combining ability (SCA) indicate dominance and all types of epistasis. Diallel experiments with the F1 generation often involved field grown spaced plants and yield measured as grams per plant. In a review of five such studies of non-random sets of inbred parents, variation due to GCA was found to be 1.6 and 1.9 times greater than SCA variation in three of the studies. In the other two, specific combining ability was nonsignificant (Burton, 1987). Using the Hayman (1954) diallel analysis which assumes no epistasis, Harer and Deshmukh (1991) and El-Sayad et al., (2005) found dominance variation to be greater than additive variation. Pandini et al. (2002) using the analysis suggested by Gardner and Eberhart (1966) also found significant non-additive effects. The experiments summarized above used diallel crosses of between 6 and 10 parents. Taken together this is a diverse sampling of soybean lines and varieties from germplasm pools in India, United States, Egypt, and Brazil. Even though the results are ambiguous regarding dominance, they are clear evidence of significant non-additive gene effects for single spaced plant yield. Similar results have been reported for diallel experiments in which the F2 generation was tested in plots that provided a better estimate of line or cultivar productivity. Leffel and Hanson (1961) found dominance variance to be 2.4 times the additive (using the Hayman no-epistasis analysis). Loiselle et al. (1990) following the Gardner and Eberhart (1966) analysis II, found significant variety (GCA) effects for yield at all locations and significant specific heterosis (SCA) effects at one of the three locations. Cho and Scott (2000) found GCA effects for yield to be large compared to SCA effects. The ration 2GCA/2GCA + SCA, was 0.93 which is evidence that most of the variation was additive and additive x additive epistasis (Baker, 1978). Gizlice et al. (1993) found significant GCA, but nonsignificant SCA in a 5 parent half-diallel of ancestor cultivars tested as F2 bulks. Generation means Heterosis, i.e. significant deviation of F1 or F2 generation means from the mid-parent (parent average), is evidence of non-additive genetic effects. This may be due to either epistasis or dominance (Compton, 1977). Inbreeding depression, i.e. a decrease in generation means with inbreeding, is evidence of dominance genetic effects. A review of nine experiments in which a total of 260 F1’s from biparental crosses were compared with their parents in a spaced plant field design, the mean percentage high parent heterosis of F1’s was 13.4 (Table 1). Fifty-five percent of those combinations had F1 yields greater than the high parent. The average percentage mid-parent heterosis of the F1’s was 25.7%. Cerna et al. (1997) tested 16 F1’s in a replicated spaced plant design (2 years, 2 locations) and found significant midparent and high-parent heterosis for 11 and 5 of the crosses, respectively. F1 seeds for testing in standard yield-row plots were generated by manual pollinations (Brim and Cockerham, 1961; Hillsman and Carter (1981); Burton and Brownie (2006) and by insect pollination using genetically male-sterile (ms2ms2 or ms6ms6) female parents (Nelson and Bernard, 1984; Lewers et al., 1998). Brim and Cockerham (1961) found an average of 20% high parent heterosis for the F1’s of two crosses; Hillsman and Carter reported an average 6.2% high 66

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parent heterosis among the F1’s of 8 crosses; Nelson and Bernard (1984) reported an average 3.3% high parent heterosis among 37 crosses. Of the 46 crosses from the 3 experiments, 32 (68%) had F1 yields greater then the parent yield (Table 1). More recently, Lewers et al. (1998) made 36 testcrosses using 3 isolines of Clark and 3 isolines of Harosoy as male parents and 6 genetically diverse soybean lines as female parents. The 36 test crosses were yield tested and average F1 mid-parent heterosis between 9.3% and 2.5% was reported. Burton and Brownie (2006) found 16% and 5% F1 high-parent heterosis for yield. F2 bulks have also been tested in standard yield plots along with parents. In four such experiments average mid-parent heterosis was found to be 8%, 11%, 9% and 7% (Weiss et al., 1947; Loiselle et al., 1990; Gizlice et al., 1993; Manjarrez-Sandoval et al., 1997). Table 1. Average yield heterosis expressed as a percent of the midparent and/or as a percent of the high parent. F1 yield of F yield in F1 yield in 1 spaced single ‡ row plots plants† rows§ Mean % midparent heterosis Mean % high parent heterosis %F1’s > midparent %F1’s > high parent

ManjarrezLoiselle Burton & Gizlice et Sandoval Lewers et etal. ¶ ‡‡ Brownie al. (1993) et al (1997) al. (1998) (1990)# (2006) §§ ††

24.9

9.6

48.2

10.8

9.3

6.8

5.0

—-

13.4

4.5

—-

—-

—-

3.1

—-

10.5

78.1

93.6

—-

—-

—-

—-

83

100

54.6

68.1

—-

—-

—-

—-

—-

100

†Average of results reported in 9 experiments, 260 different F1’s (Burton, 1987; Mehta et al., 1984; Kunta, et al., 1985; Dayde et al., 1989) ‡ Average of results reported in 3 experiments, 47 different F1’s (Burton, 1987) §Average results of 2 experiments, 24 F1’s, single rows, 1 yr., 1 location, 3 replications, per plant yield reported (Chauhan, & Singh, 1982; Rahangdale and Raut, 2002) # 55 F2 bulks, 4-row yield plots, 3 replications, 3 locations, 1 year ¶ 10 F2 bulks, 3-row yield plots, 3 replications, 2 locations, 2 years †† 24 F2 bulks, 3-row yield plots, 8 replications, 2 locations, 1 year ‡‡ 36 F1’s, 3-row yield plots, 3 replications, 2 years §§ 2 F1’s, 3-row yield plots, 3 replications, 3 locations, 2 years

Significant inbreeding depression has been observed where inbred generation bulks have been yield tested together in the same field experiment (Weiss et al., 1943; Brim and Cockerham, 1961; Lewers et al., 1998; Burton and Brownie, 2006; Rahangdale and Raut, 2002). When generation means were regressed on percentage inbreeding, average linear declines of -6.64 kg/ha-1 and -5.59 ha-1 (Brim and Cockerham, 1961) and -5.73 kg/ha-1 and -2.79 kg/ha-1 (Burton and Brownie, 2006) were found. Deviations from linearity were non-significant in both experiments. Taken together, observations of both heterosis and inbreeding depression are strong evidence that dominance genetic effects for seed yield are probably important in progeny of many cross combinations. Efforts to relate yield heterosis to parental genetic distance or coancestry have had mixed success (Nelson and Bernard, 1984; Gizlice et al., 1993; Cerna et al., 1997; Manjarrez-Sandoval et al., 1997). Genetics of dominance inbreeding depression There are likely several genetic causes for heterosis and inbreeding depression in soybean. Being a self-pollinated species, it is unlikely that soybeans carry a genetic load of major deleteri67

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ous genes that would contribute to inbreeding depression. However, soybean is an ancient polyploid originating from at least two genome duplications (Schlueter et al., 2004). So there are many homeologous regions in the genome with genes present in 2 or more copies. Gene duplications contribute to the conservation of functional but mildly deleterious genes (Husband and Schemske, 1996) which would partly explain heterosis in an F1 hybrid that combined favorable alleles at both loci, one contributed by each parent. F1 heterosis could be simply due to a greater number of these favorable (dominant) loci in the hybrid than either parent singly. Duplicate favorable alleles may complement each other either singly or as linked dominant alleles that are inherited together as suggested by Bingham (1998). Overdominance, the interaction of alleles at a single locus is also a possibility. Genetic control of quantitative traits may be due to multiple dosage dependant regulatory loci (Birchler et al., 2003). Heterosis is produced when allele differences at those loci effect structural gene expression. Unequal allelic expression has been observed in hybrids due to differences in gene regulation (Adams, 2007). Mackey (1990) suggested that duplicate genes at homeologous regions might interact similarly to heterozygous alleles at a single locus, and produce an overdominance-like effect. Dominance in soybean breeding Because there is currently no effective and economical way to produce F1 hybrid seeds dominance effects can not be exploited directly in soybean production. However, all of the genetic causes for heterosis discussed above, can be fixed with inbreeding with the exception of overdominance at single loci. Overdominant or dominant effects at duplicate loci become additive x additive effects with inbreeding. Thus, the immediate way to use dominance would be to use F1 or F2 heterosis as a criterion for selection among a set of crosses. While F1 seeds are difficult to produce, F2 seeds can easily be produced in an off-season nursery and tested as bulks in the following season. Those crosses with the best performance can be selected for further inbreeding using single seed descent or some other standard breeding practice. This is an old idea that was suggested for use in wheat and barley breeding (Harrington, 1944; Lupton, 1961, Weinhues, 1968) and used with some success. In soybean, Weiss et al., (1947) found the correlation between F2 bulk performance and number of high yielding lines selected from crosses to be low. Perhaps because of this result, the practice was never widely tested or used in soybean. Also, it was generally accepted that most variation was additive or additive x additive, so crossing a good parent with another good parent was the only cross prediction that was needed. Of course, the success of soybean breeding over the past 50 years has been based on the exploitation of additive variance. But plant breeders still need ways to distinguish between good and mediocre breeding populations. F2 bulk performance may be a way to make that distinction. Lewers et al., (1998) has suggested using testcrosses of a high yielding line to plant introductions as a way of finding those which can bring genetic diversity into a breeding program with no loss in productivity. Choosing those testcrosses that show F2 heterosis should be combinations that would have a higher probability of generating productive inbred lines. Finally, if there is significant dominance, early generation testing (EGT) may be warranted. In soybeans, EGT is difficult to do, again because of low seed supply in early generations, and the expense associated with it. But EGT would probably improve breeding success if an economical and efficient method could be devised. Molecular maker technology may be useful in this regard. Conclusion A review of evidence for heterosis and inbreeding breeding depression in soybean breeding literature suggests that dominance genetic effects can be significant in the F1 and F2 generations of many biparental crosses. While this dominance can not be exploited directly in F1 hybrid production, it may be useful for selection among breeding populations, and also successfully exploited in an efficient economical early generation testing method. Acknowledgement 68

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The author would like to thank Connie Bryant for her assistance in preparing and editing this manuscript. References Adams, K.L. (1970): Evolution of duplicate gene expression in polyploidy and hybrid plants. Journal of Heredity, 98, 1-6. Baker, R.J. (1978): Issues in diallel analysis. Crop Science, 18, 533-536. Bingham, E.T. (1998): Role of chromosome blocks in heterosis and estimates of dominance and over dominance. P. 71-87. In: Lamkey, K.R., Staub, J.E. (ed.) Concepts and breeding of heterosis in crop plants. ASA, CSSA, and SSSA, Madison, WI, USA Birchler, J.A., Auger, D.L., Riddle, N.C. (2003): In search of the molecular basis of heterosis. The Plant Cell, 15, 2236-2240. Brim, C.A., Cockerham, C.C. (1961): Inheritance of quantitative characters in soybeans. Crop Science, 1, 187-190. Brim, C.A. (1966): A modified pedigree method of selection in soybeans. Crop Science, 6, 220. Burton, J.W. (1987): Quantitiative genetics: Results relevant to soybean breeding. In: Wilcox, J.R. (ed.) Soybeans: Improvement, production, and uses, 2nd ed. Agronomy Monograph, 16, 211-247. ASA-CSSA, SSSA, Madison, WI, USA. Burton, J.W., Koinange, E.M.K., Brim, C.A., (1990): Recurrent selfed progeny selection for yield in soybean using genetic male-sterility. Crop Science, 30, 1222-1226. Burton, J.W., Brownie, C. (2006): Heterosis and inbreeding depression in two soybean single crosses. Crop Science, 46, 2643-2648. Cerna, F.J., Cianzio, S.R., Rafalski, A., Tingey, S., Dyer, D. (1997): Relationship between seed yield heterosis and molecular marker heterozygosity in soybean. Theoretical and Applied Genetics, 95, 460-467. Chauhan, V.S., Singh, B.B. (1982): Heterosis and genetic variability in relation to genetic divergence in soybean. Indian Journal of Genetics and Plant Breeding, 42, 324-328. Cho, Y., Scott, R.A. (2000): Combining ability of seed vigor and seed yield in soybean. Euphytica, 112, 145-150. Cockerham, C.C. (1983): Covariances of relatives from self-fertilization. Crop Science, 23, 1177-1180. Compton, W.A. (1977): Heterosis and additive x additive epistasis. Soybean Genetics Newsletter, 4, 60-62. Croissant, G.L., Torrie, J.H. (1971): Evidence of nonadditive effects and linkage in two hybrid populations of soybeans. Crop Science, 11, 675-677. Dayde’, J., Ecochard, R., Marmey, P. (1989): The possible influence of cytoplasm on the performance of reciprocal soybean hybrids. Euphytica, 44, 49-53. El-Sayad, Z.S., Soliman, M.M., Mokhtar, S.A., El-Shaboury, H.M.G., El-Hafez, G.A.A. (2005): Heterosis, combining ability, and gene action in F1 and F2 diallel crosses among six soybean genotypes. Annals of Agricultural Science, Moshtohor, 43, 545-559. Gardner, C. O., Eberhart, S. A. (1966) Analysis and interpretation of the variety cross diallel and related populations. Biometrics, 22, 439-452. Gates, C.E., Weber, C.R., Horner, T.W. (1960): A linkage study of quantitative characters in a soybean cross. Agronomy Journal, 52, 45-49. Gizlice, Z., Carter, T.E., Jr., Burton, J.W. (1993): Genetic diversity in North American soybean: II. Prediction of heterosis in F2 populations of southern founding stock using genetic similarity measures. Crop Science, 33, 620-626. Griffing, B. (1956): A generalized treatment of the use of diallel crosses in quantitative inheritance. Heredity, 10, 31-50. Hanson, W.D., Weber, C.R. (1961): Resolution of genetic variability in self-pollinated species with an application to the soybean. Genetics, 46, 1425-1434. Hanson, W.D., Probst, A.H., Caldwell, B.E. (1967): Evaluation of a population of soybean genotypes with implications for improving self-pollinated crops. Crop Sciences, 7, 99-103. Harer, P.W. and Deshmukh, R.B. (1991): Components of genetic variations in soybean (Glycine max (L.) Merrill). Journal of Oilseeds Research, 8, 220-225. Harrington, J.B. (1944): Yielding capacity of wheat crosses is indicated by bulk hybrid tests. Canadian Journal of Research, 18, 578-584. Hayman, B.I. (1954): The theory of diallel crosses. Genetics, 39, 789-809. Hillsman, K.J. and Carter, H.W. (1981): Performance of F1 hybrid soybeans in replicated row trials. Agronomy Abstracts. American Society of Agronomy, Madison, WI, p. 63. Husband, B.C., Schemske, D.W. (1996): Evolution of the magnitude and timing of inbreeding depression in plants. Evolution, 50, 54-70. Kenworthy, W. J., Brim, C.A. (1979) Recurrent selection in soybeans I. seed yield. Crop Science 19, 315-318. Kunta, T., Edwards, L.H., McNew, R.W., Dinkins, R. (1985): Heterotic performance and combining ability in soybeans. Soybean Genetics Newsletter, 12, 97-99. Leffel, R.C., Hansen, W.D. (1961): Early generation testing of diallel crosses of soybeans. Crop Science, 1, 169-174. Lewers, K.S., St. Martin, S.K., Hedges, B.R., Palmer, R.G. (1998): Testcross evaluation of soybean germplasm. Crop Science, 38, 1143-1149. Loiselle, F., Voldeng, H.D., Turcotte, P., St. Pierre, C.A. (1990): Analysis of agronomic characters for an eleven parent diallel of early-maturing soybean genotypes in eastern Canada. Canadian Journal of Plant Science, 70, 107-115.

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CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008 Lupton, F.G.H. (1961): Studies in the breeding of self-pollinating cereals. 3. Further studies in cross prediction. Euphytica, 10, 209-224. Mackey, J. (1970): Significance of mating systems for chromosomes and gametes in polyploids. Hereditas, 66, 165-176. Manjarrez-Sandoval, P., Carter, T.E. Jr., Webb, D.M., Burton, J.W. (1997): Heterosis in soybean and its prediction by genetic similarity measures. Crop Science, 37, 1443-1452. Mehta, S.K., Lal, M.S. and Beohar, A.B.L. (1984): Heterosis in soybean crosses. Indian Journal of Agricultural Science, 54, 682-684. Nelson, R.L., Bernard, R.L. (1984): Production and performance of hybrid soybeans. Crop Science, 24, 549-553. Pandini, F., Vello, N.A., Lopes, A.C. de A. (2002): Heterosis in soybeans for seed yield components and associated traits. Brazilian Archives of Biology and Technology, 45, 401-412. Rahangdale, S.R., Raut, V.M. (2002): Heterosis and inbreeding depression in soybean (Glycine max). Indian Journal of Agricultural Science, 72, 267-269. Rose, J.L., Butler, D.G., Ryley, M.J. (1992): Yield improvement in soybeans using recurrent selection. Australian Journal of Agricultural Research, 43, 135-144. Schlueter, J.A., Dixon, P., Granger, C., Grant, D., Doyle, J.J., Shoemaker, R.C. (2004): Mining EST databases to resolve evolutionary events in major crop species. Genome, 47, 868-876. Weinhues, F. (1968): Long-term yield analyses of heterosis in wheat and barley: variability of heterosis, fixation of heterosis. Euphytica, 17, (1968 Supplement 1), 49-62. Weiss, M.G., Weber, C.R., Kalton, R.R. (1947): Early generation testing in soybeans. Journal of the American Society of Agronomy, 39, 791-811.

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USE OF WILD HELIANTHUS SPECIES IN SUNFLOWER BREEDING Gerald J. Seiler, Chao-Chien Jan, Thomas Gulya USDA-ARS, Northern Crop Science Laboratory, Sunflower Unit, 1307 18th Street North, Fargo, North Dakota, USA E-mail: [email protected]

Abstract The genus Helianthus consists of 51 species and 19 subspecies with 14 annual and 37 perennial species. The current USDA-ARS wild Helianthus germplasm collection contains 2150 accessions, 1369 annual species accessions and 781 perennial species accessions. The narrow genetic base of cultivated sunflower has been broadened by the infusion of genes from wild species, which have provided a continued source of beneficial agronomic traits. Transfer of genes from the difficult-to-cross wild perennial Helianthus species has been enhanced by culturing of otherwise abortive interspecific hybrid embryos, making these species widely available for breeding purposes, either for specific major gene transfer or for the transfer of quantitative trait genes. Significant progress has been made in identifying genes in the wild species and the development of germplasm with resistance to new races of downy mildew, rust, broomrape and other persistent diseases such as Sclerotinia stalk and head rot. In addition, several cytoplasmic male-sterile sources and corresponding fertility restoration genes have been identified, together with new genes helping to improve oil quality, herbicide resistance, and salt tolerance. Thus far, only a small portion of the available genetic diversity of the wild Helianthus species has been utilized globally. There is no doubt that wild Helianthus species will continue to enhance new genetic variability of the crop, and help maintain sunflower as a viable major global oilseed crop. Key words: genetic resources, genetic diversity, Helianthus species, interspecific hybridization, prebreeding Introduction Crop wild relatives, which include the progenitors of the crop as well as the other species more or less closely related to them, have been beneficial to modern agriculture, providing plant breeders with a broad pool of potentially useful genetic resources. The use of crop wild relatives to improve crop performance is well established with examples dating back more than 60 years in sugar cane (Hajjar & Hodgkin, 2007). The wild species of sunflower are a valuable genetic resource for improving the sunflower crop (Jan et al., 2008; Jan & Seiler, 2007). Hajjar & Hodgkin (2007) reported that wild sunflower species have contributed seven traits for cultivated sunflower improvement including pest and disease resistance, abiotic stress (salt tolerance), herbicide tolerance, male sterility, and fertility restoration. The estimated economic contribution of the wild species to the cultivated sunflower is $384 million per year (Prescott-Allen & Prescott-Allen, 1986). Another estimate is $269.5 million per year (Phillips & Meilleur, 1998). Sunflower production continues to face challenges from both abiotic and biotic factors as well as from today’s ever-changing market needs as production is shifting from areas of high productivity to marginal areas with lower yield potential. The crop has been faring quite well; however, the limited genetic variability in cultivated sunflower has placed the crop in a vulnerable position should any major shifts of disease races or pests occur. The uniform use of a single CMS PET1 (French) cytoplasm and a few fertility restoration genes for worldwide hybrid sunflower production makes the crop extremely vulnerable. This paper will discuss the importance and the utilization of the wild sunflower species for increasing the genetic diversity in cultivated sunflower. Wild Helianthus germplasm collection. The USDA-ARS National Plant Germplasm System (NPGS) sunflower collection is maintained at the North Central Regional Plant Introduction Station (NCRPIS) in Ames, Iowa, USA. The mission of the NCRPIS is to conserve genetically diverse crop germplasm and associated information, to conduct germplasm-related research, and to encourage the use of germplasm and associated information for research, crop improvement and product development. The wild species collection contains all 37 perennial species and 14 an71

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nual species (Schilling, 2006). Cultivated sunflower is represented by a single species, Helianthus annuus. The NPGS sunflower collection is a diverse assemblage of 3850 accessions: 1708 cultivated Helianthus annuus accessions (44%) from 59 countries, 932 wild Helianthus annuus accessions (25%), 437 accessions representing 13 other wild annual Helianthus species (11%), and 773 accessions representing 37 perennial Helianthus species (20%). This collection is one of the largest and most genetically diverse seed collections in the world, and it is vital to the conservation of Helianthus germplasm. Over 14,000 samples of wild sunflower accessions from this collection have been distributed to more than 365 researchers from 34 different countries over the last 28 years. Collection of germplasm not only facilitates preservation of germplasm, but it also provides valuable information about the diverse habitats occupied by wild sunflowers and associated species. This information is particularly important for the genus Helianthus because of the co-evolution of its species and associated native insects and pathogens. Knowledge of a particular habitat and adaptations of a species occurring therein can often help to identify potential sources of genes for desired traits. Based on the habitat of a species and its immediate environment, selection of potential species for a particular characteristic may become easier, more accurate, and more efficient. Interspecific hybridization. In recent years there has been considerable interest in interspecific hybridization for transferring unique genes from wild species into cultivated lines for the development of pre-breeding populations for sunflower improvement. This procedure allowed for the production of interspecific combinations not previously available and has facilitated additional studies of species relationships not previously possible. Wild sunflower species and cultivated sunflower can generally be crossed, but the divergence and heterogeneity of the genus causes considerable difficulties, such as cross-incompatibility, embryo abortion, sterility, and reduced fertility in interspecific hybrids. Cultivated sunflower is grown primarily as a single-cross hybrid. It is the second largest hybrid crop in the world, after maize. As a hybrid crop, much effort has gone into creating genetically diverse inbred lines. A considerable amount of this diversity has come from the wild ancestors with agronomic traits introgressed into the crop species. The development of a two-step embryo procedure by Chandler & Beard (1983) and used by Kräuter et al. (1991) greatly facilitated interspecific hybridization in sunflower. Pathogen resistance. Wild sunflower species have been a valuable source of resistance genes for many of the common pathogens of cultivated sunflower. Helianthus annuus, H. petiolaris, and H. praecox are major sources of genes for Verticillium wilt (Verticillium dahliae) resistance (Hoes et al., 1973). These species plus H. argophyllus are also major sources of resistance genes for downy mildew (Plasmopara halstedii) and rust (Puccinia helianthi) in cultivated sunflower. Resistance genes for these pathogens occur frequently in the wild annual species (Tan et al., 1992; Quresh et al., 1993). Resistance to broomrape (Orobanche cumana) has been observed in most of the wild perennial species (Fernández-Martínez et al., 2000). Phoma black stem (Phoma macdonaldii) resistance has been reported in several perennial species, H. decapetalus, H. eggertii, H. hirsutus, H. resinosus and H. tuberosus (Skoric, 1985). Phomopsis stem canker (Phomopsis helianthi) resistance has been found in perennials H. maximiliani, H. pauciflorus, H. hirsutus, H. resinosus, H. mollis, and H. tuberosus (Skoric, 1985; Dozet, 1990). Similarly, Alternaria leaf spot (Alternaria helianthi) resistance was observed in perennials H. hirsutus, H. pauciflorus, and H. tuberosus (Morris et al., 1983), while Rhizopus head rot (Rhizopus arrhizus) resistance has been observed in perennials H. divaricatus, H. hirsutus, H. resinosus, and H. x laetiflorus (Yang et al., 1980). Powdery mildew (Erysiphe cichoracearum) resistance was found in annuals H. debilis ssp. debilis, H. bolanderi, and H. praecox (Saliman et al., 1982; Jan & Chandler, 1985). Sclerotinia (Sclerotinia sclerotiorum) head rot tolerance has been observed in perennials H. resinosus, H. tuberosus, H. decapetalus, H. grosseserratus, H. nuttallii, and H. pauciflorus (Pustovoit & Gubin, 1974; Mondolot-Cosson & Andary, 1994; Ronicke et al., 2004). Sclerotinia root rot tolerance was found in perennials H. mollis, H. nuttallii, H. resinosus, and H. tuberosus (Skoric, 1987), while Sclerotinia stalk rot tolerance was observed in annual H. praecox, and perennials H. pauciflorus, H. giganteus, 72

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H. maximiliani, H. resinosus, and H. tuberosus (Skoric, 1987). The stalk rot resistance in hexaploid perennial H. californicus is being transferred into cultivated sunflower (Feng et al., 2006). Five interspecific amphiploids derived from perennial H. strumosus, H. grosseserratus, H. maximiliani, H. nuttallii and H. divaricatus appear to have stalk rot resistance (Jan et al., 2006). Insect resistance. Wild sunflowers are native to North America, where their associated insect herbivores and entomophages co-evolved in natural communities. This provides the opportunity to search for insect resistance genes in the wild species. North America has the largest losses due to insect pests. In the major production areas there are about 15 principal insect pests of cultivated sunflower, and of this total, about six are considered important economic pests from year to year (Charlet & Brewer, 1997). Sunflower moth (Homoeosoma electellum) tolerance was observed in annual H. petiolaris, and perennials H. maximiliani, H. ciliaris, H. strumosus, and H. tuberosus (Rogers et al., 1984). Stem weevil (Cylindrocopturus adspersus) tolerance occurs in perennials H. grosseserratus, H. hirsutus, H. maximiliani, H. pauciflorus, H. salicifolius, and H. tuberosus (Rogers & Seiler, 1985). Sunflower beetle (Zygogramma exclamationis) tolerance was observed in annuals H. agrestis and H. praecox, and perennials H. grosseserratus, H. pauciflorus, H. salicifolius, and H. tuberosus (Rogers & Thompson, 1978; 1980). Charlet & Seiler (1994) found indications of resistance to the red sunflower seed weevil (Smicronyx fulvus)in several Helianthus species. Oil and oil quality. Variability for oil concentration exists in the wild species. While oil concentration is lower in the wild species than in cultivated sunflower, backcrossing to cultivated lines quickly raises the oil concentration to an acceptable level. Annual H. anomalus has the highest oil concentration recorded for a wild sunflower species with 460 g kg-1 (Seiler, 2007), followed by H. niveus ssp. canescens with 402 g kg-1, H. petiolaris with 377 g kg-1, and H. deserticola with 343 g kg-1. Perennial H. salicifolius has a concentration of 370 g kg-1 (Seiler, 1985). Cultivated sunflower generally contains 450 to 470 g kg-1. The linoleic fatty acid concentration in the oil of H. anomalus populations was uncharacteristically high for a southern desert environment, approaching 700 g kg-1 (Seiler, 2007). A linoleic acid concentration of 540 g kg-1 in H. deserticola is more typical for a southern desert environment. Cultivated sunflower grown at northern latitudes generally has linoleic acid contents over 680 g kg-1, while these in southern latitudes have approximately 550 g kg-1. Reduced concentrations of saturated palmitic and stearic fatty acids have been observed in a population of wild H. annuus that had a combined palmitic and stearic acid concentration of 58 g kg-1 (Seiler, 1998). This is 50% lower than the oil concentration of cultivated sunflower. A combined palmitic and stearic acid concentration of 65 g kg-1 was observed in a wild perennial species, H. giganteus (Seiler, 1998). Cytoplasmic male sterility. Sunflower is the only Asteraceae in which the cytoplasmic male-sterile (CMS) system is known to exist. A single male-sterile cytoplasm, PET1, derived from H. petiolaris ssp. petiolaris (Leclercq, 1969), and the identification of dominant fertility restoration genes (Enns et al., 1970; Kinman, 1970; Vranceanu & Stoenescu, 1971) advanced sunflower production from the use of open-pollinated cultivars to hybrid production 35 years ago. This source of cytoplasmic male sterility and a few fertility restoration genes, including the widely used Rf1 and Rf2 genes, have been used exclusively for sunflower hybrid production worldwide (Fick & Miller, 1997). Seventy CMS sources have been identified from progenies of crosses between wild Helianthus accessions and cultivated lines, from wild accessions grown in observation nurseries, or from induced mutation. Fertility restoration genes have been reported for 34 CMS sources, and detailed inheritance studies have been conducted for 19 of 34 sources (Serieys, 2002). Salt tolerance. Several species of Helianthus are native to salt-impacted habitats. Interspecific germplasm with high salt tolerance, withstanding salt concentrations up to EC 24.7 d Sm-1, have been identified from annual H. paradoxus. It appears that one major gene controls salt tolerance, although a modifier gene may also be present, possibly recessive in control (Miller, 1995). Two salt-tolerant parental oilseed maintainer lines, HA 429 and HA 430, have been released (Miller & Seiler, 2003). 73

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Herbicide tolerance. A wild population of annual H. annuus from a soybean field in Kansas, USA, that had been repeatedly treated with imazethapyr herbicide for seven consecutive years developed resistance to the imidazolinone and sulfonylurea herbicides (Al-Khatib et al., 1998). Resistance to imidazolinone and sulfonylurea herbicides has great potential for producers in all regions of the world for controlling several broadleaf weeds. Several populations of wild sunflower (H. annuus and H. petiolaris) from the USA and Canada have been screened for resistance to these two herbicides. Eight percent of 50 wild sunflower populations had some resistance to imazamox and 57% had some resistance to tribenuron, a sulfonylurea herbicide in the central USA (Olson et al., 2004). In Canada, 52% of 23 wild H. annuus populations had some resistance to tribenuron (Miller & Seiler, 2005). Genetic stocks IMISUN-1 (oil maintainer), IMISUN-2 (oil restorer), and IMISUN-3 (confection maintainer) with resistance to imidazolinone herbicides have been developed and released (Al-Khatib & Miller, 2000). Miller & Al-Khatib (2002) also released one oilseed maintainer and two fertility restorer breeding lines with imidazolinone herbicide resistance. Genetic stocks SURES-1 and SURES-2 with resistance to the sulfonylurea herbicide tribenuron have been developed and released by Miller & Al-Khatib (2004). In addition, the two herbicides may control broomrape in areas of the world where this parasitic weed attacks sunflower (Alonso et al., 1998). Conclusions and prospective. Significant progress has been made in increasing the number of accessions in the wild sunflower species collection to preserve the wild species and increase the available genetic diversity for improvement of the sunflower crop. Interspecific gene transfer for sunflower improvement has been practiced since the very early years by breeders in the Former Soviet Union and it has continued to play a key role as the crop developed into a major global oilseed crop. Recent advances in culturing of otherwise abortive interspecific hybrid embryos are highly effective for making the difficult-to-cross wild perennial Helianthus species crosses available for breeding purposes, either for specific major gene transfer or for the transfer of quantitative trait genes. Significant results have been reported on sunflower germplasm development with regard to resistance to new races of downy mildew, rust, broomrape and other major diseases. In addition, new CMS and corresponding fertility restoration genes have been continuously identified together with new genes helping to improve oil quality, herbicide resistance, and salt tolerance. Thus far, only a small portion of the available genetic diversity of the wild Helianthus species has been used globally. There is no doubt that wild Helianthus species will continue to increase the genetic variability available to sunflower breeders and enhance the future of sunflower as a major global oilseed crop. References Al-Khatib K., Baumgartner J. R., Peterson D. E., Currie R. S. (1998): Imazethapyr resistance in common sunflower (Helianthus annuus). Weed Science, 46,403-407. Al-Khatib K., Miller J. F. (2000): Registration of four genetic stocks of sunflower resistant to imidazolinone herbicides. Crop Science, 40, 869-870. Alonso L.C., Rodriguez-Ojeda M.I., Fernandez-Escobar J., Lopez-Calero G. (1998): Chemical control of broomrape (Orobanche cernua Loefl.) in sunflower (Helianthus annuus L.) resistant to imazethapyr herbicide. Helia, 21, 45-54. Chandler J. M., Beard B. H. (1983): Embryo culture of Helianthus hybrids. Crop Science, 23, 1004-1007. Charlet L. D., Brewer G. (1997): Management strategies for insect pests of sunflower in North America. Recent Research Developments in Entomology, 1, 215-229. Charlet L. D., Seiler G. J. (1994): Sunflower seed weevils (Coleoptera:Curculionidae) and their parasitoids from native sunflowers (Helianthus spp.) in the Northern Great Plains. Annals of the Entomological Society of America, 87, 831-835. Dozet B. M. (1990): Resistance to Diaporthe/Phomopsis helianthi Munt.-Cvet. et al. in wild sunflower species. Proceedings of the 12th Sunflower Research Workshop, Fargo, ND, USA, 8-9 January 1990, 86-88. Enns H., Dorrell D. G., Hoes J. A., Chubb W. O. (1970): Sunflower research, a progress report. Proceedings of the 4th International Sunflower Conference, Memphis, TN, USA, 23-25 June, 1970, 162-167. Feng J. H., Seiler G. J., Gulya, T. J., Jan C. C. (2006): Development of Sclerotinia stem rot resistant germplasm utilizing hexaploid Helianthus species. Proceedings of the 28th Sunflower Research Workshop, Fargo, ND, USA, January 11-12, 2006, http://www. sunflowernsa.com/research/research-workshop/ documents/ FengSclerotinia _06.pdf.

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CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008 Fernández-Martínez J., Melero-Vara J. J., MuZoz-Ruz J., Ruso J., Domínguez J. (2000): Selection of wild and cultivated sunflower for resistance to a new broomrape race that overcomes resistance to Or5 gene. Crop Science, 40, 550-555. Fick G. N., Miller J. F. (1997): Sunflower breeding. In: Schneiter A.A. (Ed.) Sunflower Technology and Production. Crop Science Society of America, Madison, WI, USA, 395-439. Hajjar R., Hodgkin T. (2007): The use of wild relatives in crop improvement: A survey of developments over the last 20 years. Euphytica, 156, 1-13. Hoes J. A., Putt E. D., Enns H. (1973): Resistance to Verticillium wilt in collections of wild Helianthus in North America. Phytopathology, 63, 1517-1520. Jan C. C., Chandler J. M. (1985): Transfer of powdery mildew resistance from Helianthus debilis Nutt. into cultivated sunflower (H. annuus L.). Crop Science, 25, 664-666. Jan C. C., Feng J., Seiler G. J., Gulya T. J. (2006): Amphiploids of perennial Helianthus species x cultivated sunflower possess valuable genes for resistance to Sclerotinia stem and head rot. Proceedings of the 28th Sunflower Research Workshop, Fargo, ND, USA,11-12 January 2006, http://www. sunflowernsa. com/research/research-workshop/ documents/Jan_Amphiploids _06.pdf. Jan C. C., Seiler G. J. (2007): Sunflower. In: Singh R. J. (Ed.) Genetics Resources, Chromosome Engineering, and Crop Improvement, Volume 4, Oilseed Crops. CRC Press, NY, 103-165. Jan C. C., Seiler G., Gulya T., Feng J. (2008): Sunflower germplasm development utilizing wild Helianthus species. Proceedings of the 17th International Sunflower Conference, Cordoba, Spain, 7-12 June 2008, 29-43. Kinman M. L. (1970): New developments in the USDA and state experiment station sunflower breeding programs. Proceedings of the 4th International Sunflower Conference, Memphis, TN, USA, 23-25 June 1970, 181-183. Kräuter R., Steinmetz A., Friedt W. (1991): Efficient interspecific hybridization in the genus Helianthus via “embryo rescue” and characterization of the hybrids. Theoretical and Applied Genetics, 82, 521-525. Leclercq P. (1969): Cytoplasmic male sterility in sunflower. Annals de l’amélioration des plants, 19, 99-106. Miller J. F. (1995): Inheritance of salt tolerance in sunflower. Helia 18, 9-16. Miller J. F., Al-Khatib K. (2002): Registration of imidazolinone herbicide-resistant sunflower maintainer (HA 425) and fertility restorer (RHA 426 and RHA 427) germplasms. Crop Science, 42, 988-989. Miller J. F., Al-Khatib K. (2004): Registration of two oilseed sunflower genetic stocks, SURES-1 and SURES-2 resistant to tribenuron herbicide. Crop Science, 44, 1037-1038. Miller, J.F., Seiler G. J. (2003): Registration of five oilseed maintainer (HA 429-HA 433) sunflower germplasm lines. Crop Science, 43, 2313-2314. Miller J. F., Seiler G. J. (2005): Tribenuron resistance in accessions of wild sunflower collected in Canada. Proceedings of the 27th Sunflower Research Workshop, Fargo ND USA. 12-13 January 2005, http://www.sunflowernsa.com /research/research- workshop/ documents /miller_ tribenuron_05.pdf, 2005. Mondolot-Cosson L., Andary C. (1994): Resistance factors of wild species of sunflower, Helianthus resinosus to Sclerotinia sclerotiorum. Acta Horticulturae, 381, 642-645. Morris J. B., Yang S. M., Wilson L. (1983): Reaction of Helianthus species to Alternaria helianthi. Plant Disease, 67, 539–540. Olson B., Al-Khatib K., Aiken R. M. (2004): Distribution of resistance to imazamox and tribenuron-methyl in native sunflowers. Proceedings of the 26th Sunflower Research Workshop, 14-15 January, Fargo, ND, USA, http://www.sunflowernsa.com /research/ research-workshop/documents/ 158.pdf. Phillips O. L., Meilleur B. A. (1998): Usefulness and economic potential of rare plants of the United States: A statistical survey. Economic Botany, 52, 57-67. Prescott-Allen C. P., Prescott-Allen R. (1986): The First Resource: Wild Species in the North American Economy. Yale University Press, London, UK, 529. Pustovoit G. V., Gubin I. A. (1974): Results and prospects in sunflower breeding for group immunity by using the interspecific hybridization method. Proceedings of the 6th International Sunflower Conference, Bucharest, Romania, 22-24 July 1974, 373-381. Quresh Z., Jan C. C., Gulya T. J. (1993): Resistance of sunflower rust and its inheritance in wild sunflower species. Plant Breeding, 110, 297-306. Rogers C.E., Seiler G. J. (1985): Sunflower (Helianthus) resistance to stem weevil (Cylindrocopturus adspersus). Environmental Entomology, 14, 624-628. Rogers C. E., Thompson T. E. (1978): Resistance in wild Helianthus to the sunflower beetle. Journal of Economic Entomology, 71, 622-623. Rogers C. E., Thompson T. E. (1980): Helianthus resistance to the sunflower beetle. Journal of the Kansas Entomology Society, 53, 727-730. Rogers C. E., Thompson T. E., Seiler G. J. (1984): Registration of three Helianthus germplasms for resistance to the sunflower moth. Crop Science, 24, 212-213. Ronicke S., Hahn V., Horn R., Gron I., Brahn L., Schnabl H., Freidt W. (2004): Interspecific hybrids of sunflower as sources of Sclerotinia resistance. Plant Breeding, 123, 152-157. Ruso J., Sukno S., Domínguez-Gimenez J., Melero-Vara J. M., Fernández-Martínez J. M. (1996): Screening wild Helianthus species and derived lines for resistance to several populations of Orobanche cernua. Plant Disease, 80, 1165-1169.

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Plenary lectures

CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008 Saliman M., Yang S. M., Wilson L. (1982): Reaction of Helianthus species to Erysiphe cichoracearum. Plant Disease, 66, 572-573. Schilling E. E. (2006): Helianthus. In: Flora of North America Editorial Committee (Eds.) Flora of North America North of Mexico. Oxford University Press, New York and Oxford, Vol. 21,141-169. Seiler G. J. (1985): Evaluation of seeds of sunflower species for several chemical and morphological characteristics. Crop Science, 25, 183-187. Seiler G. J. (1998): The potential use of wild Helianthus species for selection of low saturated fatty acids in sunflower oil. In: de Ron A. M. (Ed.) International Symposium on Breeding of Protein and Oil Crops. EUCARPIA, Pontevedra, Spain, 1-4 April 1998, 109-110. Seiler G. J. (2007): Wild annual Helianthus anomalus and H. deserticola for improving oil content and quality in sunflower. Industrial Crops and Products, 25, 95-100. Seiler G. J., Rieseberg L. H. (1997): Systematics, origin, and germplasm resources of wild and domesticated sunflower. In: Schneiter, A. A. (Ed.) Sunflower Technology and Production. Crop Science Society of America, Madison, WI, USA, 21-65. Serieys H. (2002): Report on the Past Activities of the FAO Working Group Identification, Study and Utilization in Breeding Programs of New CMS Sources for 1999-2001. FAO Sunflower Subnetwork Progress Report, 1999-2001, FAO, Rome, Italy, 1-54. Skoric D. (1985): Sunflower breeding for resistance to Diaporthe/Phomopsis helianthi Munt.-Cvet. et al. Helia, 8, 21-23. Skoric D. (1987): FAO sunflower sub-network report 1984-1986. In: Skoric D. (Ed.) Genetic Evaluation and Use of Helianthus Wild Species and Their Use in Breeding Programs, FAO Rome, Italy, 1-17. Tan A. S., Jan C. C., Gulya T. J. (1992): Inheritance of resistance to race 4 of sunflower downy mildew in wild sunflower accessions. Crop Science, 32, 949-952. Vranceanu A. V., Stoenescu F. M. (1971): Pollen fertility restorer genes from cultivated sunflower. Euphytica, 20, 536-541. Yang S. M., Morris J. B., Thompson T. E. (1980): Evaluation of Helianthus spp. for resistance to Rhizopus head rot. Proceedings of the 9th International Sunflower Conference, Torremolinos, Spain, 8-13 June, 1980, 1, 147-151.

76

Plenary lectures CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008

GERMPLASM COLLECTIONS AS AN IMPORTANT TOOL FOR BREEDING - EXAMPLES ON WHEAT Andreas Börner1, Kerstin Neumann1, Ulrike Lohwasser1, Marion S. Röder1, Elena K. Khlestkina2, Oxana Dobrovolskaya2, Tatyana A. Pshenichnikova2, Petr Martinek3, Maria Rosa Simon4, Borislav Kobiljski5 1

Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung, Corrensstrasse 3, D-06466 Gatersleben, Germany 2 Institute of Cytology and Genetics SB RAS, Novosibirsk, 630090 Russia 3 Agrotest Fyto, Ltd., Havlí~kova 2787, 767 01 Kromìøí`, Czech Republic 4 Cerealicultura, Facultad de Ciencias Agrarias y Forestales, Universidad Nacional de La Plata, 60 y 119, CC31, 1900 La Plata, Argentina 5 Institute of Field and Vegetable Crops, Maksima Gorkog 30, 21000 Novi Sad, Serbia E-mail: [email protected]

Abstract Based on FAO statement it is estimated that world-wide existing germplasm collections contain more than 6 million accessions of plant genetic resources of which wheat (Triticum and Aegilops) represents the biggest group with about 800,000 accessions. One of the four largest ex situ genebanks of the world is located at the Leibniz-Institute of Plant Genetics and Crop Plant Research in Gatersleben. This collection comprised wild and primitive forms, landraces as well as old and more recent cultivars of mainly cereals but also other crops. Starting in the 1920’s material was accumulated systematically. The collection is supplemented by genetic stocks created during the last 50 years. These stocks include single chromosome substitution lines, single chromosome recombinant lines, recombinant inbred lines, introgression lines, etc. Beside the long term storage and frequent regeneration of the material phenotypic characterisation and evaluation data are collected as a prerequisite for gene identification and mapping. In our presentation we give examples for the successful utilisation of germplasm for the molecular mapping of major genes and QTL determining morphological and agronomically important traits. Homologous and homoeologous relationships of detected loci are discussed. Key words: ex situ collections, genetic resources, genetic mapping, wheat, wild relatives. Maintenance and management of plant genetic resources - ex situ genebanks Plant ex situ genebank collections comprise seed genebanks, field genebanks and in vitro collections. Species whose seed can be dried, without damage, down to low moisture contents, can be stored in seed banks. Field genebanks and in vitro storage are used primarily for species which are either vegetatively propagated or which have recalcitrant seeds that cannot be dried and stored for long periods. In addition, perennial species, for example certain forage species, which produce small quantities of seed, and long-lived plants (in particular, trees) are also maintained this way. It is estimated that worldwide, less than 10% of genebank holdings are stored in vivo in the field, and less than 1% are conserved in vitro (FAO, 1998). World-wide existing germplasm collections contain more than 6 million accessions of which wheat represents the biggest group with about 800,000 samples. Beside the genus Triticum comprising 788,654 accessions another 21,360 accessions of the wild ancestor Aegilops are maintained. A list of the ten world-wide largest germplasm collections by crop is given in table 1 (FAO, 1998). The German ex situ genebank, located at the Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK) in Gatersleben, is one of the four largest global collections. About 150,000 accessions are maintained including cereals (65,000), legumes (28,000), vegetables (18,000), forage crops (14,000), oil crops (8,000), potatoes (6,000) and medicinal and spice plants (6,000). As on the global scale wheat (Triticum) is the largest group having 28.000 accessions. The wild relative Aegilops comprises 1,500 samples (Annonymus, 2008). Seed storage is managed in five large cold chambers, two maintained at 0°C and three at -15°C. Seeds are kept in glass jars, covered with bags containing silica gel. Each year between 8 77


and 10% of the collection is grown either in the field or in the glasshouse. Voucher specimens, photographs and written documentation are used to monitor the identity of the material. The germplasm collection is supplemented by genetic stocks created during the last 50 years. These stocks include single chromosome substitution lines, single chromosome recombinant lines, recombinant inbred lines, introgression lines, etc. This material has been used successfully for the molecular mapping of major genes and QTL determining morphological and agronomically important traits. Table 1. The ten largest world-wide germplasm collections by crop (FAO, 1998). Crop Wheat Barley Rice Bean Maize Oat Soybean Sorghum Mustard/Rape Apple

Genus Triticum Hordeum Oryza Phaseolus Zea Avena Glycine Sorghum Brassica Malus

Accessions 788,654 486,724 420,341 268,369 261,584 223,287 176,400 168,550 106,923 97,543

Utilisation of wheat genetic resources ‡ 1. Abiotic stress (Trichomes) Outgrowths of the epidermis of plant organs, called trichomes or hairs are common in many plant species. It is supposed that the occurrence of hairs (pubescence) is positively associated with harsh moisture regimes. A layer of hairs will in most cases decrease the air movement next to the leaf (or any other plant organ), and thus create a special microclimate being some kind of buffer. In addition a thick hair cover also protects the surface from intensive solar irradiation. The genetics of hairiness of several organs including leaves is well studied. Performing F2 monosomic analysis Maystrenko (1976) described a gene for leaf hairiness (Hl1) to be located on chromosome 4B. Maystrenko (1992) showed that nine cultivars bred in drought environments of Siberia, Kazakhstan and the Volga region carry one and the same gene (Hl1) for leaf hairiness. Another dominant gene controlling the hairiness of the auricles and designated Pa (pubescent auricles) was determined (Maystrenko, 1992). Using ditelosomic lines, both Hl1 and Pa were positioned on the long arm of chromosome 4B. Linkage between the Hl1 and Pa was calculated to be 30 cM. Another gene for leaf hairiness (Hl2) was discovered on chromosome 7BS applying monosomic and telosomic analysis (Taketa et al., 2002). Beside of wheat, genes for hairiness of leaves are described for barley or rye but also for the wild relatives of the cultivated cereals. In cultivated barley (Hordeum vulgare L.) a gene for pubescent leaf blade is located on chromosome 3HL (Pub) whereas another gene determining hairy leaf sheath (Hs syn. Hsh) is known to be located on the long arm of chromosome 4H pleiotropically linked to Hn syn. Hln determining the trait hairs on lemma (Franckowiak, 1997; Lundqvist et al., 1997). A homoeologous gene determining hairy leaf sheath in Hordeum bulbosum L. and designated Hsb was described by Korzun et al. (1999). Furthermore, Korzun et al. (1999) could show that the gene Hp1, determining pleiotropically the hairiness of the peduncle and leaf sheath in rye (Secale cereale L.) and which is known to be located on the long arm of chromosome 5R lines up with the barley genes Hs (Hsh) and Hsb. The co-linearity is due to a translocation with and a homoeology to the distal part of the 4L chromosomes of the other Triticeae members (Devos et al. 1993). Pshenichnikova et al. (2007) identified a gene determining hairy leaves in Aegilops speltoides Tausch, a wild relative of cultivated wheat, in the wheat/Aegilops speltoides introgre78


ssion line ‘102/00i’. Results of a monosomic analysis revealed that the introgression carrying the hairy leaf gene was located on chromosome 7B. Mapping populations were created segregating for major genes on chromosomes 4B and 7B, originating from cultivated wheat (T. aestivum) and the wheat/Aegilops speltoides introgression line described above, respectively. Beside this, a QTL mapping approach was performed investigating the ‘International Triticeae Mapping Initiative’ (ITMI) mapping population and considering the hairyness of leaves and auricles. Finally a test cross was carried out for testing the allelism between Hl2 (7BL) and the Hl gene of the wheat/Aegilops speltoides introgression line (7B). The results were summarised by Dobrovolskaya et al. (2007). Two major genes for leaf pubescence of wheat and the wheat/Aegilops introgression line were mapped on chromosomes 4BL (Hl1) and 7BS (Hl2Aesp), respectively, together with QTL determining leaf and auricle pubescence on the long arms of chromosomes 4B (contributed by Opata) and 4D (contributed by Synthetics, i.e. Ae. tauschii). Because the positions of the QTL for hairy leaves and auricles were highly comparable on both chromosomes, it may be concluded that both traits are inherited pleiotropically. However, linkage of two different loci can not be excluded. Considering the data obtained by Korzun et al. (1998, 1999) and using the consensus linkage map of barley published by Langridge et al. (1995) the homoeologous group 4 wheat (Ae. tauschii) genes/QTL Hl1, QHl.ipk-4B, QPa.ipk-4B, QHl.ipk-4D and QPa.ipk-4D line up with the barley pubescence genes Hln/Hsh and Hsb as well as the rye gene Hp1 (Figure 1). I was concluded that the locus seems to be pleiotropically responsible for the pubescence of different plant organs in different species of the Triticeae.

Figure 1: Comparative molecular mapping of genes determining hairiness of different plant organs in wheat (Aegilops tauschii), barley and rye. The mapping data were originated from (1) Dobrovolskaya et al., 2007; (2) Langridge et al., 1995; (3) Korzun et al., 1999; (4) Korzun et al., 1998. c = centromere position, L = long arm A second homoeologous series seems to be present on the short arms of the homoeologous group 7 chromosomes at least in wheat (7B) and Aegilops speltoides. For this clear indication is given by the result of the test cross analysed. Utilisation of wheat genetic resources ‡ 2. Biotic stress (Septoria) A set of 84 wheat (T. aestivum)/Aegilops tauschii introgression lines was developed by backcrossing the seven wheat cv. ’Chinese Spring’/’Synthetic 6x’ D genome chromosome substitution lines with ‘Chinese Spring’ (‘CS’). The ’Synthetic 6x’ used for the creation of the substitution lines had been obtained from a cross between tetraploid emmer (T. dicoccoides) and Ae. tauschii and therefore, the material available contains different segments of individual chromosomes of Ae. 79


tauschii in the ‘CS’ background. The introgressed segments of the individual lines were determined by using SSR markers (Pestsova et al., 2001; 2006). Analysing several sets of single chromosome substitution lines including the ’CS’/’Synthetic 6x’ series, Simón et al. (2001; 2005) identified chromosome 7D of ’Synthetic 6x’ to be almost complete resistant to two virulent Argentinean isolates of the disease Septoria tritici blotch, designated IPO 92067 and IPO 93014. Both isolates were used to phenotype thirteen chromosome 7D wheat/Aegilops introgression lines by Simon et al. (2007). A summary is given in figure 2.

Figure 2. Wheat/Ae. tauschii chromosome 7D introgression lines inoculated with septoria tritici blotch isolates IPO 92067 and IPO 93014 at seedlings and adult plant stages. Lines significant different to ‘CS’ in at least two and four independent experiments are given in grey and black colour, respectively. Box in broken line indicates the position of the resistance locus. L = long arm, S = short arm, c = centromere position. Considering the introgressions being significantly different to ‘CS’ in at least two (grey bars) or even four (black bars) independent experiments it is clearly indicated, that the disease resistance locus is present in the centromeric region of the short arm of chromosome 7D. It was shown, that the resistance is acting against both isolates used and in both developmental stages, although the effects were more pronounced at the seedling stage. The position of the locus detected here is highly comparable with that, described by Arraiano et al. (2001), investigating single-chromosome recombinant lines developed on the basis of the CS (Syn 7D) substitution line. Stb5 was mapped distal to the marker Xgwm44, also included for the identification of the introgression lines (Pestsova et al., 2006) and therefore, present in our studies. We suppose that we have tagged the major gene Stb5 by applying the ‘Introgression Mapping Approach’. This example nicely indicates, that the present set of Triticum/Aegilops introgression lines is a suitable tool for the detection of genes/QTL originated from Ae. tauschii, the progenitor of the D genome of hexaploid wheat. The whole set of introgression lines is available on request for any kind of further investigation. 80


Utilisation of wheat genetic resources ‡ 3. Spike morphology The spike morphology trait multirow spike (MRS) was studied. Phenotypic analysis revealed a segregation ratio of 3 (wild type) to 1 (mutant) i.e MRS is controlled by a recessive gene. It is originated from the hexaploid wheat accession ‘Ra1’, a mutant that was produced through chemical mutagenesis. The gene mrs was genetically mapped on chromosome 2DS, about 8 cM from the centromere. In addition physical mapping was performed employing deletion lines for chromosome 2D. The details are described by Dobrovolskaya et al. (2008) in the present proceedings book of the conference ‘Breeding 2008’. Utilisation of wheat genetic resources ‡ 4. Association mapping Genetic studies of agronomic important traits in cereals have revealed that most of them are inherited quantitatively and therefore, they are difficult to detect within the genome. Using segregation-based mapping methods a huge amount of QTL has been mapped during the last decade. Another methodology for the detection of QTL is the association-based approach largely and effectively used in human genetics. In plants only few examples of association based mapping studies were done. We performed a genome wide association analysis using a genetically diverse core collection of 96 wheat varieties/accessions. The collection was evaluated for agronomic traits during up to five growing seasons. In order to investigate trait-marker associations the wheat lines were genotyped using diversity array technology (DarT) markers. Genotyping was carried out by Triticarte Pty Ltd (http://www.triticarte.com.au/content/FAQ.html). The amount of 874 markers was found to be polymorphic among the 96 genotypes. From 501 of these markers the map positions are known. With a subset of these markers the population structure was investigated with the software STRUCTURE (Pritchard et al., 2000) and revealed that two subpopulations are present in our collection. The calculation of testing for an association between the markers and the trait were done with the software Tassel 2.0.1 (Bradbury et al., 2007). The general linear model (GLM) with including the Q-Matrix from STRUCTURE as correction for population structure was used for testing the marker-trait associations. As one example the trait flowering time was analysed. Markerloci being significant (p 1). The distance indicated their genetic divergence and applicability for developing high quality synthetics or for crossing to obtain new populations with improved quality. The group comprising the populations derived from the varieties from Brno, Oslava /05, Jitka /05 and Hana /05 was genetically close, pointing out the importance of source populations for divergence among alfalfa genotypes. However, the proximity of these experimental populations might be due to the application of one-cycle phenotypic selection in their development, indicating that the effectiveness of this selection method in alfalfa breeding is relatively modest, especially if the one-cycle variant is used (Figure 1). The third group in the dendrogram consisted of populations which combined good yield and quality and which were not distant. However, these populations had been developed by different selection methods from a variety of source populations (all developed in different breeding centers around the world) and were therefore expected to possess significant genetic divergence. The experimental populations developed from the varieties NS Banat ZMS II and Slavija had high yields of green forage and dry matter and were genetically quite divergent. Thus, they can be used as components in developing alfalfa synthetics with an increased yield of dry matter (Figure 1). The populations obtained by selfing the variety Orka (S2) were genetically distant, indicating that self-pollination over several generations can be used to increase the polymorphism of alfalfa germplasm. Selfing across a larger number of generations (S7), on the other hand, results in the material becoming more homogenous, as in the case of the experimental populations 12515 and 162016. Conclusions The experimental populations Meldor /05, Oslava /05, 12515 and Jitka 05 had excellent quality and represented a valuable source of genes for quality. The experimental populations Morava /05, Magda /05, Luzelle /05, Orca /05 12515 and 162016 combined in themselves both genes for quality and genes for yield performance. The high-yielding varieties NS Banat ZMS II 210

Cross-pollinated crops Genetic Resources and Prebreeding Poster Presentation


and Slavija were shown to be desirable sources for breeding for increased yields of green forage or dry matter. The geographic origin of the source population and the breeding objective are important for obtaining divergent experimental populations. Inbreeding source populations is the shortest way for obtaining divergent experimental populations. References Annicchiarico P. (2006): Diversity, genetic structure, distinctness and agronomic value of Italian lucerne (Medicago sativa L.) landraces. Euphytica 148, 269-282. Hill, R.R., Jr., Shenk, J.S. and Barnes, R.F. (1988): Breeding for yield and quality. In: A.A. Hanson et al. (ed.) Alfalfa and alfalfa improvement. ASA–CSSA–SSSA, Madison, Wisconsin, 809–825. Julier, B. Huyghe, Ch. Guy, P. and Crochemore, M. L. (1996): Genetic variation in Medicago sativa complex. Cahiers Options Méditerranéennes, 18, 91-102. Julier, B. and Huyghe C. (1997): Effect of growth and cultivar on alfalfa digestibility in a multi–site trial. Agronomie 17, 481-489. Julier B., Guines F., Ecalle C., and Huyghe C. (2001): From description to explanation of variations in alfalfa digestibility. Proceedings of the XIV EUCARPIA Medicago sp. Group Meeting. Zaragoza, 45, 19-23. Jenczewski E., Prosperi J. M. and Ronfort J. (1999): Evidence for gene flow between wild and cultivated Medicago sativa (Leguminosae) based on allozyme markers and quantitative traits. Am. J. Bot. 86, 677-687. Katic, S., Milic, D., Mihailovic, V., Mikic, A. and Vasiljevic, S. (2005 a): Changes in crude protein content with advancing maturity in lucerne. XX International Grassland Congress: Offered papers. Dublin 26. 06. – 1. 07. 270. Katic, S., Milic, D. and Vasiljevic, S. (2005 b): Variability of dry matter yield and quality of lucerne genotypes depending on geographic origin. EGF, Grassland Sci. in Europe, 10, 537-540. Kendall, M. 1980. Multivariate analysis. 2nd ed. MacMillan, New York. Lamb, F. S. J., Sheaffer C. C., Rhodes, H. L., Sulc R. M., Undersander, J. D. and Brummer E. C. (2006): Five decades of alfalfa cultivar improvement: Impact on forage yield, persistence, and nutritive value. Crop Sci. 46, 902-909. Michaud, R., Tremblay, G.F., Belanger, G. And Michaud J. (2001): Crude protein degradation in leaves and stems of alfalfa (Medicago sativa L.). Proceedings of the XIV EUCARPIA Medicago sp. Group Meeting. Zaragoza, Spain 45, 211-214. Stjepanovi} M. (1998): Lucerna. Nova zemlja, Osijek, 143.

211



GENETIC DIVERSITY, COMBINING ABILITY AND HETEROSIS IN MAIZE INBRED LINES Sneàna Mladenovi} Drini}, Aleksandar Radoj~i}, Goran Drini}, Milomir Filipovi} Maize Research Institute „Zemun Polje“, Slobodana Baji}a 1, Belgrade, Serbia E-mail: [email protected]

Abstract The goal of this study was to investigate the relationship between combining ability and heterosis with genetic distance among maize inbred lines based on molecular markers. A diallel cross between six maize inbred lines was carried out to estimate genetic parameters for grain yield and determine the heterosis and combining abilities of the inbreds and their crosses. The cluster analysis based on genetic distance for RAPD data clasiffies inbred lines into two principial heterotic groups. The correlation between genetic distance and heterosis as well as and combining ability was positive, middle and significant. Results of this study indicate that RAPD markers can be used for genetic divergence analysis of maize inbred lines, although their use for prediction of combinig ability and heterosis is still limited. Key words: combining ability, genetic distance, heterosis, maize Introduction Prediction of hybrid performance has been of primary interest to essentially all hybrid breeding programmes. Breeders have been interested in choosing the parental lines, which would result in heterotic combination without necessarily making all possible crosses among the potential parents. The various methods employed to predict heterosis can be grouped into (i) per se performance, (ii) combining ability and (iii) genetic diversity. The past limitations associated with pedigree data and morphological, physiological and cytological markers for assessing genetic diversity have largely been circumvented by the development of molecular markers. Molecular markers have been used to analyze the genetic relationships among maize inbred lines and to examine the relationship between marker-based GD and heterosis (Ajmone Marsan et al., 1998; Melchinger et al., 1990; Shiel & Thseng, 2002; Reif et al., 2003; Xu et al., 2004; Mohammadi et al., 2008) and combining ability (Lee et al., 1989; Parentoni et al., 2001; Srdi} et al., 2006, Balestre et al., 2008) in maize. While significant correlations between hybrid performance and marker divergence of parental lines were detected in several studies, the level of correlations varied widely from one report to another depending on the germplasm analysed. The objective of this study was to estimate genetic diversity among set of inbred lines and its relationship with combining ability and heterosis. Materials and Methods Three inbred lines related with BSSS (ZPL 142, ZPL 680 and ZPL 357) and three with non-BSSS genetic background (ZPL 257, ZPL 17/5, and ZPL 173) were crossed to generate diallel set of progenis. Parent inbred lines, 30 F1 crosses with reciprocial¢s, were included in a randomized complete block design with four replications in two densities (44.640 and 64.935 plants/ha-1) at location Zemun Polje in two years. An analysis of variance, general and specific combining ability for grain yield was calculated according to Griffing’s (1956) with diallel analysis software of Burrow & Coors, (1994).The genomic DNA was isolated from inbred lines following the protocol of Saghai and Maroof et al., (1984) and RAPD analyses was performed using modified protocol of Williams et al., (1990). Genetic distance between all pairs of lines was calculated using the Jaccard’s coefficient. Distances were visualized using a dendogram created using the UPGMA algorithm (NTSYS-pc software, Rohlf, 2000). Results and Disscussion Both GCA and SCA for grain yield were significant in both plant densities and years (Table 1). Higer value of SCA pointed out that yield is mainly controled by non-additive gene action in F1 crosses. In general, inbred lines ZPL 357 shows the best GCA values in favorable condi212



tions. In the same time ZPL 357 provided the highest grain yield per se in both densities, as well as years. Table 1. GCA (diagonal) and SCA effects (above diagonal) for grain yield Inbred ZPL142

density 44,640 64,935

ZPL 275

44,640 64,935

ZPL680

44,640 64,935

ZPL17/5

44,640 64,935

ZPL357

44,640 64,935

ZPL173

44,640 64,935

year 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2

ZPL142 0.521* 0.010 0.698* 0.322

ZPL275 1.947* 2.249* 1.624* 2.149* -0.331* 0.286* -0.345* 0.217

ZPL680 ZPL17/5 ZPL357 0.852* 1.543* -1.783* 0.508 1.931* -0.710* 1.084* 2.036* -2.005* 0.254 2.466* -1.478* 0.464 -0.009 1.122* 0.879* 1.289* 1.856* 1.148* -1.064* 1.698* 0.616 0.120 1.450* 0.586* 1.772* 0.643* -0.096 1.218* 2.401* 0.032 1.055* -0.362 -0.041 2.283* 1.432* -0.554* 0.400 -0.599* 1.385* -0.677* 1.491* -0.678* 1.223* -0.066 0.608* 0.315* 0.460*

ZPL173 1.447* 2.053* 1.807* 2.186 0.189 1.217* -0.353* 1.289* 0.938* 1.693* 1.535* 1.593* -1.479* -0.650* -1.534* -0.881* 1.865* 1.575* 1.893* 2.679* -0.156 -0.209 -0.022 -0.280

The highest heterosis for yield was detected in the combination ZPL 17/5 x ZPL 680 while the lowest one was determined in the combination ZPL 142 x ZPL 357 (Table 2). The degree of heterosis depends on the relative performance of inbred parents and the corresponding hybrids. Table 2. The grain yield heterosis (above diagonal, %) and GD (below diagonal) genotype ZPL142 ZPL 275 ZPL 680 ZPL 17/5 ZPL 357 ZPL 173

ZPL142 0.64 0.58 0.63 0.50 0.66

ZPL 275 127.44 0.63 0.57 0.62 0.54

ZPL 680 123.57 134.54 0.60 0.61 0.65

ZPL 17/5 123.76 88.10 144.84 0.62 0.48

ZPL 357 50.66 92.86 89.86 75.39

ZPL 173 119.41 101.45 141.84 59.25 103.52

0.65

Ten RAPD primers from Genosys Biotechnologies were used to amplify fragments from the DNA templates of six inbred lines. A total of 42 fragments of different molecular weight were scored from which 71% was polymorphic. The average number of alleles per locus was 5.2, rang213



ing from 4 to 8. The estimated mean genetic distance based on RAPD markers was 0.6, ranging from 0.48 to 0.66, Table 2. The lowest genetic distance as well the lowest grain yield and SCA value was established between inbred lines ZPL 173/3 and ZPL 17/5.

Figure 1. Dendogram based on GD from RAPD data The cluster analysis based on genetic distance computed from RAPD data classifies six inbreeds into two principal heterotic groups. The first group encompasses inbreeds non- related to BSSS germplasm and the second group consists of inbreeds related to BSSS germplasm (Fig.1). Clustering was found to be fairly consistent with known pedigree relationships. Table 3. Spearman’s rank correlation coefficient between SCA and GD (rs1) and heterosis and GD (rs2) Densities 44,640 plants ha-1 64,935 plants ha-1

Years Y1 Y2 Y1 Y2

rs1 0,74** 0,72** 0,86** 0,74**

rs2 0,56* 0,56* 0,79** 0,54*

Genetic distance was positively correlated with SCA and heterosis in all environments. Higher correlation was estimated in higher density for both years, except for correlations between heterosis and GD in year 2 (Table 3.). Similar results have been found in other published studies (Melchinger et al., 1990; Ajmone Marsan et al., 1998; Lee et al., 1989; Drini} et al., 2002; Betran et al., 2003; Mohammadi et al., 2008; Balestre et al., 2008) Conclusion Both GCA an SCA contributed to the high yields in these F1 hybrids. The level of genetic diversity in this set of lines was high with an average 5.2 alleles per locus and a range from 4 to 8. Positive and significant correlation were found between GD and SCA and heterosis, although in general these values were low to be of practical predictive value. Clustering of lines based on the D showed relationship fairly consistent with know pedigree relationships. Acknowledgements This research was supported by the Ministry of science of Republic of Serbia. References Ajmone Marsan P., Castiglioni P., Fusari F., Kuiper M., and Motto M. (1998): Genetic diversity and its relationship to hybrid performance in maize as revealed by RFLP and AFLP markers. Theor. Appl. Genet. 96:219-227.

214


CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008 Balestre M., Machado J.C., Lima J.L., Souza J.C. and Nóbrega Filho L. (2008): Genetic distance estimates among single cross hybrids and correlation with specific combining ability and yield in corn double cross hybrids. Genet. Mol. Res. 7 (1): 65-73. Betrán F.J., Ribaut J-M., Beck D., and Gonzalez de Leon D.(2003): Genetic diversity, specific combining ability, and heterosis in tropical maize inbreds under stress and nonstress environments. Crop Sci. 43:797-806. Drini} Mladenovi} S., Trifunovi} S., Drini} G., Konstantinov K. (2002): Genetic diversity and its correlation to heterosis in maize as revealed by SSR-based markers. Maydica, 47, 1-8. Griffing B. (1956): Concept of general and specific combining ability in relation to diallel crossing sistems.Australian Journal of biological science 9:463-564. Lee M., Godshalk E.B., Lamkey K.R., and Woodman W.W. (1989): Association of restriction fragment length polymorphisms among maize inbreds with agronomic performance of their crosses. Crop Sci. 29:1067-1071 Melchinger A.E., Lee M., Lamkey K.R., Woodman W.L.(1990): Genetic diversity for restriction fragment length polymorfisms: relation to estimated genetic effect in maize inbreds. Crop Sci., 30: 1033-40. Mohammadi S.A., Prasanna B.M., Sudan C. and Singh N.N. (2008): SSR heterogenic patterns of maize parental lines and prediction of hybrid performance. Biotehnol.&Biotechnol.EQ. 22, 541-547. Parentoni S.N., Magalhaes J.V., Pacheco C.A., Santos M.X., Abadie T.,. Gama E.E.G, Guimaraes P.E., Meirelles W.F., Lopes M.A., Vasconcelos M.J.V. and Paiva E. (2001): Heterotic groups based on yield-specific combining ability data and phylogenetic relationship determined by RAPD markers for 28 tropical maize open pollinated variety. Euphytica 121:197-208. Reif J.C., Melchinger A.E., Xia X.C., Warburton M.L., Hoisington D.A., Vasal S.K., Srinivasan G., Bohn M. and Frisch M. (2003):. Genetic distance based on simple sequence repeats and heterosis in tropical maize populations. Crop Sci. 43:1275-1282. Rohlf F.J. (2000): NTSYS-pc. Numerical taxonomy and multivariate analysis system. Version 2.0 Exeter Software, Setaket, N.Y. Sagai-Maroof M.A., Soliman K.M., Jorgenson R., Allard R.W. (1984): Ribosomal DNA spacer length polymorphism in barley: Mendel Ian inheritance, chromosomal location and population dynamics. Proc.Natl. Acad. Sci. USA 81: 8014-8018. Shiel G.J. and Thseng F.S. (2002): Genetic diversity of Tainan-white maize inbred lines and prediction of single cross hybrid performance using RAPD markers. Euphytica 124:307-313. Srdi} J., Mladenovi} Drini} S., Paji} Z. (2006): Combining abilities and genetic resemblance of maize inbred line. Acta Agronomica Hungarica vol.54, No.3, 337-342. Williams J.G.K., Kubelik A.R., Livak K.J., Rafalski J.A. and Tingey S.V. (1990): DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Res. 18: 6531-6535. Xu S., Liu J., and Liu G. (2004): The use of SSRs for predicting the hybrid yield and yield heterosis in 15 key inbred lines of Chinese maize. Hereditas 141:207-215.

215



CORE COLLECTION OF BROOMCORN (Sorghum bicolor (L.) Moench) Vladimir Sikora, Jano{ Berenji Institute of Field and Vegetable Crops, Department of Hops, Sorghum and Medicinal Plants, Maksima Gorkog 30, 21000 Novi Sad, Serbia E-mail: [email protected]

Abstract From the broomcorn germplasm that is collected and maintained at the Institute of Field and Vegetable Crops in Novi Sad and includes 450 genotypes, a core collection was separated. First, stratification was carried out based on the most important agronomic and technological characters such as stalk height and fiber length, and then from each group genotypes were selected proportional to group height and information on origin as well as measurements of quantitative traits. The core collection established in this manner numbered 54 genotypes, representing 12% of the basic collection. The core was compared with the basic collection for the variation of 13 quantitative traits. Depending on the trait, the core collection varied by 68–100% relative to the basic collection and can be representatively used in sorghum breeding programs. Key words: basic collection, broomcorn , core collection. Introduction Sorghum is one of the first domesticated plants with a broad region of growing, which is the main cause for the diversification of a few agronomic types. Broomcorn is primarily grown for its panicles, which serve as a raw material in the manufacturing of corn brooms. Serbia could be considered as the most significant world producer of broomcorn and corn brooms. The concept of core collection was first proposed by Frankel (1984). Further determination of this concept suggests that a core collection includes a limited number of samples originating from the existing germplasm collection, selected to represent the genetic spectrum of the whole collection (Frankel & Brown, 1984; Brown, 1989a, 1995). The regularly formed core covered about 70% of the alleles spread in the initial gene pool (Brown, 1989b). Brown (1989a) suggests that the first step in core forming is the determination of groups in the basic collection using geographic region or some important quantitative characteristics. In the second phase, genotypes are selected from each group for the core. The number of selected genotypes depends on the volume of the core and can be determined using constant, proportional or logaritmic methods. Material and Methods The broomcorn collection of the Institute of Field and Vegetable Crops in Novi Sad includes 450 genotypes and by its volume and structure represents a world collection. The collection consists of landraces, former and contemporary varieties, and breeding material. The genotypes originate from 19 countries representing all world regions where broomcorn is grown. Core collection formating included information on origin as well as measurements of quantitative traits, which was done in 2006. The broomcorn core collection was made by the proportional hierarchical method (Hintum, 1995; Hintum et al., 2000). By this method, the whole germplasm is divided into three groups based on stalk height: European short, American short, and tall (Berenji, 1990). The three groups are further subdivided into subgroups based on fiber length. Stalk height is the most important agronomic trait, because its influence on manual harvesting and fiber length directly influences production and quality of corn brooms. The core collection is formed by selecting genotypes from all subgroups proportionally to their geographic distribution and size of groups. Genotypes with extreme values are included in the core collection, although they have low frequency. The consistency of genetic variability is tested by comparing variability and range ratio in the basic and core collections. Results and Discussion In the sorghum world collection at ICRISAT, which numbers 22 473 genotypes, the core collecton is formed on the basis of photoperiodic sensitivity and geographic origin (Garnier et al., 216



2001a) by comparing three random sampling strategies (Garnier et al., 2001b). The variability of differently sized broomcorn collections was examined in our earlier experiments (Berenji, 1990; Sikora, 2005; Berenji and Sikora, 2006). Diwan et al. (1995) reported that when they formed the core collection of Medicago sp., the core that consisted of 5% and 10% genotypes covered less than 62% of variability of the complete collection. According to their results, use of the proportional method caused larger differences in range between the basic and core collections. In our experiment, the core collection consisted of 54 genotypes that covered 12% of the basic collection. The range ratio between the basic and core collections varied from 68% for the number of fibers per panicle to 100% for plant height, panicle length, fiber length and flag leaf sheath length. On the basis of results in Table 1, it can be concluded that the proportional method was appropriate for making broomcorn core collection which fully represented phenotypic variability inside the germplasm of 450 genotypes. According to earlier examination (Narkhede et al., 2000; Singh et al., 2001; Kadam et al., 2001), genetic diversity of sorghum germplasm does not depend on geographic diversity. The core collection group of European short genotypes includes material that originated from different centers, including American and Asian ones. The situation is the same with American short and tall broomcorns. Based on this data, it can be conclud that a core collection formed on the basis of quantitative traits is more representative than a core formed on the basis of geographic data. Table 1. Mean values, standard deviations and range of quantitative traits for basic collection and core collections of broomcorn. Basic collection

Trait

X ± sx

Range

Core collection X ± sx

Range

Range ratio (%)

Components of plant height Plant height (cm)

240.0±2.88

95-397

236.2±3.02

95-397

100

Stalk height (cm)

146.0±2.75

32-301

143.0±2.91

35-301

98

Panicle length (cm)

87.5±0.46

49-123

93.3±0.64

49-123

100

Fiber length (cm)

61.0±0.52

31-96

59.8±0.48

31-96

100

Length of peduncle (cm)

33.1±0.38

14-54

33.4±0.40

14-52

95

Flag leaf sheath length (cm)

44.2±0.24

34-52

44.0±0.22

34-52

100

Panicle exsertion (cm)

-11.1±0.38

-31-+11

-10.1±0.36

-31-+10

95

Components of panicle yield and quality Untreshed panicle (g)

73.4±1.05

30-138

73.2±1.03

30-107

80

Treshed panicle (g)

21.4±0.31

6-46

20.4±0.28

6-36

75

Seed mass (g)

52.3±0.88

16-114

51.3±0.78

3-87

86

Randament of panicle (g)

29.2±0.44

13-50

28.2±0.41

17-45

76

Number of fiber

58.7±0.53

31-90

58.6±0.52

38-78

68

Fiber fineness [(g/m) 1000]

483±5.38

261-742

473±4.89

276-650

78

Comparative frequency of genotypes in basic and core collections of broomcorn is presented in Table 2 for components of plant height and in Table 3 for components of panicle yield and quality. As can be seen, the core includes all groups of genotypes that can be found in the basic collection. 217



Table 2. Frequency (%) of genotypes for components of plant height in the base and core collections (underline bold) of broomcorn. Plant height (cm) Very short 350 1.9 3.7 39.5 33.3 21.4 35.2 16.6 14.8 14.6 13.0 Stalk height (cm) European short 150 27.4 27.8 32.5 35.2 40.1 37.0 Panicle length (cm) Very short 120 0.6 1.9 17.8 18.5 42.0 48.1 38.8 29.6 0.6 1.9 Peduncle length (cm) Very short 45 cm 19.1 18.5 45.9 40.7 25.5 35.2 9.5 5.6 Fiber length (cm) Very short 75 14.6 13.0 33.8 40.7 35.0 35.2 16.6 11.1 Flag leaf sheath length (cm) Very short 50 12.7 13.0 52.9 53.7 29.9 27.7 4.5 5.6 Panicle exsertion (cm) Negative 0 cm 87.3 83.3 12.7 16.7 Table 3. Frequency (%) of genotypes for components of panicle yield and quality in the base and core collections (underlined) of broomcorn. Mass of unthreshed panicle (g) Very short 100 2.5 5.6 18.5 18.5 44.6 40.7 30.6 27.8 3.8 7.4 Mass of threshed panicle (g) Very short 30 3.8 3.7 33.1 29.6 32.5 40.7 19.1 14.8 11.5 11.2 Seed mass per panicle (g) Very short 80 1.3 3.7 19.1 22.2 54.1 48.1 21.0 20.4 4.5 5.6 Randament of panicle (%) Short 30 14.7 22.2 43.9 38.9 41.4 38.9 Number of fibers per panicle Very short 70 12.1 16.7 47.1 40.7 30.6 25.9 10.2 16.7 Fiber fineness [(g/m) 1000] Short 600 20.4 22.2 35.0 37.0 34.4 31.5 10.2 9.3 218



References Berenji J. (1990): Varijabilnost i me|uzavisnost svojstava u raznih genotipova sirka metla{a. Bilten za hmelj, sirak i lekovito bilje, 22, 68. Brown A.H.D. (1989a): Core collections: a practical approach to genetic resources management. Genome, 31, 818-824. Brown A.H.D. (1989b): The case for core collections. In: Brown A.H.D., Frankel O.H., Marshal D.R., Williams D.R. (Eds.) The use of plant genetic resources. Cambridge University Press, Cambridge, UK, 136-156. Brown A.H.D. (1995): The core collection at the crossroads. In: Hodgkin T., Brown A.H.D., Hintum Th.J.L.van, Morales E.A.V. (Eds.) Core Collections: Improving the Management and Use of Plant Germplasm. Chichester, John Wiley & Sons, 3-20. Diwan N., McIntosh M.S., Bauchan,G.R. (1995): Methods of developing a core collection of annual Medicago species. Theor. Appl. Genet., 90, 755-761. Frankel O.H. (1984): Genetic perspective of germplasm conservation. In: Arber W.K., Limensee K., Peacock W.J., Starlinger P. (Eds.) Genetic Manipulation: Impact on Man and Society. Cambridge University Press, Cambridge, UK, 161-170. Frankel O.H., Brown A.H.D. (1984): Current plant genetic resources– a critical appraisal. In: Genetics: New Frontiers. Oxford & IBH Publ., Co., New Delhi, 4, 1-11. Grenier C., Bramel-Cox P.J., Hamon P. (2001a): Core collection of sorghum: I. Stratification on eco-geografical data. Crop Science, 41, 234-240. Grenier C., Hamon P., Bramel-Cox P.J. (2001b): Core collection of sorghum: II. Comparison of three random sampling strategies. Crop Science, 41, 241-246. Kadam D.E., Patil F.B., Bhor T.J., Harer P.N. (2001): Genetic diversity studies in sweet sorghum. Jour. Mahar. Agric. Univ., 26, 140-143. Narkhede B.N., Akade J.H., Awari W.R. (2000): Genetic diversity in rabi sorghum local types. Jour. Mahar. Agric. Univ., 25, 245-248. Sikora V. (2005): Varijabilnost germplazme sirka metla{a. Bilten za hmelj, sirak i lekovito bilje, 37, 78, 105. Sikora V., Berenji J. (2006): Variability in germplasm of broomcorn. XX International Conference of the EUCARPIA Maize and Sorghum Section, Budapest, Hungary, 119. Singh’G., Singh H.C., Ram K., Sunil K.S. (2001): Genetic diversity in sorghum. Ann. Agric. Res., 22, 229-231. Van Hintum T.J.L. (1995): Hierarchical approaches to the analysis of genetic diversity in crop plants. In: Hodgkin T., Brown A.H.D., Van Hintum T.J.L., Morales E.A.V. (Eds.), Core Collections of Plant Genetic Resources, IPGRI, Rome, Italy, 23-34. Van Hintum T.J.L., Brown A.H.D., Spillane C., Hodgkin T. (2000): Core collection of plant genetic resources. IPGRI Technical Bulletin No.3, IPGRI, Rome, Italy.

219



STUDY OF AMINO ACID COMPOSITION OF WINTER VETCH (V. villosa Roth.) DEPENDING ON SOME MAJOR CULTURAL FACTORS Nataliya Georgieva, Todor Kertikov Institute of Forage Crops, 89 General Vladimir Vazov Street, 5800 Pleven, Bulgaria E-mail: [email protected]

Abstract With the purpose of studying the amino acid composition of winter vetch variety Asko 1 grown in the conditions of different sowing dates (20-25 September, 5-10 October, 20-25 October, 5-10 November) and rates of nitrogen fertilizing (0, 30, 60 and 90 kg ha-1), during the 2001-2004 period a two-factor field trial was carried out at the Institute of Forage Crops, Pleven. It was found that the sowing date and nitrogen fertilizing as cultural factors had effect on the amino acid synthesis in winter vetch grain. The fertilizing effect was not unidirectional. The increasing rates of nitrogen fertilizing resulted in a decrease of biological protein value and content of most amino acids. An exception was observed for glutamic acid, threonine, serine, glycine and lysine, the maximum of which was reached when applying nitrogen at the dose of 60 kg ha-1. Consideration of the independent effect of the sowing date factor showed that the amino acid accumulation in the vetch grain was highest for second or third date (except for glutamic acid and cystine), these dates being distinguished for lower temperature supply and rainfall. The synthesis of glutamic acid, aspartic acid, cystine, methionine, lysine, leucine, arginine, proline, glycine, alanine and tyrosine in the winter vetch grain was influenced more strongly by the sowing date and the synthesis of valine, phenylalanine, isoleucine, histidine and serine by the nitrogen fertilizing. The only amino acid, the synthesis of which was influenced equally strongly by both studied factors was threonine. Key words: amino acids, fertilizing, winter vetch. Introduction An important part of breeding and cultural research work is to improve the chemical composition of grain. That concerns mainly the content of proteins, fat, amino acids and vitamins determining its biological value as a forage. The differences in growing of a stand, namely density, fertilizing with nitrogen fertilizers and irrigation, on the one hand and ecological factors, on the other hand, condition the direction of metabolitic processes in the plant and hence the amino acid accumulation in the grain in particular. The variations in the environmental conditions, such as light, temperature and moisture of soil and air during the 24-hour period, as well as during the growing season, cause profound changes in activity and nature of enzyme effect, so in the whole metabolism (Tosheva & Marinov, 1989). For the conditions of Bulgaria there are studies on the major factors having effect on the amino acid composition in maize (Tosheva & Marinov, 1989), grasses (Pavlov, 2002), forage pea (Petkova & Pavlov, 2007), etc. Similar studies have not been conducted in winter vetch. The objective of this study was to investigate the amino acid composition of winter vetch grown at different rates of fertilizing and sowing dates. Materials and Methods During the 2001-2004 period in IFC, Pleven a two-factor field trial was carried out by the split plot method, with four replications of the variants and a size of record plot of 10 m2. The degrees of A factor (sowing date) were arranged in the big plots: A1 – 20-25 September; A2 – 5-10 October; A3 – 20-25 October; A4 – 5-10 November and the degrees of T factor (fertilizer rate in kg ha-1) were in the small plots: T0 – N0; T1 – N30; T2 – N60; T3 – N90. The nitrogen fertilizer (NH4NO3) was applied in early spring and phosphorus (Ca(H2PO4)2.H2O) and potassium (KCl) fertilizers were applied before basic soil cultivation at the dose of 60 and 40 kg/ha, respectively. Grain samples were taken from all experimental variants to perform an amino acid analysis. An automated amino analyzer was used. Winter vetch (V.villosa) represented by the only registered variety in Bulgaria Asko 1 was studied. 220



Results and Discussion The amino acid content in the grain of winter vetch variety Asko 1 is presented in Table 1. The averaged values according to fertilizing rates showed that the effect of fertilizing factor was not unidirectional. The increasing levels of nitrogen fertilizing resulted in a decrease of the content of most amino acids. An exception was observed for glutamic acid, threonine, serine, glycine and lysine, the maximum of which was reached in variant T2 (N60). Similar relation was reported by Pavlov (1996) in maize and sunflower. Considering the independent effect of the sowing date factor it was found that the amino acid accumulation in the vetch grain was highest for second or third date (except for glutamic acid and cystine), these dates being distinguished for lower temperature and rainfall supply. On average for the three-year experimental period the effective temperature sums from first to last sowing date decreased by 10.3, 11.5 and 20.8%, respectively and rainfall amount by 13.6, 19.6 and 38.5%, respectively. Table 1. Amino acid content in the grain of winter vetch variety Asko 1 at different sowing dates and fertilizing rates, g 100g protein-1 20-25 September 5-10 October 20-25 October 5-10 November TO T1 T2 T3 TO T1 T2 T3 TO T1 T2 T3 TO T1 T2 T3 Aspartic acid 12.05 11.56 11.75 11.84 11.70 11.27 11.68 11.33 11.72 11.80 11.79 12.31 12.19 11.84 11.39 11.71 Threonine 3.36 3.33 3.53 3.55 3.53 3.39 3.45 3.41 3.26 3.38 3.40 3.44 3.34 3.22 3.41 3.34 Serine 2.54 3.33 3.08 3.02 2.75 2.73 3.18 3.57 2.89 3.52 3.37 3.38 3.25 3.02 3.30 3.35 Glutamic acid 19.10 20.83 20.19 18.49 16.09 16.07 20.76 20.97 19.20 20.35 19.58 20.43 20.34 20.96 21.07 21.37 Proline 4.25 4.47 4.12 3.99 4.33 4.56 4.32 4.46 5.07 4.93 4.90 4.67 4.59 4.26 4.36 4.08 Cystine 1.02 0.59 1.07 0.83 0.84 0.63 0.88 0.59 0.57 0.40 0.52 0.56 0.59 0.70 0.47 0.89 Glycine 3.44 4.34 3.94 3.32 2.84 3.18 3.72 3.99 3.97 4.18 4.31 4.56 4.21 4.25 4.28 4.06 Alanine 4.53 4.40 4.47 4.76 5.10 5.33 4.32 4.29 4.40 4.14 4.29 4.25 4.29 4.45 4.32 4.31 Valine 5.42 5.15 5.39 5.59 5.95 6.09 5.20 5.10 5.53 5.15 5.32 5.60 5.44 5.70 5.66 5.31 Methionine 0.74 0.42 0.49 0.73 0.87 0.83 0.34 0.39 0.42 0.19 0.53 0.21 0.29 0.23 0.23 0.21 Isoleucine 4.90 4.50 4.72 5.03 5.32 5.38 4.49 4.39 4.67 4.41 4.58 4.50 4.49 4.51 4.48 4.41 Leucine 8.24 7.77 7.91 8.34 8.73 8.81 7.71 7.66 7.91 7.72 7.88 7.69 7.72 7.73 7.71 7.61 Tyrosine 1.75 1.68 1.63 1.84 1.98 2.04 1.75 1.83 1.86 1.72 1.88 1.83 1.83 1.92 1.74 1.84 Phenylalanine 4.47 4.47 4.45 4.58 4.75 4.78 4.42 4.47 4.59 4.40 4.60 4.55 4.51 4.63 4.50 4.44 Histidine 9.36 8.96 9.04 9.70 10.10 9.61 8.99 9.37 9.56 9.40 8.99 8.12 8.85 8.40 8.89 8.89 Lysine 6.43 6.54 6.65 6.28 5.96 6.29 6.48 6.43 6.50 6.68 6.64 6.63 6.55 6.59 6.59 6.44 Arginine 8.39 7.55 7.57 8.13 9.16 8.92 8.31 7.74 7.79 7.53 7.41 7.26 7.53 7.59 7.61 7.73 Biological 0.78 0.71 0.74 0.79 0.84 0.83 0.70 0.70 0.73 0.65 0.74 0.66 0.68 0.67 0.67 0.65 value-EAAI* Amino acids

* The biological protein value (EAAI index) is calculated by Professor Dimitar Pavlov (Trakia University, Stara Zagora)

The quantity of dicarboxylic amino acids, glutamic and aspartic, participating in physiological degradation of proteins in plant organism was greatest in the winter vetch grain. Under the conditions of the trial the average content of glutamic acid was 19.74 g 100g protein-1 and that of aspartic acid – 11.75 g 100g protein-1, being affected stronger by the sowing date than by the nitrogen fertilizing. The quantity of essential amino acids in grain is an important indicator of forage value. Lysine and leucine, the average values of which were 6.48 and 7.95 g 100g protein-1, changed their quantity to a greater extent under the influence of different degrees of the sowing date factor, whereas for isoleucine, phenylalanine, valine and histidine the effect of nitrogen fertilizing was decisive. The average content of isoleucine was 4.62 g 100g protein-1, the values of the studied variants being from 4.39 to 5.38 g 100g protein-1. 221



The phenylalanine plays an important structural role in the animal organism and its participation in the grain composition was on average 4.54 g 100g protein-1. Its variation according to variants was within narrowest limits. The recorded average quantity of valine in the grain was 5.48 g 100g protein-1, its values varying from 5.10 to 6.09 g 100g protein-1. More substantial differences between the studied variants were observed for histidine. It belongs to the group of heterocyclic amino acids and participates in the synthesis of nucleic acids and haemoglobin (Angelova et al., 1984). Its average value in the trial was 9.14 g 100g protein-1. The sulphur-containing amino acids methionine and cystine that are very important in animal nutrition were in insignificant quantities (0.45 and 0.70 g 100g protein-1, respectively), but their values according to variants varied considerably mainly under the influence of the sowing date. They play an exceptionally great role in the animal organism stimulating the growth and development of the young animals and making harmless many toxic products of metabolism (Angelova et al., 1984). The sowing date as a factor is also decisive in the synthesis of arginine, glycine, proline, alanine and tyrosine. This is confirmed by the studies of Tosheva & Marinov (1989), according to which the amino acid synthesis in the maize grain is influenced more by the moisture supply than by the nitrogen fertilizing. The average content of arginine under the conditions of the trial was 7.89 g 100g protein-1 and exceeded by 54.7% that found by Pavlov (1996) in spring vetch (Vicia sativa L.). Among the amino acids from the fatty order, the glycine, participating in the composition of many proteins, is of great importance. It is found in collagen of skin, tendons, joint ligaments, marrow, etc. (Angelova et al., 1984). The glycine quantity was on average 3.91 g 100g protein-1 in the winter vetch grain. Its values varied considerably under the influence of the studied factors. The contents of the amino acids alanine (4.48 g 100g protein-1) and proline (4.46 g 100g protein-1) had almost identical values, the latter being one of the main constituent parts of the collagen. Another vitally important aromatic amino acid is tyrosine. Under the conditions of the conducted trial its quantity was on average 1.82 g 100g protein-1. The only amino acid, the synthesis of which was influenced equally strongly by both studied factors was threonine. The average content of this essential amino acid in the vetch grain was 3.40 g 100g protein-1. Consideration of the complex interaction of the two factors showed that the variational coefficient (Dimova & Marinkov, 1999) that is an important statistical indicator had the lowest value (VC=2.38%) for aspartic acid and the highest one (VC= 51.11%) for methionine. Observing the EAAI index it was found that the nitrogen fertilizing decreased the biological protein value from 0.76 (variant T0) to 0.70 (variant T3). According to Pavlov (1996) the reason was that the fertilizing of legume crops with nitrogen decreases the amino acid participation in the protein due to increase of nonprotein nitrogen and as an end result, the biological protein value also decreases. Conclusions The sowing date and nitrogen fertilizing are factors that had effect on the amino acid synthesis in winter vetch grain. The fertilizing effect was not unidirectional. The increasing rates of nitrogen fertilizing resulted in a decrease of the biological protein value and content of most amino acids. An exception was observed for glutamic acid, threonine, serine, glycine and lysine, the maximum of which was reached when applying nitrogen at the dose of 60 kg ha-1. Considering the independent effect of the sowing date factor it was found that the amino acid accumulation in the vetch grain was highest for second or third date (except for glutamic acid and cystine), these dates being distinguished for lower temperature supply and rainfall. The synthesis of glutamic acid, aspartic acid, cystine, methionine, lysine, leucine, arginine, proline, glycine, alanine and tyrosine in the winter vetch grain was influenced more strongly by the sowing date and the synthesis of valine, phenylalanine, isoleucine, histidine and serine by the 222



nitrogen fertilizing. The only amino acid, the synthesis of which was influenced equally strongly by both studied factors was threonine. References Angelova L., Dzharova M., Marinov B, Stanchev H. (1984): The amino acids in nutrition of agricultural animals. Zemizdat, Sofia, Bulgaria, 5-10. Dimova D., Marinkov E. (1999): Experimental work and biometrics. Academic Publishing House of HAI, Plovdiv, Bulgaria, 137. Pavlov D. (1996): Productivity, feeding value, quality characteristics of different groups of forage crops and possibilities for their prediction. Dissertation. AA, Sofia, Bulgaria, 342. Pavlov D. (2002): Fertilizing effect on the content of amino acids and nonprotein nitrogenous compounds in perennial grasses. Scientific Works HAI Plovdiv, Bulgaria, vol. XLVII, No.2. Petkova R., Pavlov D. (2007): Influence of different concentrations growth regulators on the aminoacid composition of forage pea variety Mir grain. Journal of Mountain Agriculture on the Balkans, 10, 1, 113-121. Tosheva T., Marinov Y. (1989): Effect of irrigation, fertilization and seeding density on amino acid composition of maize grain. Plant Science, 3, 18-25

223


Self-pollinated crops Breeding for Resistance to Biotic and Abiotic Stresses Oral Presentation



USE OF MARKER-ASSISTED SELECTION (MAS) FOR PYRAMIDING TWO LEAF RUST RESISTANCE GENES (Lr9 and Lr24) in WHEAT Odile Moullet1, Dario Fossati1, Fabio Mascher1, Roberto Guadagnolo2, Arnold Schori1 1

Agroscope Changins-Wädenswil Research Station ACW, Plant Breeding and Genetics Resources, Route de Duillier, P.O. Box 1012, 1260 Nyon 1, Switzerland 2 University of Neuchâtel, Evolutionary botany laboratory, Institute of biology, rue Emile Argand 11, 2009 Neuchâtel, Switzerland E-mail: [email protected]

Abstract Two leaf rust resistance genes, Lr9 and Lr24 have been pyramidised through the use of simple sequence repeats (SSR) markers. The wheat lines obtained which carry the two resistance genes are indeed resistant to the leaf rust races currently present in Switzerland and have a very good baking quality. However these lines can only be considered as a first step, since it was difficult to reach an acceptable uniformity. Furthermore, sufficient yield for commercial success could not be achieved. However they can be used as parents to cumulate other resistance genes in new elite material. This first cycle of “pyramidisation” allowed us to evaluate the cost for marker-assisted selection (MAS). MAS proved to be an efficient tool in a breeding program. It is yet necessary to integrate this benefit into the global context of yield, resistance and quality required for the release of commercially successful wheat varieties. Key words: leaf rust, MAS, molecular markers, PCR, resistance breeding, SSR, wheat. Introduction Leaf rust is an important foliar disease of wheat. Growing resistant cultivars is probably the most efficient, cost-effective and environment-friendly method to control this disease (Singh et al., 2004). More than 70 specific leaf rust resistance genes are known (KOMUGI, 2008). Many of them have been introgressed into wheat from wild relatives as Lr9 from Aegilops umbellulata or Lr24 from Agropyron elongatum. However the ability of the pathogen to adapt to new resistances by single step mutation constitutes a never-ending challenge for breeders. Frequently, the pyramiding strategy, combining several resistance genes into one cultivar, has been proposed to enhance the durability of resistances (Pedersen & Leath, 1988). Combining two or more resistance genes using classical host-parasite infection methods is highly time-consuming and needs specific virulent pathotypes that are often not available or too risky to use. Molecular biology and marker-assisted selection (MAS) offers the possibility to trace resistance genes in cultivars in an easier and more efficient way. At least 33 molecular markers linked to Lr resistance genes have been described at present (KOMUGI, 2008). When the project started, no virulence was found for Lr9 or Lr24 in the leaf rust populations in Switzerland. And, worldwide, no virulence was reported for the combination Lr9 and Lr24 (Schachermayr et al., 1995). Molecular markers and plant material for these genes were also available. Similar studies have been done by other groups in Europe (Nocente et al., 2007; Vida et al., 2005) but only little information is available on the lines and their commercial outcome. In this article, we evaluate the pyramidising of two leaf rust resistance genes by MAS in a small breeding program. Materials and Methods Plant material. The Lr9 and the Lr24 resistance gene donors (‘Tranfer’/6 * “Thatcher” and ‘Agent’/6 * “Thatcher”) were backcrossed seven times to susceptible Swiss winter wheat cultivar “Arina” and selfed to produce the F8 generation. NILs containing Lr9 gene were crossed with the Lr24 one. Three F1 populations were crossed with four advanced lines giving 765 F2 progenies on which, marker assisted selection (MAS) was used to select 194 lines containing both resistance genes. After 6 years of classical breeding, MAS was applied to confirm the presence of Lr9 and/or Lr24 in 30 of the F8 remaining lines. 225



Leaf rust and other diseases evaluation. The lines were evaluated for leaf rust and other diseases in separate nurseries using artificial infection with mixtures of isolates collected in Switzerland as describe by Michel (2001). Homogeneity. The lines homogeneity was evaluated comparing the plant height, the spike and leaves morphology and colour of 30 head-to-row lines. Lines with insufficient uniformity were selfed one to tree more generation before testing them in yield trials. Field trials and bread making quality. Small-plot (7m2) trials with 2 replications have been carried out in 4 locations during one year. Sample collected from yield trial were used for quality parameters evaluation involving protein content and Zeleny sedimentation value (ICC-Standards methods, 1999). DNA extraction. Genomic DNA from the 765 F2 populations was isolated from leaves tissue according to Lagudah and Appels (1991). For the 30 advanced lines, the DNA was extracted with a quick an efficient method. Two young leaves were grown in 2 ml of extraction buffer (Tris-HCl 50 mM pH 8, EDTA 50 mM ph8, sucrose 15 % (w/v), NaCl 250 mM). After centrifugation (5 min at 6’000 x g), the supernatant was removed and the pellet, suspended in 340 ml of Tris-HCl 20 mM pH8, EDTA 10 mM pH8 and SDS 1.2 % (w/v), was incubated for 15 min at 70 EC. Then 150 ml of 7,5 M ammonium acetate were added, the mixture incubated on ice for 30 min and centrifuged at 16’000 x g for 15 min. The DNA from the supernatant was concentrated by ethanol precipitation, washed with 75 % (v/v) ethanol and dissolved in TE at a concentration of 25 ng/ml. PCR amplification. Polymerase chain reaction (PCR) was performed in 10 ml volumes with 25 ng of template, Qiagen PCR buffer and Q-solution as recommended by the manufacturer, 0.2 mM dNTPs, 1 mM of each primer, 1.5 mM MgCl2 and 0.35 U HotStar Taq DNA polymerase (Qiagen). Amplifications were performed in an Hybaid PX2 thermocycler programmed at 95°C for 15 min, followed by 35 cycles at 94°C for 1 min, at 64 °C for 1 min 30 sec and at 72°C for 2 min 30 sec. The extension of amplified fragment was achieved at 72°C for 10 min. The sequences of the specific primers for Lr9 and Lr24 are shown in table 1. Table 1. Sequence of primers for STS locus linked to the Lr9 and Lr24 resistance genes Gene Lr9

Lr24

Name Primer sequence (5’ - 3’) J13 F – CCA CAC TAC CCC AAA GAG ACG R – TCC TTT TAT TCC GCA CGC CGG SCS5 F – TGC GCC CTT CAA AGG AAG R - TGC GCC CTT CTG AAC TGT AT J09 F – TCT AGT CTG TAC ATG GGG GC R - TGG CAC ATG AAC TCC ATA CG H05 F – AGT CGT CCC CGA AGA CCC GCT GGA R - TCG TCC CCT GAT GCC ATG TAA TGT

Reference Schachermayr et al., 1994 Gupta et al., 2005 Schachermayr et al., 1995 Dedryver et al., 1996

Electrophoresis. Amplification products were separated by electrophoresis on 1.5 % agarose gel in 1 X TAE buffer at 100 V for 3 h and visualized under UV light after ethidium bromide staining. Results and Discussion Homogeneity. At F7, only 14.3% of the 98 F7 “Lr9/Lr24 lines” reached a sufficient uniformity to be tested in yield trials and to start the maintenance breeding compared to 20.6% for the “normal” lines. Leaf rust markers and disease resistance. The MAS at F2 with dominant PCR-based markers discard the plants without Lr genes but cannot sort heterozygous from homozygous plants. Lines without the genes continue to appear after self-pollination of heterozygous plants. The second PCR was performed with accurate concentration of DNA isolated from 6 to 10 plants. For the heterozygous lines, the band intensity was lower than the one obtained with homozygous lines. 226



The heterozygosity of these lines was confirmed by analysing 6 plants separately. For the 30 lines tested in yield trials, 6 lines have markers for Lr9 and Lr24, 10 lines only for Lr24, 4 lines only for Lr9 and 10 lines have no markers for neither resistance genes. In fact, the susceptibility to leaf rust confirmed the role of Lr9 and Lr24 in the resistance response. Even if the virulence Lr9 is now frequently observed in Switzerland (F. Mascher, data not published), lines possessing Lr9 show few or no symptoms. On the other hand, some lines possessing Lr24 markers display low symptoms even if virulence Lr24 has not been reported in Switzerland. The few lines with both Lr markers have absolutely no symptoms (Fig.1). Arguably the pyramidisation of both resistance genes is feasible and the results obtained are efficient but the durability of the resistance has still to be proved. The mean resistance of these lines against other important diseases is very good for stripe rust (note 2.0), septoria nodorum blotch (index leaf 79, index spike 85) and good for septoria tritici blotch (index 91), powdery mildew (note 2.4) and fusarium head scab (3.2).

Figure 1: Evaluation of leaf rust resistance (1: no symptom; 9: fully susceptible) of F8 lines derived from the project of pyramidisation of Lr9 and Lr24. Yield trial. The 30 lines mean yield is only 90% of the usual standards cultivars hence insufficient for a commercial cultivar. Even if the number of lines is certainly insufficient to compare with confidence the yield between the lines with or without Lr markers or between the lines from different crosses we observe that the relative yield for the 6 lines with Lr9 and Lr24 markers is 94.2% (86.5% to 100.9%) compared to 88.8% (77.7% to 97.4%) for the 10 lines without Lr markers. The 8 lines issued from the cross with the best parent have a 94.1% relative mean yield compared to 80.8% for the 4 lines issued from the lowest yielding parent. Bread making quality. The 30 lines Zeleny mean value (60.2ml, 43.7ml to 73.5ml) and the protein content mean values (13.5%, 11.7% to 15.0%) indicate a good to very good bread making quality for the lines compared with the results for “Arina” (Zeleny 52.3ml, protein content 13.8%) and “Runal” (Zeleny 65.2ml, protein content 14.3%), respectively good and very good bread making quality standards. Cost. If we don’t include costs for markers development and field trials cost (sowing, treatments, sampling), we need now, in our conditions, 1 person, two weeks and a cost of 515.-C for analyzing 1000 samples. Conclusions The lines herein obtained, even though displaying good resistances and excellent bread making quality, had low yield and more difficulties to reach uniformity. They could not be developed as commercial cultivars and are used as genitors. The low yield and low uniformity might be unwanted effects of Lr genes and of “drag genes” unintentionally introduced from the wild relative. This is especially valid for the Lr24 donor where a large segment has been translocated 227



(Schachermayr et al., 1995). It might be also caused by the genetic value of the advanced lines used as genitors in this experiment. The number of lines tested here is too small to have clear evidences for one or other hypothesis. Some of the best lines have been crossed with more yielding lines and with lines with other Lr genes especially adult plant resistance genes to combine different kind of resistance. The MAS was effective for pyramidising two resistance genes but the investment was important just for one of the six important diseases we breed for. Even if the cost of MAS has dropped dramatically during the last decade, it is still a challenge to find the best way to use it in a breeding program with the aim of producing cultivars not only resistant against one single disease but aiming at an optimal combination between yield, resistance and quality. References Dedryver F., Jubier M.-F., Thouvenin J., Goyeau H., (1996). Molecular markers linked to the leaf rust resistance gene Lr24 in different wheat cultivars. Genome 39, 830-835. Gupta S., Charpe A., Koul S., Prabhu V., Mohd Q., Haq R., (2005). Development and validation of molecular markers linked to an Aegilops umbellulata-derived leaf rust resistance gene, Lr9, for marker-assited selection in bread wheat. Genome 48, 823-830. KOMUGI (2008). Integrated wheat science Database KOMUGI. http://www.shigen.nig.ac.jp/wheat/komugi/ ICC Standards (1999). International association for cereal science and technology (ICC), Vienna Lagudah E., Appels R., (1991). The Nor-D3 locus of Triticum tauschii: natural variation and genetic linkage to markers in chromosome 5. Genome 34, 387-395. Michel V., (2001). La sélection de variétés de blé et de triticale résistantes aux maladies, Revue suisse Agric. 33(4), 133-140. Nocente F., Gazza L., Pasquini M., (2007). Evaluation of leaf rust resistance genes Lr1, Lr9, Lr24, Lr47 and their introgression into common wheat cultivars by marker-assisted selection. Euphytica 155, 329-336. Pedersen W.L., Leath S., (1988). Pyramiding major genes for resistance to maintain residual effects. Ann. Rev. Phytopathol. 26, 369-378 Schachermayr G., Siedler H., Gale M.D., Winzeler H., Winzeler M., Keller B., (1994). Identification and localization of molecular markers linked to the Lr9 leaf rust resistance gene of wheat. Theor. Appl. Genet. 88, 110-115. Schachermayr G., Messmer M., Feuillet C., Winzeler H., Winzeler M., Keller B., (1995). Identification of molecular markers linked to the Agropyron elongatum-derived leaf rust resistance gene Lr24 in wheat. Theor. Appl. Genet. 90, 982-990. Singh R., Datta D., Priyamvada, Singh S., Tiwari R., (2004). Marker-assisted selection for leaf rust resistance genes Lr19 and Lr24 in wheat (Triticum aestivum L.). J. Appl. Genet. 45(4), 399-403. Vida G., Gál M., Szunics L., Veisz O. (2005). Use of conventional breeding and marker-assisted selection to improve the leaf rust resistance of winter wheat. Proceedings of the 7th International Wheat Conference, Wheat production in stressed environments, Mar del Plata, Argentina, 27 November – 2 December 2005, Posters presentation.

228



PHOTOSYNTHETIC TECHNIQUES IN SCREENING OF WHEAT (Triticum aestivum L.) GENOTYPES FOR IMPROVED DROUGHT AND HEAT STRESS TOLERANCE Marek @iv~ák, Jana Repková, Katarína Ol{ovská, Marian Bresti~ Department of Plant Physiology, Slovak Agricultural University, Tr. A. Hlinku 2, 949 76 Nitra, Slovakia. E-mail: [email protected]

Abstract We assessed several traits and methods of sensing drought and high temperature susceptibility in the vegetation pot and field trials with a collection of winter bread wheat genotypes. Gasometrically measured decrease CO2 assimilation rate was mainly due to the stomatal closure. Studied genotypes differed in sensitivity of stomatal closure and hence in CO2 assimilation rate, too. Delayed stomatal closure with higher values of net assimilation was correlated with higher grain yield in drought conditions. Similarly, the non-stressed values of transpiration efficiency were also related to higher drought tolerance. Fast chlorophyll a fluorescence kinetics measurements seem to be a promising tool for detection of drought and heat susceptibility in observed plant material. Evaluation of drought effects in observed genotypes by chlorophyll fluorescence was feasible using Performance Index (PI) as the most sensitive fluorescence parameter characterizing better the drought susceptibility of studied genotypes. We elaborated a high temperature test with leaf segments measuring plenty of material in a short time. We observed significant differences in sensitivity of individual genotypes based on fluorescence parameters. Key words: drought stress, heat stress, photosynthesis, screening criteria, tolerance, wheat Introduction Photosynthesis is the crucial process leading to biomass and yield formation. However it is strongly dependent on environmental conditions and the photosynthetic apparatus is characteristic by its vulnerability (Long et al., 1994). Plant species and varieties dispose of different level of protective mechanisms (Reddy et al, 2004). There are a lot of genetic resources, which could serve as a donors of improved tolerance of photosynthetic apparatus to different environmental factors; however they have to be identified and analyzed for distinguishing individual protective mechanisms that are coactive in creation of complex characteristic named as tolerance. For this purpose it is advantageous to use modern physiological techniques rather than empirical methods. In our experiments we aimed at assessment of photosynthetic and related techniques and routines and their ability to identify different level of tolerance to drought and high temperature at the level of leaves. We did a very detailed work with middle-sized group of wheat genotypes in pot experiments supplemented with application of selected methods in field trials with higher number of genotypes (poster). Materials and Methods Plants of winter wheat (Triticum aestivum L.), genotypes Viginta (abbr. VIG), Ilona (ILO), Arida (ARI), Eva (EVA) from Slovakia; Pobeda (POB) from Serbia; Stephens (STE) from USA and Amerigo (AME) from France, were cultivated in the pot experiments in three seasons. After anthesis a part of plants was exposed to slowly developing water stress induced by restriction of irrigation. Water supply by rain was avoided using a transparent foil shelter. The heat test was done on leaf segments exposed to high temperatures (30 – 45 °C) for 1 hour. The segments were closed in glass tubes immersed in thermostated water bath. Measured characteristics: Leaf water status was calculated as relative water content (RWC) using the fresh (W), saturated (WFT) and dry mass weight (WD) of leaf segments (RWC (%) = (W – WD) / (WFT – WD) * 100). The chlorophyll a fluorescence emitted by leaves after excitation with red light was measured in the dark adapted plants (30 min.) using fluorometer (Handy PEA, Hansatech, UK). Collected data were analyzed by the JIP-test (Strasser et al., 1995) and software Biolyzer©. 229



Stomatal conductance (gs) was measured by porometer Delta T AP4 (Delta-T Devices, UK) on both abaxial and adaxial part of flag leaves. Gas exchange measurements were provided on the same leaves within the open gas exchange measurement system Ciras-2 (PP-systems, UK) using artificial light source (800 mmol.m-2.s-1) to get saturating irradiance. The main measured parameters were the net assimilation rate (PN, mmol CO2.m-2.s-1) and leaf transpiration rate (E, mmol H2O.m-2.s-1). From PN and E values we calculated the photosynthetic water use efficiency (WUE) as WUE = PN / E. Data analysis. Data measured or calculated from replicates were averaged and plotted with a standard deviation. To compare the effect of drought stress on yield and other parameters (X) we selected the drought susceptibility index (SIX), a relative parameter, calculated for each genotype after Fischer and Maurer (1978) as: SIX = (1-Yds/Yno) / (1-Xds/Xno), where Yds is the value of parameter under drought, Yno is the value of parameter under near optimum conditions, Xds is Xno is the average value of parameter of all genotypes under drought and the average value of parameter of all genotypes under near optimum conditions. The relationships between the selected parameters and grain yield were assessed under drought by correlation analysis using analysis of variance (SigmaPlot 9.0 software). Results and Discussion Drought stress. Drought stress affected grain yield as well as all observed parameters in all genotypes. However, there were different severity in individual genotypes and parameters as shown by values of susceptibility indices (table 1). The higher value represents the more severe impact of drought stress on observed characteristic (grain yield or measured parameter). Thus the most drought susceptible cultivar considering grain yield was Eva (SI = 1.340 ± 0.016), in contrary as most tolerant appeared genotype Ilona (SI = 0.550 ± 0.110). Wheat genotypes differed in the sensitivity for stomatal closure; however, the differences were distinct mainly in few days. This fact was reflected also in values of standard deviation, which were the highest among all parameters observed and hence, differences between genotypes were statistically less significant. A similar trend was observed from the measurements of CO2 assimilation, but with lower variation of measured data and higher statistical significance. One of the traits which signalize saving the water in plants is the photosynthetic water use efficiency (Turner, 1997). We recorded also for this parameter statistical differences between observed genotypes. All of these photosynthetic parameters are strongly dependent on activity of stomata. The delayed stomatal closure supports continuing growth and CO2 assimilation in case if it is accompanied with cell osmotic adjustment and turgor maintenance (Blum et al., 1999). The chlorophyll fluorescence parameters are almost independent of previously mentioned. Visually evaluated, water deficit initiated only moderate changes in the fluorescence transient. However, many of fluorescence parameters derived from the JIP-test, were able to reflect changes during the drought stress. The most sensitive fluorescence parameter at 80% dehydration was Performance Index (PI), which showed a statistically significant correlation with RWC level in comparison to Fv/Fm, which was reduced only at a very strong water deficit (less than 70% RWC). The sensitivity of PI to water loss was almost similar to the sensitivity of stomata. What was important, we recorded differences between values recorded in observed genotypes during drought stress (table 1). Expression of measured characteristics in relative units allows comparing their susceptibility to water stress (table 1). The data showed similar trends in the stomatal conductance, net assimilation rate, PI and grain yield parameters under water stress. For example, the most drought susceptible genotype considering grain yield (cv. Eva) was susceptible also in other measured parameters (except stomatal conductance with moderate values); in contrary, the most tolerant genotype considering grain yield (cv. Ilona) had low SI values also for other measured parameters. We assessed correlations between relative decrease of grain yield and relative change or absolute values (WUE) of all measured physiological parameters (table 2). 230



Table 1. The average values and standard deviations of susceptibility indices calculated for grain yield and other parameters in all observed genotypes in all measuring seasons. Cultivar Eva Stephens Viginta Arida Amerigo Pobeda Ilona

Grain yield Average 1.340 1.200 1.120 1.090 0.940 0.900 0.550

SD 0.016 0.140 0.220 0.180 0.012 0.040 0.110

Susceptibility indices (rel. units) Net assimilation Water use Stomatal Performance rate efficiency conductance index Average SD Average SD Average SD Average SD 1.277 0.012 1.241 0.099 0.977 0.103 1.068 0.012 0.947 0.239 1.108 0.067 1.172 0.283 1.129 0.150 1.023 0.113 0.844 0.026 1.172 0.035 0.979 0.085 0.956 0.044 1.055 0.050 1.106 0.130 1.092 0.161 1.130 0.043 0.888 0.037 0.734 0.143 0.880 0.061 0.906 0.047 1.014 0.003 0.933 0.127 0.911 0.091 0.750 0.062 0.956 0.027 0.828 0.140 0.884 0.016

Table 2. Parameters of correlation analysis and analysis of variance made for relationship between relative grain yield decrease and relative increase/decrease of selected parameters by drought stress. Level of correlation classified according to Cohen (1988). Correlation Power of p. index test (a=0.05)

R

2

Correlation parameters Trait/method

Level of correlation

Stomatal conductance measured in non-stressed plants

0.6493

0.8721

0.4216

high

Water use efficiency measured as PN/E

0.6382

0.3265

0.4073

high

Net assimilation rate during dehydration

0.6283

0.3146

0.3947

high

Chlorophyll Fluorescence - Performance index

0.5671

0.5689

0.3216

high

Stomatal conductance measured in stressed plants

0.523

0.6414

0.2736

high

The results in table 2 show relatively high level of correlation between grain yield decrease and measured parameters. However, low number of genotypes and repetitions in some measurement caused, that only correlation of stomatal conductance measured in non-stressed plants was shown as statistically significant. However, this parameter is closely related to photosynthetic water use efficiency with very similar correlation index. Also chlorophyll fluorescence with performance index as evaluated parameter looks very promising (Zivcak et al., 2008). The advantage of this method is also its rapidity with hundreds measurements that could be done within one hour compared to several tenths per hour made used stomatal conductance measurements by porometer and less than ten gasometric measurements workable within same time.

Figure 1. a) genotype variability in maximum quantum yield of PSII photochemistry (Fv/Fm) at the temperatures from 30 to 45°C; b) Fv/Fm measured after 1-hour treatment of leaf segments at 40°C in observed genotypes. Small letters identify statistically different groups. 231



High temperature test. The heat stress affected directly and markedly the plant photochemistry. Temperature up to 37.5°C had only small impact on Fv/Fm parameter with almost no genotypic variation (figure 1a). At higher temperatures (over 40°C), the differences among genotypes were also diminished. The temperature of 40°C allowed distinguishing the genotypes according to their thermostability (figure 1a,b). Maximum quantum yield of the photochemistry (Fv/Fm) was used to determine genotypic differences in heat stress effects. The method is very simple, rapid and easy-to-do and matches the basic requests for physiological methods useful for plant breeding (Reynolds et al., 2001). However, it is sensitive to interaction with another stresses, for example drought stress increases tolerance to heat stress (Lu and Zhang, 1999) and any other biotic and abiotic stress (e.g. pests, diseases) can distort results of measurements. Conclusions Photosynthetic parameters measured in drought and heat stress conditions showed sufficient genotypic variability and correlation level with grain yield. Development of portable, easy operable and efficient devices enables us to test a lot of material in short time. Especially, the fast chlorophyll fluorescence method looks very promising; however, for successful use will be necessary good experimental design and perfect trial management and maintenance. Acknowledgement The work was supported by the projects APVV LPP-0345-06 and AV MS SR - Climate change and drought in Slovak Republic: impact and scopes for sustainable yield production and quality. References Blum A, Zhang J. X, Nguyen, H. T. (1999). Consistent differences among wheat cultivars in osmotic adjustment and their relationship to plant production. Field Crops Research, 64, 287-291. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, Lawrence Erlbaum, 567 p. Fischer, R. A., Maurer, R. (1978). Drought resistance in spring wheat cultivars: I. Grain yield responses. Australian Journal of Agricultural Research, 1978, 29, 897-912. Long S. P., Humphries S., Falkowski P. G. (1994): Photoinhibition of Photosynthesis in Nature. Annual Review of Plant Physiology and Plant Molecular Biology, 45, 633-662. Lu, C., Zhang, J. 1999. Effects of water stress on photosystem II photochemistry and its thermostability in wheat plants. In: Journal of Experimental Botany, 1999, 336, 50, 1199-1206. Reddy A. R., Chaitanya K. V., Vivekanandan M, 2004. Drought-induced responses of photosynthesis and antioxidant metabolism in higher plants. Journal of Plant Physiology, 161, 11, 1189-1202. Reynolds MP (2001) Application of Physiology in Wheat Breading. In: Reynolds MP ed. Applicaton of Physiology in Wheat Breeding. CIMMYT, Mexico, 2-16. Strasser R. J., Srivastava A., Govindjee. (1995). Polyphasic chlorophyll a fluorescence transients in plants and cyanobacteria. J. Photochem. Photobiol, 61, 32-42. Turner N. C. (1997). Further Progress in Crop Water Relations. Adv. Agron, 58, 293-338. Zivcak, M., Brestic, M., Olsovska, K., Slamka, P. (2008). Performance index as a sensitive indicator of water stress in Triticum aestivum. Plant Soil Environment, 54, 4, 133-139.

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Self-pollinated crops Breeding for Resistance to Biotic and Abiotic Stresses Oral Presentation CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008

IMPORTANCE OF DIAGNOSTIC MARKERS FOR THE MANAGEMENT OF SOIL-BORNE VIRAL DISEASES OF BARLEY AND WHEAT Dragan Perovic1, Miros³aw Tyrka2, Jutta Förster3, Pierre Devaux4, Djabbar Hariri5, Morgane Guilleroux5, Kostya Kanyuka6, Rebecca Lyons6, Jens Weyen3, David Feuerhelm7, Ute Kastirr8, Pierre Sourdille9, Marion Röder10 and Frank Ordon1 1

Julius Kuehn-Institute, Federal Research Centre for Cultivated Plants, Institute for Resistance Research and Stress Tolerance, Erwin-Baur-Str. 27, 06484 Quedlinburg, Germany; e-mail: [email protected] 2 Laboratory of Population Genetics, Polonia University, Pu³askiego 4/6, 42-200 Czêstochowa, Poland 3 Saaten-Union Resistenzlabor GmbH, Hovedisser Str. 92, 33818 Leopoldshöhe, Germany 4 Florimond Desprez, 3, Rue Florimond Desprez, 59242 Cappelle en Pévèle, France 5 INRA, BIOGER, Route de Saint Cyr, F-78026, Versailles Cedex, France 6 Centre for Sustainable Pest and Disease Management, Department of Plant Pathology and Microbiology, Rothamsted Research, Harpenden, Hertfordshire, AL5 2JQ, United Kingdom 7 Elsoms Seeds LTD, Pinchbeck Road, PE11 1QG Spalding, United Kingdom 8 Julius Kuehn-Institute, Federal Research Centre for Cultivated Plants, Institute for Epidemiology and Pathogen Diagnostics, Erwin-Baur-Str. 27, 06484 Quedlinburg, Germany 9 INRA; UMR 1095 Amélioration et Santé des Plantes, Domaine de Crouelle 234, Avenue du Brézet, Clermont Ferrand, France 10 Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Gatersleben, Germany

Abstract Soil-borne viral mosaic disease is a major threat to crop production. Yield losses in barley and wheat caused by Barley mild mosaic virus (BaMMV), Barley yellow mosaic virus (BaYMV), and Soil-borne cereal mosaic virus (SBCMV) can reach up to 50-70% in susceptible varieties. Since their first detection in Japan and USA, respectively, these viruses have become important pathogens in other countries throughout the world including several European countries (France, Italy, UK, Germany). It is likely that over time these viruses will spread to other parts of Europe. Due to transmission by the soil-borne plasmodiophorid Polymyxa graminis, chemical measures against soil-borne viruses are neither economically nor ecologically acceptable. Therefore, breeding and growing of resistant cultivars is the only way to prevent high yield losses. During the last decade, marker assisted selection procedures (MAS) have gained evident importance in the breeding of resistant cultivars. These procedures are of special importance in European countries like Poland, Austria, Serbia etc., which lack uniformly infested fields required for reliable resistance screening of breeding lines. Recently, diagnostic SSR markers, QLB1 and Xgwm469-5D, which are closely linked to resistance genes against BaMMV/BaYMV in barley and SBCMV in wheat, respectively, were developed. These markers are very well suited for reliable MAS procedures in breeding for resistance to soil-borne viral mosaic diseases. Key words: barley, wheat, soil-borne viruses, BaMMV, BaYMV, SBCMV, diagnostic SSRs Introduction In large parts of Europe yield losses of winter barley caused by Bymoviruses (i.e. Barley mild mosaic virus (BaMMV) and Barley yellow mosaic virus (BaYMV) can reach 50-70% (Ordon et al., 2004), while Soil-borne cereal mosaic virus (SBCMV), belonging to the genus Furovirus, causes serious yield losses in winter wheat (Budge et al., 2008). Winter wheat and barley plants infected in the autumn are particularly sensitive to frost damage resulting in increased winter killing or reduced vigour during the following spring. Chemical measures except soil fumigation, which is unacceptable for economical and ecological reasons, are ineffective against P. graminis. Furthermore, as virus-containing resting spores of P. graminis are distributed by wind, water and machinery and can survive in the soil for decades (Brake and Langenberg 1988), crop rotation is not an effective option for disease control, either. Therefore, the only possibility of controlling soil-borne viruses of cereals on infested fields is by growing of resistant cultivars. 233


The use of molecular markers accelerates the breeding process and offers a straightforward aid in the selection of resistant genotypes. Marker-assisted selection (MAS) is very efficient in the backcross-assisted incorporation of single recessive resistance genes (Ordon et al. 2004) as well as in the pyramiding of non-linked resistance genes (Werner et al. 2005). Microsatellites, also called simple sequence repeats (SSRs), are currently the most popular and widely used PCR-based marker systems in MAS. SSR markers combine a number of advantages for practical applications, as they are co-dominant and multi-allelic, stably inherited, amenable to automation and high-throughput analysis, and detect the highest level of polymorphism per locus (Röder et al. 2004). Up to now, sixteen BaMMV and BaYMV resistance genes have been identified in barley and assigned to at least 8 independent genetic loci. In wheat, only one locus controlling resistance to SBCMV has been identified (Bass et al., 2006). Development of genetic markers closely linked to disease resistance genes is of special importance in wheat and barley molecular breeding as fields uniformly infested with soil-borne mosaic viruses required for reliable phenotypic selection are quite rare. The cloning of the eIF4E (eukaryotic translation initiation factor 4E) gene from barley has allowed the identification of single-nucleotide polymorphisms (SNPs) present in the rym4 and rym5 alleles of Hv-eIF4E which specify resistance against different strains of BaMMV and BaYMV (Kanyuka et al., 2005; Stein et al. 2005). This has improved the understanding of the molecular mechanism of this plant-virus interaction and has enabled the development of single mutation based PCR assays (Pyrosequencing; Ronaghi et al. 1998), which are theoretically ideal for the application in barley breeding. Nevertheless, the application of such markers is still too expensive, especially in smaller European cereal breeding companies. Therefore, SSRs remain the most preferable markers in MAS. In contrast to the resistance to BaMMV and BaYMV in barley, the information on resistance to SBCMV in wheat is less detailed. Also, in wheat the closest known linked marker locates at more than 2 cM away from the Sbm1 resistance locus and is not of high diagnostic value (Perovic et al, 2008). In this study, attempts were made to develop diagnostic SSR markers facilitating an efficient marker-assisted selection of the barley rym4/rym5 and the wheat Sbm1 resistance locus. Material and Methods GenBank sequence AY661558 (439 641 bp), annotated as the Hordeum vulgare ssp. vulgare eIF4E locus, was exploited to search for microsatellite repeats using the microsatellite identification tool (MISA) available at http://pgrc.ipk-gatersleben.de/misa (Thiel et al. 2003). The minimum number of repeats was set to 10, 6, and 5 repeats for mono-, di-, and trimeric microsatellites, respectively. Out of 57 detected SSR motifs, which fulfilled the above criteria, primers were designed for 5 motifs using the software package Primer 3.0 (Rozen and Skaletsky 2000). To obtain the information on the usefulness of new SSR markers, 6 reference barley cultivars with known resistance genes, 94 barley varieties from breeders’ collections and 673 barley breeding lines were analyzed. In wheat, SBCMV resistance was genetically characterised using two doubled haploid (DH) mapping populations. One population was derived from a cross between the resistant cv. 'Tremie' and the susceptible cultivars 'Texel', 'Aztek' and 'Soissons' (in total 64 DH lines), and another from a cross between the resistant cv. 'Claire' and the susceptible cv. 'Savannah' (126 DH lines). Phenotypic data of the SBCMV resistance were used for composing resistant and susceptible DNA bulks for Bulk Segregant Analysis (BSA) according to Michelmore et al. (1991). Resistant and susceptible bulks were screened with 256 EcoRI+3/MseI+3 AFLP primer combinations according to the 'AFLP Core Kit manual' (Invitrogen) and with a set of 162 genomic and EST-derived microsatellite markers according to Röder et al. (1998), Somers et al. (2004) and Zhang et al. (2005). Diagnostic value of newly identified closely linked markers was assessed using a collection of 99 wheat genotypes with known or putative resistance to SBCMV. 234


Results and discussion One of the new barley SSR markers, QLB1, developed from the available sequence of the Hv-eIF4E locus, was highly polymorphic. Analysis of six barley reference cultivars containing different alleles of Hv-eIF4E (‘Express’ rym4, ‘Tokyo’ rym5, ‘Miho Golden’ rym6, ‘Hiberna’ rym10, ‘Mokusekko’ rym1/rym5, and ‘Morex’ susceptible) revealed five unique banding patterns for QLB1 (Fig 1A). A linkage of QLB1 with the Hv-eIF4E locus was assessed by mapping this SSR in two high resolution mapping populations segregating either for rym4 or rym5 (Pellio et al. 2005). No recombinants between rym4, rym5 and QLB1 were detected leading to the conclusion that the latter co-segregates with the Hv-eIF4E locus. For physical mapping of QLB1, the sequenced barley ‘Morex’ derived BAC clone 519J04 containing the Hv-eIF4E gene was used (Wicker et al. 2005). PCR products of 359-bp and 373-bp were amplified from this BAC clone, thus confirming the physical linkage of QLB1 with Hv-eIF4E (Fig. 1A – line 1). Next, the SSR marker QLB1 was used to screen a set 100 barley genotypes, which included 6 reference cultivars and 94 cultivars from breeders’ collections. This study revealed a total of seven banding patterns for QLB1 (Tyrka et al. 2008). Two banding patterns were indicative of rym4 and rym5 (Fig 1A – lines 4 and 6), while four different patterns were observed in analyses of susceptible lines as well as lines carrying rym6 (Fig. 1A – lines 2, 3, 5 and 8) and rym10 (data not shown). QLB1 banding pattern for rym4-containing genotypes (Fig. 1A – line 4) was similar to that for some of the susceptible genotypes (Fig. 1A – line 5). However, these two patterns were distinguished by a reproducible smear around 380-bp associated with the susceptibility, and two smeary bands at 400-bp and 470-bp associated with the resistance. QLB1 marker analysis of the Chinese landrace Mokusekko, carrying rym5 and a non-allelic rym1 gene, revealed another unique banding pattern (Fig. 1A – line 7). The QLB1 banding patterns indicative of the presence of rym4 or rym5 were detected in 42 and 3 out of 100 tested cultivars, respectively. Recessive resistance genes from the barley gene pool exhibit a range of reactions to the different members of the barley yellow mosaic virus complex. These reactions vary from complete immunity (allelic rym1 and rym11, allelic rym4 and rym5, and rym15) and organ specific immunity in leaves (rym9) to partial resistance that can be broken at elevated temperatures (rym7, allelic rym6 and rym10, and rym8) (McGrann and Adams 2004). In the late 1980s, an isolate of BaYMV, BaYMV-2, which overcomes rym4-mediated immunity, was identified in Germany and England. New isolates of BaMMV that overcome rym5 have been recently found in France (BaMMV-Sil) and Germany (BaMMV-TEIK) (Kanyuka et al. 2004; Habekub et al. 2008). Therefore, backcross-based incorporation of new alleles in combination with pyramiding of non-linked rym resistance genes should be considered the method of choice for obtaining durable resistance (Werner et al. 2005). The cloning of Hv-eIF4E allowed the identification of single-nucleotide polymorphisms (SNPs) being responsible for the different specificities of rym4 and rym5 against the different strains of BaMMV/BaYMV (Stein et al. 2005). Nevertheless, the application of such markers is still too expensive, especially in smaller European cereal breeding companies, and therefore SSRs remain the most frequent markers used in MAS. Besides microsatellites, the digestion of PCR products with restriction endonucleases (cleaved amplified polymorphic sequences, CAPS) is a useful and relatively inexpensive method to reveal SNPs. But in contrast to QLB1, no CAPS are known which allow the simultaneous differentiation of carriers of rym4, rym5 and susceptible lines. Monogenically-inherited resistance to Soil-borne cereal mosaic virus (SBCMV) in hexaploid bread wheat cultivars ’Tremie’ and ‘Claire’ was genetically mapped to chromosome 5D. Marker saturation of this resistance locus with SSRs and AFLPs revealed three closely linked marker loci, Xgwm469, Xgwm805 and E37M49. A previously uncharacterized fragment of gwm469 mapped in two different DH mapping populations (Fig. 1B) either 1 cM distally or co-segregated with the SBCMV resistance locus, respectively, while E37M49 and Xgwm805 were located at 9 cM proximal to the resistance locus. The diagnostic value of Xgwm469-5D was assessed using a collection of 99 SBCMV resistant and susceptible wheat genotypes. Importantly, all of the susceptible 235


genotypes carried a null allele of Xgwm469-5D, whereas all resistant genotypes carried a 152-bp or 154-bp allele, respectively.

Fig. 1 A. Silver stained polyacrylamide gel showing seven banding patterns of the QLB1 SSR marker. Lines 1 - BAC clone 519J04 from barley ‘Morex’ carrying Hv-eIF4E; 2 - barley ‘Morex’ (S); 3 - barley ‘Tiffany’ (S); 4 - barley ‘Express’ (rym4); 5 - barley ‘Igri’ (S); 6 - barley ‘Tokyo’ (rym5); 7 - barley ‘Mokusekko’ (rym1 + rym5); 8 - barley ‘Miho Golden’ (rym6). B. Li-Cor gel image showing analysis of the SSR marker gwm469 in wheat genotypes. Xgwm469-5DL alleles linked to the SBCMV resistance are indicated by arrows. Lines 1 -microSTEP-20a DNA ladder (Microzone Ltd); 2 - wheat ‘Claire’ (R); 3 - wheat ‘Moulin’ (R); 4 - wheat ‘Wasp’ (S); 5 - wheat ‘Flame’ (R); 6 - wheat ‘Avalon’ (S); 7 - wheat ‘Cadenza’ (R). R - genotypes resistant to SBCMV, and S - genotypes susceptible to SBCMV. In contrast to resistance to bymoviruses in barley, only one major resistance locus effective against SBCMV has been identified in wheat. Two different alleles of the microsatellite marker Xgwm469-5D were found to be linked to this resistance locus. These data, therefore, suggest that the SBCMV-resistance existing in the worldwide wheat germplasm tested may have been derived from two separate sources. The low level of polymorphism at the Xgwm469-5D locus is in agreement with the low diversity of the D genome (Balfouier et al. 2007). Thus, this molecular marker, which is closely linked to the gene of interest and displays a low allelic diversity, is best suited for MAS. Conclusions We demonstrated that the QLB1 marker can be efficiently used in breeding for Hv-eIF4E based BaMMV/BaYMV resistance, as well as Xgwm469-5D in wheat breeding for SBCMV resistance. Both these markers are easy to use and their high diagnostic value facilitates quarantine breeding, i.e. the development of resistant cultivars in the absence of the respective viruses. Acknowledgements The work is supported by a grant in the Community’s Sixth Framework Programme (EU contract number COOP-CT-2004-512703). Financial support from the Ministry of Agriculture and Rural Development, Poland (to M.T.) as well as from the Federal Ministry of Food, Agriculture and Consumer Protection, Germany (to F.O.), are gratefully acknowledged. Rothamsted Research receives grant-aided support from the Biotechnology and Biological Sciences Research Council (BBSRC) of the United Kingdom. RL was supported by a BBSRC quota studentship awarded to Rothamsted Research. Literature Bass C, Hendley R, Adams MJ, Hammond-Kosack KE, Kanyuka K (2006) The Sbm1 locus conferring resistance to Soil-borne cereal mosaic virus maps to a gene-rich region on 5DL in wheat. Genome 49:1140-1148. Brakke MK, Langenberg WG (1988) Experiences with soil-borne wheat mosaic virus in North America and elsewhere. In: Cooper JI, Asher MJC (Eds) Developments in Applied Biology II. Viruses with Fungal Vectors. Association of Applied Biologists, Wellesbourne, UK, pp. 183-202.

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Self-pollinated crops Breeding for Resistance to Biotic and Abiotic Stresses Oral Presentation CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008 Budge GE, Ratti C,Rubies-Autonell C, Lockley D, Bonnefoy M, Vallega V, Pietravalle S & Henry CM (2008) Response of UK winter wheat cultivars to Soil-borne cereal mosaic and Wheat spindle streak mosaic viruses across Europe. Eur J Plant Pathol 120:259–272. Habekuß A, Kühne T, Krämer I, Rabenstein F, Ehrig F, Ruge-Wehling B, Huth W, Ordon F (2008) Identification of Barley mild mosaic virus Isolates in Germany Breaking rym5 Resistance. J Phytopathology156:36-41. Huth W (1989) Ein weiterer Stamm des Barley Yellow Mosaic Virus in der Bundesrepublik Deutschland. Nachrichtenbl Deut Pflanzenschutzd 40:49-55. Kanyuka K, Druka A, Caldwell DG, Tymon A, McCallum N, Waugh R, Adams MJ (2005) Evidence that the recessive bymovirus resistance locus rym4 in barley corresponds to the eukaryotic translation initiation factor 4E gene. Mol Plant Pathol 6, 449-458. Kanyuka K, Lovell D, Mitrofanova OP, Hammond-Kosack K, Adams MJ (2004) A controlled environment test for resistance to Soil-borne cereal mosaic virus and its use to determine the mode of inheritance of the resistance in the UK wheat variety Cadenza, and to screen diverse Triticum monococcum genotypes for potential sources of improved disease resistance. Plant Pathol 53:154-160. Michelmore RW, Paran I, Kesseli RV (1991) Identification of markers linked to disease resistant genes by bulk segregant analysis: a rapid method to detect markers in specific genomic regions using segregating populations. Proc Natl Acad Sci USA 88:9828-9832. Ordon F, Friedt W, Scheurer K, Pellio B, Werner K, Neuhaus G, Huth W, Habekuss A, Graner A (2004) Molecular markers in breeding for virus resistance in barley. J Appl Genet 45:145-159. Pellio B, Streng S, Bauer E, Stein N, Perovic D, Schiemann A, Friedt W, Ordon F, Graner A (2005) High-resolution mapping of the Rym4/Rym5 locus conferring resistance to the barley yellow mosaic virus complex (BaMMV, BaYMV, BaYMV-2) in barley (Hordeum vulgare ssp. vulgare L.). Theor Appl Genet 110: 283-293. Perovic D, Förster J, Devaux P, Hariri D, Guilleroux M, Kanyuka K, Lyons R, Weyen J, Feuerhelm D, Kastirr U, Sourdille P, Röder M and Ordon F (2008) Mapping and diagnostic marker development for Soil-borne cereal mosaic virus resistance in bread wheat (submitted to Mol Breed). Röder MS, Korzun V, Wendehake K, Plaschke J, Tixier MH, Leroy P, Ganal MW (1998) A microsatellite map of wheat. Genetics 149:2007-2023. Ronaghi M, Uhlén M, Nyrén P (1998) A sequencing method based on real-time pyrophosphate. Science 281:363-365. Rozen S, Skaletsky H, (2000) Primer3 on the WWW for general users and for biologist programmers. In: Krawetz S, Misener S, eds. Bioinformatics Methods and Protocols: Methods in Molecular Biology, Humana Press, Totowa: 365-386. Somers DJ, Peter I, Edwards K (2004) A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theor Appl Genet 109:1105-1114. Stein N, Perovic D, Kumlehn J, Pellio B, Stracke S, Streng S, Ordon F, Graner A (2005) The eukaryotic translation initiation factor 4E confers multiallelic recessive Bymovirus resistance in Hordeum vulgare (L.). Plant J. 42: 912-922. Thiel T, Michalek W, Varshney RK, Graner A (2003) Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.). Theor Appl Genet 106: 411-422. Tyrka M., Perovic D., Wardyñska A. and Ordon F. (2008): Development of a new diagnostic SSR marker for marker assisted selection of the Rym4/5 locus in barley. Journal of applied genetics 49 (2): 127–134. Werner K, Friedt W, Ordon F,(2005) Strategies for pyramiding resistance genes against the barley yellow mosaic virus complex (BaMMV, BaYMV, BaYMV-2). Mol Breed 16: 45-55. Wicker T, Zimmermann W, Perovic D, Paterson AH, Ganal M, Graner A, Stein N, (2005) A detailed look at 7 million years of genome evolution in a 439 kb contiguous sequence at the barley Hv-eIF4E locus: recombination, rearrangements and repeats. Plant J 41: 184-194. Zhang LY, Bernard M, Leroy P, Feuillet C, Sourdille P (2005) High transferability of bread wheat EST-derived SSRs to other cereals. Theor Appl Genet 111:677-687.

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ESTIMATION OF GRAIN YIELD AND ITS COMPONENTS IN WINTER WHEAT ADVANCED LINES UNDER FAVORABLE AND DROUGHT FIELD ENVIRONMENTS Nikolay Tsenov, Tatiana Petrova, Elena Tsenova Dobroudja Agricultural Research Institute, General Toshevo, Bulgaria E-mail: [email protected]

Abstract An attempt was made to find genotype differences in the performance of various lines of common origin with regard to grain productivity, and to evaluate the possibility for efficient selection under severe drought. Grain yield and its most important components were analyzed during two years contrasting by air temperature and amount of rainfalls; the data from year 2006 were taken as a 100 % basis. The drought resistance coefficient was used for evaluation of tolerance. The variances, covariances, and correlations between yield and its components were analyzed under the conditions of each year. Under drought, important traits such as 1000 grain weight and productive tillering did not significantly affect grain yield level. Their effect was probably indirect, expressed through yield and number of grains per spike. Under conditions of severe drought in the region of north-east Bulgaria, grain yield decreased with about 30 % in comparison to conditions favorable for obtaining the highest possible yield. Significant difference was established between drought-tolerant and drought-susceptible genotypes to the amount 10 - 14 % from the components directly determining grain yield. Key words: correlations, drought tolerance, winter wheat, yield components Introduction Breeding for increasing wheat adaptability and its drought resistance in particular is a difficult and complex task which requires long and large-scale work (Singh et al., 2007). Indirect methods and approaches are applied, which reveal only some nuances of each performance of the wheat varieties and lines (Richards et al., 2001). Conditions in Bulgaria imply at least medium level of drought tolerance due to existing and recently observed tendencies towards global warming (Knight et al., 2004, Slavov and Moteva, 2005). Several authors (Galovic et al., 2005; Christopher et al., 2008, Reynolds et al., 2008) report the use of a number of methods for evaluating the tolerance to drought. Each of these methods can be used, but ultimately grain yield level is the important trait reflecting possible genetic variations among the varieties. The criteria used for selection of spring wheat are difficult to extrapolate for winter wheat due to the much more specific growing conditions. Therefore the so called “residual yield” is used as a breeding tool for impartial assessment of drought resistance in the winter wheat type (Boyadjieva, 1999; Petrova, 2003). The aim of this investigation was: a) to find out if there is variation in the performance of different lines of common origin with regard to grain productivity and its components; b) to analyze the correlations of grain yield with its components under optimal and stress conditions; c) to assess the possibilities for selection of promising lines under severe drought. Material and methods The productivity of 75 promising winter wheat lines was investigated in the trial field of DARI-General Toshevo during 2006-2007. They were all grown by the Latin square method in six replicates together with three standard varieties, the size of the experimental plot being 15 m2. The studied traits were grain yield, number of productive tillers per m2, grain yield per spike, 1000 kernel weight and number of grains per spike. Grain yield and its most important components were analyzed during two years contrasting by air temperatures and rainfalls. In comparison to the mean statistic data for the period 1953-2007, year 2006 was characterized with optimal conditions for maximum expression of what productivity, and year 2007 had the severest drought for the last 55 years (Figure 1). 238



Figure1. Variations in daily temperature (a) and sum of precipitation (b) averaged for the period 1953-2007 and for the two years of study, during wheat vegetation These variations, rather contrasting both by year and in comparison to the long-term data, are a prerequisite for obtaining different results from the evaluation of the same genotype. The unique combination of mean daily air temperature with 3-5o C higher and sum of precipitation with 60 % lower than the mean value during 2007 was the reason for undertaking this investigation. The character number of productive tillers per m2 was determined at stage full maturity; grain yield per ha was re-calculated from the yield per plot averaged for all six replications; 1000 kernel weight was found by double counting of 500 grains per each replicate; grain weight per spike resulted from the ratio of yield and the number of productive tillers per plot; the mean number of grains per spike was re-calculated from 1000 kernel weight and grain weigh per spike. The variation in grain yield and its components was determined for the two years of study, taking the data from year 2006 as 100 % basis. The drought resistance coefficient was calculated by the method of Fisher & Maurer (1978). The variances and covariances analyses were done with the statistical software package Statgraphics XV, and the correlations of yield with its components were calculated separately for the two years of the investigation. Results and discussion The analysis of variances significantly determined the effect of the genotype and of the year for all investigated traits (data not given). This was another evidence for a strong variation caused by the contrasting growing conditions. Since grain yield was at the center of this study, the variances and covariances between grain yield and its components were determined (Table 1). Table1. Analysis of variance for grain yield in 2007 Source A:Genotype B:Year AxB NKS WGS TKW NPT

P-Value 0.0000* 0.0000* 0.0000* 0.0001* 0.0008* 0.094 ns 0.232 ns 239



Two of the investigated characters – 1000 kernel weight and number of productive tillers did not have a significant effect on yield under drought conditions in 2007. The other traits – number of grains per spike and grain weight per spike determined to a high degree grain yield under drought. In order to check and prove these results, the correlations between the productivity components under optimal (2006) and stress (2007) field conditions were compared (Table 2). It is evident that the above two traits – 1000 kernel weight and number of productive tillers had significant effect on grain yield under optimal conditions (r=0.348*) and (r=0.393*), respectively. The correlation data imply that grain weight per spike and number of grains per spike are the traits which determine the level of grain yield under various growing conditions. In this case we have a strong positive effect of the two characters both under conditions of optimal soil moisture, and under conditions of severe drought. Similar results have been reported by Dencic et al., (2000), with an emphasis on the strong effect of number of grains per spike. This means that the response of each genotype could be followed not only by the variation in grain yield, but also by the variation of the above two traits. Table 2. Pearson’s correlations between grain yield and its components (Above diagonal - 2006; Below diagonal - 2007) GY GY TKW NPT WGS NKS

-.025 ns .009 ns .419(**) .434(**)

TKW .348(**)

NPT .393(**) .212(**)

-.310(*) .293(*) -.257(*)

WGS .467(**) -.464(**) -.826(**)

.887(**) .826(**)

NKS .499(**) -.159(*) -.317(**) .092 ns

.826(**)

The question arises could this be a criterion for selection of drought-tolerant promising lines? The answer to this question may be positive if significant differences are found between the investigated genotypes (Table 3). Drought-tolerant were considered those varieties, which demonstrated the highest absolute yield during 2007 in combination with a lower rate of decrease in comparison to the previous year. The variation of each trait investigated in this study according to elementary descriptive statistics, can group the lines by their values and outline the significant differences between them. This was done and it became clear that the lines can be divided into two groups by each character: lines with values significantly higher than mean, and lines with values significantly lower than mean. Table3. Variations in grain yield and its components of the 12 most drought-tolerant and the 12 most drought-susceptible advanced lines and standards Groups of Varieties

Grain Yield, t/ha

2007 06-07, % High yielding 7.54 a 76.6 a Low yielding 6.46 c 65.8 c Difference 1.08* 10.8** Mean 6.95 69.1 Yantar –st 1 6.72 b 72.1 b Sadovo1–st 2 6.63 c 70.0 b Pobeda –st 3 6.14 c 67.1 b

Weigh of Grain per Spike

S dr 2007 06-07, % 0.91b 1.35 a 88.2 a 0.96 b 1.13 b 74.2 c 0.05 ns 0.22* 14.0** 1.00 1.24 80.1 1.02 b 1.38 a 82.6 a 0.99 b 0.88 c 67.0 c 0.95 c 0.87 c 61.8 c

S dr 1.12 a 0.94 c 0.18** 1.02 1.05 a 0.85 c 0.78 c

Number of Kernels per Spike 2007 06-07, % S dr 33.5 a 96.1 a 1.11 a 28.0 c 82.0 c 0.95 c 8.5** 14.1** 0.16** 30.1 86.1 1.00 34.4 a 95.1 a 1.10 a 20.6 c 75.3 c 0.87 c 22.3 c 72.9 c 0.85 c

a- significantly higher than mean value, b – insignificant difference compared to mean value; c – significantly lower than mean value; St 1 – highly tolerant standard; St 2 – medium tolerant standard; St 3 – susceptible standard

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Table 3 shows only the mean value of the two groups each consisting of 12 promising lines to demonstrate the significant difference between them. A comparison can be made to the used standards with regard to their response to drought. The only insignificant difference between the two groups was according to the drought resistance coefficient. As a result from the strong water deficiency in soil combined with high air temperature, the character number of grains per spike had the relatively lowest decrease (86 %), followed by grain weigh per spike (80 %). As a resultant character, yield decreased with 30 %, averaged for the whole group of investigated lines. Although the lines were grouped only by level of absolute grain yield, the variation in the other traits was also significant: 14.0* and 14.1* %, respectively. Interesting and somewhat unexpected was the fact that in both traits the drought resistance coefficients of the tolerant group were significantly higher and were analogous for the investigated traits. Among the studied lines there were genotypes with different drought tolerance regardless of their common pedigree. On the other hand, the information about the high drought tolerance of the sibling lines is an important indication for the combining ability of the parental components in this respect. The future breeding program can be built on accessions which were included in such valuable combinations between the two traits in the new lines. This indicates the existing possibility for a real evaluation of the drought resistance level under contrasting conditions which nature rarely provides in two successive years. Furthermore, such an approach for evaluation of a given genotype would give very valuable information about the total adaptability and the stability of grain yield and its components under various growing conditions. Especially important would be lines with high drought tolerance and high grain yield under environments favorable for winter wheat. Conclusions Under drought, important characters such as 1000 kernel weight and productive tillering did not significantly affect grain yield level. Their effect was probably indirect, through the values of weight and number of grains per spike. Under conditions of strong soil and air drought in the region of north-east Bulgaria, grain yield decreased with 30 % in comparison to conditions favorable for obtaining the highest possible yield. The character number of grains per spike was important for grain yield under both optimal and drought conditions. Therefore it can be used for selection of genotypes with high production potential and high drought tolerance. References Boyadjieva, D. (1999): Breeding for productivity in wheat grown under the drought conditions of Sadovo -state and strategy. Agricultural Science, 37,3, 20-23 (In Bulg). Christopher J.T., Manschadi, A.M. Hammer, G.L. Borell, A.K. (2008): Developmental and physiological traits associated with high yield and stay-green phenotype in wheat. Aust. J. Agric. Res. 59, 4, 354-364. Dencic, S., Kastordi, R. Kobiljki, B. Duggan. B. (2000): Evaluation of grain yield and its components in wheat cultivars and landraces under near optimal and drought conditions. Euphytica, 113, 1, 43-53 Fischer, R.A. and Maurer, R. (1978): Drought resistance in spring wheat cultivars I. Grain yield response. Aust. J. Agric. Res., 29, 897-912. Galovic, V., Kotaranin, Z, and Dwencic, S. (2005): In vitro assessment of wheat tolerance to drought. Genetica, 37,2, 165-71 Knight, C.G., Raev, I. Staneva, M.P. (2004): Drought in Bulgarian, a contemporary analog for climate change. Studies in environmental policy and practice. Ashgate, 336 pp. Petrova, T. (2003): Effect of drought on some important agronomic characters in winter wheat. Res. Comm. Of USB, Dobrich, 5,1, 21-24 (In Bulg). Reynolds, M., Dreccer, F., Trethown, R. (2008): Drought-adaptive traits derived from wheat wild relatives and landraces. J. of Exp. Botany 58, 2, 177-186. Richards, M.P., Ortiz-Monasterio, J.I., McNab, A. (2001): Traits to improve yield in dry environments .In: Reynalds, Ortiz-Monasterio, J.I., McNab, A (Ed. Application of physiology in wheat breeding, Mexico, DF, chapter 7, 88-100. Singh, R.P., Huerta-Espino, J, Sharma, R. Joshi, A.K., Trethowan, R. (2007): High yielding spring bread wheat germplasm for global irrigated and rainfed production system. Euphytica 157, 3, 351-363. Slavov, N. and Moteva, M. (2005): About some drought characteristics in south Bulgaria. In: Balkan Scientific Conference, Karnobat, Bulgaria, vol.2, 369-373.

241


Self-pollinated crops Breeding for Resistance to Biotic and Abiotic Stresses Poster Presentation



INVESTIGATION ON THE RESPONSE OF CIMMYT COMMON WINTER WHEAT LINES TO BROWN RUST PUCCINIA RECONDITA F.SP.TRITICI Vanya Kiryakova Dobroudja Agricultural Institute – General Toshevo, 9520

Abstract During the period 2002 -2004 twenty common winter wheat lines of CIMMYT – Mexico were evaluated for resistance to brown rust Puccinia recondita f.sp.tritici. The investigation was carried out at Dobroudja Agricultural Institute – General Toshevo under conditions of infection field. During the winter of 2005 the same lines were tested under greenhouse conditions to 10 pathotypes of rust. The response of the Mexican lines was compared to the response of the isogenic lines; the type of resistance and the presumed genes in these lines were identified. The investigation showed that the Mexican wheat lines possess comparatively good resistance, both vertical and horizontal, and therefore can be valuable for breeding in Bulgaria. Key words: wheat, brown rust, races, pathotypes, isogenic lines, race – specific and race-non - specific resistance Introduction Brown rust Puccinia recondita Rob. ex Desm. f.sp.tritici Erikss is one of the economically most important diseases on wheat in Bulgaria. The development and introduction of resistant varieties is the economically most advantageous means for control of this pathogen. The breeding efficiency in this direction is determined by the proper selection of highly resistant forms in the initial material. While searching for sources of resistance, not only materials produced by Bulgarian breeding are being investigated, but also foreign wheat varieties that may be included in our breeding programs. Due to the fact that the race-specific genes can hardly provide long-term protection of the wheat crop, the race-unspecific resistance is dominant in CIMMYT breeding programs. Bulgarian breeding programs try to combine race-specific and race-non-specific resistance. In this sense the investigation on the CIMMYT materials can enrich our collections with resistant accessions. Materials and Methods The investigation was carried out during 2002 – 2004 in the infection field of Dobroudja Agricultural Institute. Twenty lines were studied; they were provided by Dr. S. Rajaram from CIMMYT. The lines were sown manually in 1.5 m rows, with a distance of 20 cm between them. The pathogene population under field conditions included all identified pathotypes belonging to the standard races most common during the investigated period: 167, 77, 57, 122, 149, 157 and 176. The artificial inoculation was initially done through planting of plants preliminary infected with the above races in the rows of the distributive variety – Michigan amber; later, at stage 32-36 (Zadoks et al, 1974) the infection was repeated through injection. Two rows of the distributive variety Michigan amber were sown across each 10 lines. The infection type and the attacking rate were read by Cobb’s scale modified by Peterson (Peterson at al., 1948) at stage milk maturity. For easier comparability of results the mean coefficient of infection was calculated - the so called corrected relative attacking rate P0 by (Zadoks, 1961) modified in Bulgaria by Donchev (data not published), introducing a coefficient which has the following values for the separate infection types: resistant R – 0.2 ; moderately resistant MR – 0.4; intermediate M – 0.6; moderately susceptible MS – 0.8 ; susceptible S – 1.0. According to their P0 values the lines were ranked according to the susceptible or resistant response they demonstrated. The lines with high to moderate resistance fall within the immune class I (P0 = 0), the rest being highly resistant VR (P0 = 0 – 4.99), resistant R (P0 = 5.0 – 10.0 ), and moderately resistant MR (P0 = 11.0 – 25.0). During the winter of 2005 the lines were tested under greenhouse conditions to the most virulent pathotypes of the Bulgarian brown rust population. The pathotypes were identified on the basis of 15 monogenic lines: Lr 1, Lr 2a, Lr 2b, Lr 2c, Lr 3, Lr 9, Lr 11, Lr 15, Lr 17, Lr 19, Lr 21, Lr 23, Lr 24, Lr 26, Lr 28 and were given code numbers (33567, 73763, 43763, 12562, 63563, 03762, 02562, 22762, 63562 and 43762) according to the method of Limpert and Muller (1994). Inocula243



tion of the lines at seedling stage was done according to the accepted laboratory methods (Browder, 1971). To improve spore formation, all plants were treated with 97 % Maleic hydrazide solution (1 g/ 3 l water). 9-12 days after inoculation the infection type was read according to the scale of Stakman et al (1962). The lines were not studied for their economic characters. Results and Discussion The response of the tested lines at stage second leaf to separate pathotypes which contained various combinations of avirulent and virulent genes, as well as at adult stage to a population of Puccinia recondita f.sp.tritici races is given in Table 1, and the infection type registered in the isogenic lines is presented in Table 1. Table 1. Response of isogenic lines at young stage to some Puccinia recondita f.sp.tritici pathotypes Lr genes

33567 Lr 1 S Lr 2a S Lr 2b R Lr 2c S Lr 3 S Lr 3ka S Lr 9 R Lr 10 S Lr 11 S Lr 15 R Lr 16 S Lr 17 S Lr 18 S Lr 19 R Lr 21 S Lr 23 S Lr 24 S Lr 26 S Lr 28 S Lr 30 S Lr 36 S Lr 42 R M.amber S

73763 S S S S S S R R S S S S S R S S S S R S S S S

43763 R R S S S R R S S S S S S R S S S S R S S R S

12562 S R R R S R R S S R S S R R S S R S R S S R S

Pathotypes 63563 03762 R R S R S R S R S S R R R R S S S S R S S S S S S S R R S S S S S R S S R R S S S S R R S S

02562 R R R R S R R S S R S S S R S S R S R S S R S

22762 R S R R S R R S S S S S S R S S R S R S S R S

63562 R S S S S R R S S R S S S R S S R S R S S R S

43762 R R S S S R R S S S S S S R S S R S R S S R S

The testing at seedling stage showed that the greater part of the lines at adult stage reacted as highly resistant to moderately resistant. These lines allowed the pathogen to develop up to a point, maintaining a good level of resistance to it. This type of resistance does not provoke breeding pressure and therefore does not stimulate the formation of new pathogenic pathotypes. At young stage these lines were susceptible to most of the pathotypes and demonstrated resistance to one, two, three or four pathotypes. The testing of lines RGL-15, RGL-25, RGL - 26, RGL- 48 at seedling stage showed that these lines had resistant reaction to seven, eight and nine pathotypes. Comparing the response of these lines and the response of the isogenic lines to the same pathotypes, the conclusion can be 244



made that line RGL-26 probably carries gene Lr 42. The response demonstrated by line RGL-48 corresponds completely to the response of the isogenic lines which contain gene Lr 28; therefore it may be presumed that this line carries the above gene. Furthermore, at adult stage the line was highly resistant. The investigation showed that this line combined both race-specific and race-non-specific resistance. The response of lines RGL-77, RGL-82 and RGL-89 corresponded to the response of the isogenic line carrying gene Lr 10 and therefore the suggestion that these lines carry the above gene is possible (Table 2). A large part of lines RGL-42, RGL-56, RGL-59, RGL-65, RGL-80, RGL-83 and RGL-92 demonstrated typical adult resistance; the type of response decreased at adult stage, while at stage second-first leaf these lines were susceptible to all rust pathotypes used in the investigation. Table 2. Carrier lines of certain resistance type and postulate genes Line RGL-7 RGL-15 RGL-25 RGL-26 RGL-35 RGL-42 RGL-45 RGL-48 RGL-56 RGL-59

Postulate genes Slow rusting Slow rusting Slow rusting Lr 42 Slow rusting APR Slow rusting Lr 28 APR APR

Line RGL-62 RGL-65 RGL-72 RGL-76 RGL-77 RGL-80 RGL-82 RGL-83 RGL-89 RGL-92

Postulate genes Slow rusting APR Slow rusting Lr 10 Lr 10 APR Lr 10 APR Lr 10 APR

Conclusions As a result from the investigation the following conclusions can be made: Although the lines were not studied for their economic characters, they are valuable sources of resistance: · Lines RGL-26, RGL-48, RGL- 76, RGL-77, RGL-82 and RGL- 89 probably carry the race-specific genes Lr 42, Lr 28 and Lr 10; · Lines RGL-42, RGL-56, RGL-59, RGL-65, RGL-80, RGL-83, RGL-92 carry race-unspecific genes and determine typical adult resistance; · Lines RGL-7, RGL-15, RGL-25, RGL-35, RGL-45, RGL-62, RGL-72 are not completely immune and allow the pathogen to develop up to a certain point therefore not stimulating the formation of new pathogen pathotypes. These lines are valuable for breeding. In this sense the investigated lines are of certain interest for breeding and can be used as sources of resistance in our breeding programs. Acknowledgements Thanks are due to Dr. S. Rajaram from CIMMYT for supplying the seeds of Mexican winter wheat lines studied in the present investigation. References Browder L.F.1971 Pathogenic specialization in cereal rust fungi, especially Puccinia recondite f.sp. tritici; concepts, methods of study and application, Technical Bulletin 1432, Agricultural Research service, r.45 Limprt E, Muller K. 1994 Designation of Pathotypes of Plant Pathogens, J Phytopathology 140,346-358 Peterson,R.E.,A.B.Cambell,A.E.Hennah,1948. Canad.J.Res.,C 26,65-70 Stakman E.C. Stewart D.M., Loegering W.Q. 1962 Identification of physiologic races of Puccinia graminis var tritici, Agr.Re.Service E 617( USDA), Washington D.C.,ARS 617,53 Zadoks,J C., Chang, T.T., and Konzak,G.F. 1974 A decimal code for the growth stages of cereals. Weed es.14,415- 421 Zadoks,J C.,1961. Plant Pathology,67,69-256

245



THE USE OF MAS FOR DEVELOPMENT OF MULTI-PATHOGEN RESISTANT LINES OF BARLEY Tibor Sedlá~ek, Lenka Stemberková, Martina Hanusová Research centre SELTON, s.r.o., Stupice 24, Sibøina 25084, Czech republic E-mail: [email protected]

Abstract The most critical factor for sucessfull planting of barley is resistance to biotic stresses, which in major part are caused by leaf and spike diseases. Among the most important leaf diseases caused by facultative pathogenic fungi belongs species Blumeria graminis, Pyrenophora teres, Puccinia hordei, Rhynchosporium secalis and Cochliobolus sativus. Complex of spike diseases is most commonly related to the fusarium species, including all negatives caused by the toxic secondary metabollites. The presented project is aimed for development lines of barley with cumulated genes of resistance to more diseases with the use of MAS. Up to present solving of this project we have cumulated genes Rph7 and mlo11. Acquired lines of barley are fully resistant to powdery mildew and leaf rust. The next aim is to cross these lines with donors of resistance genes for other diseases and the selection of lines with cumulated resistance genes with the help of molecular markers. Key words: breeding, barley, MAS, resistance, mildew, rust Introduction The most critical factor for sucessfull planting of barley is resistance to biotic stresses, which are in major part caused by leaf and spike diseases. Economical impact of diseases can be very serious - the yield losses can be as high as 100%. Very important are health risks caused by the toxic secondary metabollites of fusarium species. Therefore planting of resistant varieties can be a valuable solution of this problem. Blumeria graminis, Pyrenophora teres, Puccinia hordei, Rhynchosporium secalis and Cochliobolus sativus belong among the most important leaf diseases caused by facultative pathogenic fungi species. Resistance to these diseases is based mainly on major genes of resistance. Rph7 and rph16 for leaf rust resistance and mlo11/mlo9 resp. Mla complex for powdery mildew belong among the most important genes of resistance. These genes posess full resistance in Czech republic. Origin of rph16 is from Hordeum spontaneum, so it is more difficult to transfer it to the culture barley varieties – more backcrosses are required. There are molecular markers available for Rph7 (Graner et al., 2000) and mlo11 (Piffanelli et al., 2004). Complex of spike diseases is most commonly related to the fusarium species, including all negatives caused by the toxic secondary metabollites. Resistance to the fusarium heah blight (FHB) is based on quantitative genes. Several QTLs have been described (Dahleen et al., 2003; Mesfin 2003). Main effect in barley has the QTL on 2H where donor of tolerant locus is Chevron. This QTL can be trasferred with the help of microsatellite markers. Pyramiding of resistance genes can be a valuable tool for development lines of barley with multi-disease resistance. These lines then can be a resource in breeding of resistant varieties. Aim of our project is to develop such lines with the help of molecular assisted selection. Materials and Methods Plant material for testing was selected on the basis of glasshouse tests for resistance to leaf rust and powdery mildew. Two pieces of leaf long 3cm were collected from individual plants and dried at 40°C. DNA by CTAB method (Keb-Llanes et al., 2002) was extracted from these segments. DNA was analyzed by standard PCR with molecular markers MWG2133 (Ivandic et al., 1998), cMWG691 (Graner et al., 2000) and Mlo (Piffanelli et al., 2004). PCR products were run on 1%, resp 2% agarose gels and visualized by ethidium bromide under UV light. Individuals carrying resistance genes were crossed and F1 seed was acquired. F1 generation was planted during winter season in Chile and F2 seed was acquired. F2 generation was planted, and DNA was iso246



lated from selected individuals as described above. Presence of resistance genes Rph7 and mlo11 was identified as described above. Results and Discussion We have found 42 individuals with alleles of marker cMWG691 specific for Rph7 gene during the selection of resistance donors. Glasshouse tests verified resitance of these individuals to leaf rust. We detected several individuals with fragments unpublished in Graner et al., 2000 in the tested collection. These fragments could indicate new alleles. We didn´t find any plant with PCR products of marker MWG2133 specific for rph16 gene. We have found 141 individuals with alleles of marker Mlo specific for mlo11 gene. Glasshouse infection tests verified resistance of these individuals to powdery mildew. Targeted combination Rph7Rph7mlo11mlo11 was present in 18 individuals in F2 generation. These individuals are fully resistant to powdery mildew and leaf rust. Our next aim is to cross these lines with donors of resistance genes for other diseases and the selection of lines with cumulated resistance genes with the help of molecular markers. Conclusions We have found 18 individuals carrying mlo11 gene and Rph7 gene in homozygous combination in F2. Acquired lines of barley are fully resistant to powdery mildew and leaf rust. The next aim is to cross these lines with donors of resistance genes for other diseases and the selection of lines with cumulated resistance genes with the help of molecular markers. It is possible to say that marker assisted selection is valuable in common breeding. The use of this method for identification of resistance donors is a worthwhile tool. This work is supported by NAZV QH71213 References Dahleen L.S., Agrama H.A., Horsley R.D., Steffenson B.J., Schwarz P.B., Mesfin A., Franckowiak J.D.; Identification of QTLs associated with Fusarium head blight resistance in Zhedar 2 barley; Theor Appl Genet; 2003; 108; 95-104 Graner A., Streng S., Drescher A., Jin Y., Borovkova I., Steffenson B.J.; Molecular mapping of the leaf rust resistance gene Rph7 in barley; Plant breeding; 2000; 119; 389-392 Ivandic V., Walther U., Graner A.; Molecular mapping of a new gene in wild barley conferring complete resistance to leaf rust (Puccinia hordei Otth); Theor Appl Genet; 1998; 97; 1235-1239 Keb-Llanes M., González G., Chi-Manzareno B., Infante D.; A rapid and simple method for small-scale DNA extraction in Agavaceae and other tropical pplants.; Plant Molecular Biology Reporter; 2002; 3; 299a - 299e Mesfin A., Smith K.P., Dill-Macky R., Evans C.K., Waugh R., Gustus C.D., Muehlbauer G.J.; Quantitative trait loci for fusarium head bligh resistance in barley detected in a two-rowed by six-rowed population; Crop sci.; 2003; 43; 307-318 Piffanelli P., Ramsay L., Waugh R., Benabdelmouna A., D’Hont A., Hollricher K., Jørgensen J.H., Schulze-Lefert P., Panstruga R.; A barley cultivation-associated polymorphism conveys resistance to powdery mildew; Nature, 2004, 430, 887-891

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BARLEY YELLOW DWARF VIRUS ‡ BREEDING FOR TOLERANCE Ondrej Veskrna1, Pavel Horcicka1, Jana Chrpova2, Vaclav Sip2, Lucie Slamova3 1

SELTON, s.r.o., Stupice 24, 250 84 Sibrina, 2RICP Prague-Ruzyne, 3CUA Prague E-mail: [email protected]

Abstract Barley Yellow Dwarf Virus (BYDV) is transmitted by several species of aphids and causes one of the most important cereal virus disease which is spread worldwide on wheat, barley and other cereals. Management of disease is mainly achieved by the insecticide application. The most effective and sustainable control method is the use of genetic resistance/tolerance to the virus complex. BYDV was first recorded in Czech Republic by Vacke (1964). The three serotypes (PAV, RMV and RPV) were found with PAV dominance. Heavy attacks on barley and wheat by BYDV had been recorded in the Czech Republic in the years 1983-84, 1988-89, 1990-91 and 2002-03. Spring and winter wheat materials from Mexico (CIMMYT), Syria (ICARDA), Chile, Canada, USA, Australia, Hungary and Poland, together with advanced breeding lines and registered cultivars from Czech have been tested for resistance to BYDV. Genotypes with Bdv2 resistance gene from wheat/Thinopyrum translocation were also tested. Artificial infection field tests and semi-quantitative ELISA greenhouse tests results were compared. Resistance of genotypes with Bdv2 gene to Czech BYDV-PAV isolate was not confirmed. Key words: wheat, barley yellow dwarf virus, Bdv2 resistance gene Introduction Barley Yellow Dwarf Virus (BYDV) is transmitted by several species of aphids and causes probably the most important virus disease of cereals. The most effective and sustainable control method is the use of genetic resistance/tolerance to the virus complex. Several studies were done of wheat/Thinopyrum translocation by different authors. Their results advice this translocation lines as a source of BYDV resistance. Molecular markers were developed for identification Bdv2 and Bdv3 resistance genes. Objective of this study was to compare genotypes with and without wheat/Thinopyrum translocation by artificial BYDV-PAV infection field tests, semi-quantitative ELISA and DNA analysis. Materials and Methods Collection of spring wheat from CIMMYT together with Tc lines from Australia and two lines from USA (P29 and P961341) were tested in comparison with not translocated tolerant wheat lines from Brazil, Mexico, Syria and Czech Rep. Artificial infection field trials were performed in 2005, 2006 and 2008 seasons contained infected and uninfected (control) variants. The plants were grown on two-row plots 1-m long with two replications (plant spacing: 6x22 cm). Infection with PAV strain of BYDV was carried out at the beginning of the tillering stage. Bird cherry-oat aphids (Rophalosiphum padi) obtained from greenhouse rearing were used for virus transmission. The intensity of the symptomatic response (VSS – visual symptom score) was classified according to a 0-9 scale (0 = resistant) developed by Schaller and Qualset (1980), at the phase of full flowering. The effect of virus infection on yield components will be assessed after plant harvest. Semi-quantitative ELISA was done at 18 genotypes (11 with wheat/Thinopyrum translocation, 7 without). Four plants in three repetitions of each genotype were infected by BYDV-PAV. Infection was carried out at three leaves stage by Bird cherry-oat aphids (Rhopalosiphum padi) – approx. five aphids per one plant. Eleventh day after infection the youngest leaves were collected and semi-quantitative ELISA were done according to their weight. Absorbance at 405 nm was measured and relative amount of BYDV-PAV in plant tissue was estimated. Bdv2 gene detection was done with BYAgi, SCGp1 and Xgw markers (www.maswheat.com, 2005; Zhong et al., 2004) and Bdv3 gene with marker published on MASwheat server BDV3 (www.maswheat.com, 2005). 248



Table 1: Characterization of genotypes; Type (W = winter, S = spring), Visual symptom score (VSS, 0 = resistant, 9 = susceptible), ELISA (odi 405 nm) and presence of resistant allele determined by molecular marker (BYAgi, SC-gp1, Xgw and BDV3). GENOTYPE P29 WKL91-138 KIVU-85 QG 4.37 LEGUAN TOLERANT SG-S26-98 QG 2.1 SG-S604-96 ANZA P961341 QG 22.24 SG-S45-98 Tc14290E Tc14290J QG 100 JARA SUSCEPTIBLE CIM 0231 CIM 0234 CIM 0232 CIM 0235 CIM 0230 Z2 CIM 0236 CIM 0227 CIM 0233 Z6 CIM 0229 TC9 CIM 0223 CIM 0226 CIM 0228 CIM 0220 CIM 0225 CIM 0237 TC5 TC7 CIM 0221 CIM 0224 CIM 0222

type W S S S S S S S S W S S S S S S S S S S S S S S S S S S S S S S S S S S S S S

VSS 2,5 2,7 3,0 4,1 4,1 4,2 4,3 4,3 4,4 4,8 4,8 4,9 5,0 5,8 5,9 6,2 6,3 6,4 6,4 6,5 6,5 6,6 6,7 6,8 6,8 7,0 7,1 7,1 7,2 7,2 7,2 7,3 7,4 7,4 7,5 7,6 7,8 7,9 8,4

ELISA 0,4 1,3

1,3 1,7 1,9 0,8 0,4 1,5 1,1 0,8 1,0 0,5 0,7

0,7 0,3 0,8

0,3 0,5

249

BYAgi + + + + + + + + + + + + + + + + + + + + + +

SC-gp1 + + + + + + + + + + + + + + + + + + + + + + + +

Xgw + + + + + + + + + + + + + + + + + +

Bdv3 + + + + + + + + + + + + + + + + + +



Results and Discussion Artificial infection field tests showed high dependence of symptoms developing on date of infection and weather condition during vegetation. Medium tolerant variety Anza was scored in average 4,4 points in scale 0 = resistant, 9 = susceptible (Table 1). Better score were found at breeding lines WKL91-138 (Siria), KIVU-85, QG 4.37, QG 2.1 (All from Canada), SG-S26-98, SG-S604-96 (CZ – Selgen) and variety Leguan (CZ – Selgen). Breeding line P29 (USA) has the best symptom score (2,5), but it was counted from only two years results and it is together with line P961341 winter type. These lines were taken into these results because of their wheat/Thinopyrum translocation and presence of Bdv2 and Bdv3 genes. Intermediate reaction on infection was found on lines ranged between variety Anza (4,4) and susceptible control variety Jara (6,2); real susceptible lines are above Jara (Table 1). Symptom reaction on field artificial infection of lines with wheat/Thinopyrum translocation ranged from susceptible to very susceptible, except two winter wheat lines mentioned above. Semi-quantitative ELISA was done and absorbances average was counted for selected genotypes with and without wheat/Thinopyrum translocation. Measured values were very variable between repetitions and there was not possible to select individual genotypes according to low or high ELISA absorbance. Absorbance of group with wheat/Thinopyrum translocation was in average lower than in group without. This showed some effect of wheat/Thinopyrum translocation on relative virus quantity in plant tissue (Fig.1).

Fig.1: Absorbance average (11 days after infection, odi 405 nm) counted for genotypes with and without Bdv2 marker Presence of wheat/Thinopyrum translocation was tested by detection of three molecular markers. Full positive marker results (Bdv2 and Bdv3 genes) were found at 13 lines: P29 (USA), CIM 0220, CIM 0221, CIM 0222, CIM 0223, CIM 0224, CIM 0225, CIM 0226, CIM 0227, CIM 0228, CIM 0230, CIM 0231 and CIM 0233 (all from CIMMYT). There was not found clear correlation between presence of markers and field resistance. Our survey is not in accord with results from Ayala et al. 2001 and other authors. Wheat/Thinopyrum translocation effect was found positive for field resistance to BYDV by them. These results were achieved with BYDV-PAV isolates from Mexico or Australia. BYDV isolate used in this study BYDV-PAV (Czech) could be different and we have not knowledge about its conformity at this moment. Conclusions Lower virus titers were approved at Bdv2+ genotypes. There was not found correlation between field tolerance and presence of Bdv2 gene or low relative amount of virus. Difference between Czech and Australian or Mexican BYDV-PAV could be responsible for these results. DNA analysis of Czech BYDV-PAV is object of further studies. 250



Acknowledgements This work is supported by GACR (521/05/H013) and NAZV (QG 50073). References Ayala, L., Khairallah, M., van Ginkel, M., Keller, B., Henry, M. (2001): Expression of Thinopyrum intermedium-Derived Barley yellow dwarf virus Resistance in Elite Bread Wheat Backgrounds. Phytopatology, Vol. 91, No. 1, 2001 Comeau, A., St-Piere, C.A. (1982) : Trials on the resistance of cereals to barley yellow dwarf virus (BYDV). Report no. 4. Res. Stat. Agric. Canada, Sainte-Foy, Quebec, Canada: 132s. Henry, M., van Ginkel, M., Khairallah, M.(2001): Marker- Assisted Selection for BYDV Resistance in Wheat, Barley Yellow Dwarf Newsletter, D.F.: CIMMYT, Mexico. MAS-Wheat- Bringing Genomics to the wheat fields- Virus resistance. Barley Yellow Dwarf Virus (BYDV)- Bdv2 http://maswheat.ucdavis.edu/protocols/BYDV/BYDV- methods.htm, 2005. Shaller, C.W., Qualset, C.O. (1980): Breeding for resistance to barley yellow dwarf virus. In: Proc. Third int. Wheat Conf., Madrid, Spain University of Nebraska Agric. Experiment. Station, public. MP 41: 528-541. Stoutjesdijk, P.; Kammholz, S. J.; Kleven, S.; Matsay, S.; Banks, P. M.; Larkin, P. J. (2001): PCR-based molecular marker for the Bdv2 Thinopyrum intermedium source of barley yellow dwarf virus resistance in wheat. Australian Journal of Agricultural Research, 2001. 52(11-12):1383-1388. Vacke, J. (1964): @lutá zakrslost je~mene v ^SSR, Rostl. výr., 10: 859-868. Zhang, Z., Xu, J., Xu, Q., Larkin, P., Xin, Z.(2004) : Development of novel PCR markers linked to the BYDV resistance gene Bdv2 useful in wheat for marker-assisted selection, Theor. Appl. Genet 109:134-14.

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Yield components in wheat exposed to high concentrations of soil boron Milka Brdar1*, Ivana Maksimovi}1,2, Borislav Kobiljski1, Marija Kraljevi}-Balali}2 1

Institute of Field and Vegetable Crops, Small Grains Department, Maksima Gorkog 30, 21000 Novi Sad, Serbia 2 University of Novi Sad, Faculty of Agriculture, Department of Field and Vegetable Crops, Trg Dositeja Obradovi}a 8, 21000 Novi Sad, Serbia * Scholarship holder of Ministry of Science of Republic of Serbia E-mail: [email protected]

Abstract Boron is an essential plant micronutrient; however, high concentrations of soil boron may interrupt wheat growth and development and cause substantial yield losses. The considerable genetic variation that has been found among wheat genotypes in response to high boron concentrations makes it possible to breed tolerant cultivars. The present study was undertaken in order to examine the response of a group of wheat cultivars to excess boron in terms of yield components (grain weight, number of grains per spike, number of spikes per m2) and yield. Ten wheat cultivars of local origin were included in a two-year field trial that was conducted at the Rimski [an~evi Experimental Field of the Institute of Field and Vegetable Crops in Novi Sad. The cultivars were chosen on the basis of boron tolerance estimated in laboratory conditions. The trial included a control and three boron treatments (3.3, 6.7 and 13.3 g H3BO3/m2). Significant differences in response to excess boron occurred among the cultivars. Yields in the treatments differed by -11.7% to 4.6% from those in the control (100%), and they correlated well with number of spikes per m2. Number of grains per spike was affected the most by high boron concentrations, with an average reduction of 8.2%. Out of the ten analyzed cultivars, six were more boron tolerant in the field compared to laboratory conditions. Key words: boron tolerance, field conditions, wheat Introduction When present in excessive amounts, micronutrient boron (B) may cause substantial yield losses in wheat. Boron toxicity was for the first time recognized as problem in Australian field-grown barley; where a yield reduction of up to 17% appeared to be a consequence of high soil boron concentrations (Cartwright et al., 1984). Boron laden soils occur in many regions of the world, with South Australia, Turkey, Mexico, Iraq and Syria being probably among the most affected. The former Yugoslavia and Hungary were also mentioned as regions characterized by high soil boron (Miljkovi}, 1960; Nable et al., 1997). In a study that included 1,600 agricultural soil samples probed in the Vojvodina Province, the maximum boron concentration was found to be 15.9 ppm (Ubavi} et al., 1993), which is far above the recommended maximum for wheat. Soil boron concentrations of only a few ppm can cause boron toxicity in wheat plants (Yau and Saxena, 1997). Furthermore, saline soils and semi-arid growing conditions, which are common in Vojvodina, aggravate the negative impact of the element on agricultural plants, especially wheat (Miljkovi}, 1960; Wimmer et al., 2003). Great variability in boron susceptibility that has been found among wheat genotypes makes possible the breeding of tolerant cultivars. It is the best approach for solving the problem, because soil amelioration is difficult, expensive and a short-term solution (Nable et al., 1997; Torun et al., 2006). However, it is extremely difficult to predict wheat growth and yield on boron laden soils. Discrepancies between the results obtained in field and laboratory conditions, the significant genotype x environment interaction in terms of yield components and yield that occurs in field conditions regardless of soil boron concentration (Kalayci et al., 1998; Brennan and Adcock, 2004), the high possibility for experimental error in small-plot trials due to uneven vertical and horizontal distribution of the element in the soil (Avci and Akar, 2005), and the fact that the boron tolerance mechanism still remains to be clarified (Roessner et al., 2006) are some of the reasons that make predicting wheat growth and yield on boron laden soils extremely difficult. 252



The main aim of the study was to investigate the response to excess boron in terms of yield components and yield in a group of wheat cultivars of local origin in field conditions. The second aim was to compare field boron tolerance with boron tolerance estimated previously in laboratory conditions. Materials and Methods Ten wheat cultivars of local origin were included in a two-year (2005/06, 2006/07) field trial that was conducted at the Rimski [an~evi Experimental Field of the Institute of Field and Vegetable Crops in Novi Sad (45o 20’ N, 19o 51’ E, 84 m above sea level). The cultivars were chosen on the basis of boron tolerance estimated previously in a laboratory assay conducted using the filter-paper method suggested by Chantachume et al. (1995). The cultivars Nevesinjka, Rapsodija, Milijana and Helena were classified as boron tolerant, whereas Pesma, Balerina, Sofija, Kantata, Simonida and Ko{uta were sensitive to excess boron (Brdar et al., 2008). The field trial was conducted in randomized blocks with a control and three boron treatments (3.3, 6.7 and 13.3 g H3BO3/m2) in three replications. The dimension of the main plot was 1.2 m2. Standard agrotechnical procedures were applied. Treatments were imposed immediately after sowing in the form of boric acid solutions. The selection criterion for boron tolerance was the average yield reduction (YR – %) in a treatment relative to control (control=100%). Genotypes with YR below 5% were considered boron tolerant, those at 5 – 10% medium tolerant, and those above 10% boron sensitive. The average reductions/increases in treatments relative to control were calculated for the yield components as well (grain weight – GW, number of grains per spike – NG and number of spikes per m2 – NS) All calculations (ANOVA, correlation coefficients, mean values and standard errors of mean) were performed using the STATISTICA 8.0 software package. Results and Discussion Analysis of variance demonstrated significant differences among the studied wheat cultivars in yield components and yield in conditions of normal boron supply (Table 1.). On a two-year average, the highest yield was recorded for the cultivar Milijana (1.220 kg/m2) and the lowest for Sofija (0.977 kg/m2). The heaviest grains were measured in Simonida and the lightest in Kantata. Number of grains per spike varied between 56.4 (Nevesinjka) and 40.1 (Sofija), whereas number of spikes per m2 ranged from 693 (Helena) to 518 (Simonida). Table 1. Yield (Y) and yield components (GW ‡ grain weight, NG ‡ number of grains per spike and NS ‡ number of spikes per m2) in ten wheat cultivars grown in conditions of normal B supply (control) Cultivar Y (kg/m2) Rapsodija 1.133 Simonida 1.141 Kantata 1.043 Pesma 1.067 Balerina 1.026 Sofija 0.977 Nevesinjka 1.156 Ko{uta 1.122 Milijana 1.220 Helena 1.182 mean 1.107 SE of mean 0.015 F – values from ANOVA 3.29**

GW (g) 44.3 48.0 37.6 38.6 42.4 38.5 39.6 44.1 41.0 44.0 41.8 0.6

NG 50.8 48.4 53.3 54.0 45.6 40.1 56.4 52.5 47.1 40.2 48.9 0.9

NS 548 518 523 536 536 654 542 524 612 693 568 11.2

4.55*

8.85**

4.76**

** – significant at the 0.01 level of probability

253



Significant differences that were found among the cultivars in yield reduction by boron treatments relative to control made possible their classification on the basis of boron tolerance level (Table 2.). Yield variation in the treatments ranged from -11.7 (boron sensitive Helena) to 4.6% (tolerant Rapsodija) compared to the control (100%). Yield reductions that were observed in the most sensitive cultivars were in a similar range as those reported by Campbell et al. (1993). There was no significant relationship between yield in the control and yield in the boron treatments (r=-0.29). Therefore, yield reduction in boron treatments compared with the control can be used as a selection criterion for boron tolerance in field conditions. Number of grains per spike was the component most affected by high boron concentrations, with an average reduction of -8.2% (Table 2). This is in disagreement with the reported highest reduction of number of spikes per m2 in boron treatments in a greenhouse trial (Yau and Saxena 1997). The disagreement is probably a result of the different experimental conditions. Table 2. Average yield (YR), grain weight (GWR), number of grains per spike (NGR) and number of spikes per m2 (NSR) reductions (‡) / increases (+) in boron treatments (%) relative to control (control=0%) for 5 boron tolerant (T), 3 medium tolerant (MT) and 2 sensitive (S) wheat cultivars Cultivar B tolerance YR GWR NGR Rapsodija T 4.6 -2.1 -6.1 Simonida T 1.6 -4.1 -10.2 Kantata T 1.0 0.1 -15.2 Pesma T -2.0 1.4 -11.2 Balerina T -3.9 2.9 -13.9 mean 0.2 -0.4 -11.3 SE of mean 1.2 1.1 1.3 F – values from ANOVA (within group of B tolerant cultivars) 1.96 ns 1.75 ns 1.71 ns Sofija MT -5.1 4.7 0.6 Nevesinjka MT -7.1 -1.7 -7.3 Ko{uta MT -7.5 -5.0 -11.3 mean -6.6 -0.7 -6.0 SE of mean 0.9 1.7 2.3 F – values from ANOVA (within group of B medium tolerant cultivars) 0.73 ns 3.76* 3.25 ns Milijana S -11.4 1.9 -4.5 Helena S -11.7 -5.8 -2.5 mean -11.5 -1.9 -3.5 SE of mean 1.1 2.0 3.5 F – values from ANOVA (within group of B sensitive cultivars) 0.00 ns 5.07* 0.08 ns mean -4.2 -0.8 -8.2 SE of mean 0.9 0.8 1.3 F – values from ANOVA (among groups) 24.87** 0.36 ns 4.47*

NSR 2.7 9.8 13.7 3.6 7.6 7.5 1.7 2.32 ns -9.3 -0.8 0.6 -3.2 1.7 4.00* -5.7 -10.6 -8.1 3.5 0.16 ns 1.2 1.5 16.15**

ns, *, ** – insignificant, significant at the 0.05 and 0.01 levels of probability, respectively

Yields in the treatments correlated well with number of spikes per m2 (r=0.73*). Number of spikes per m2 and number of grains per spike in the treatments were negatively correlated (r=-0.90**), and this was the most apparent in the group of boron tolerant genotypes (Table 2.). Therefore, the highest reduction in number of grains per spike that was found in the group of tol254



erant genotypes in comparison with the other groups (-11.3%) might represent a consequence of the significant increase in number of spikes per m2 in the boron treatments compared to the control (7.5%). Out of ten cultivars, six were more tolerant in field comparing to laboratory conditions. Two cultivars that had been classified as tolerant in the laboratory assay (Milijana and Helena) were sensitive in field conditions. Differences between boron tolerance in field and laboratory conditions have been also reported by Kalayci et al. (1998). Considering the vast interval of variation between the minimum (0 ppm) and maximum (15.9 ppm) boron concentrations that has been found in agricultural soils of Vojvodina (Ubavi} et al. 1993), boron deficiency may also be a problem in addition to boron toxicity. Cultivars that had higher yields in the boron treatments than in the control, such as Rapsodija (Table 2.), may be boron inefficient. Therefore, the best starting material for breeding should be cultivars having yields that are as stable as possible across a wide range of soil boron concentrations, such as Simonida, Kantata and Pesma. Conclusions Significant differences in response to excess boron in field conditions occurred among the studied wheat cultivars. Yield in the treatments ranged from -11.7 to 4.6% relative to the control (100%) and it correlated with number of spikes per m2. Because boron deficiency as well as toxicity may occur in Vojvodina, the best starting material for breeding should be cultivars with yields that are stable across a wide range of soil boron concentrations. References Avci M., Akar T. (2005): Severity and spatial distribution of boron toxicity in barley cultivated areas of Central Anatolia and Transitional zones. Turkish Journal of Agriculture & Forestry, 29, 377-382. Brdar M., Maksimovi} I., Kraljevi} – Balali} M., Kobiljski B. (2008): Boron tolerance in twelve NS wheat cultivars. Acta Agriculturae Serbica, Vol. 13, No. 25, 17-23. Brennan R. F., Adcock K. G. (2004): Incidence of boron toxicity in spring barley in Southwestern Australia. Journal of Plant Nutrition, 27, 411-425. Campbell T. A., Moody D. B., Jefferies S. P., Cartwright B., Rathjen A. J. (1993): Grain yield evaluation of near isogenic lines for boron tolerance. Proceedings of the 8th International Wheat Genetics Symposium Vol. 2, Beijing, China, 20 – 25 July 1993, 1021-1027. Cartwright B., Zarcinas B. A., Mayfield A. H. (1984): Toxic concentrations of boron in a red – brown earth at Gladstone, South Australia. Australian Journal of Soil Research, 22, 261-272. Chantachume Y., Smith D., Hollamby G. J., Paull J. G., Rathjen A. J. (1995): Screening for boron tolerance in wheat (T. aestivum) by solution culture in filter paper. Plant and Soil, 177, 249-254. Kalayci M., Alkan A., Çakmak I., Bayramo-lu O., Yilmaz A., Aydin M., Ozbek V., Ekiz H. (1998): Studies on differential response of wheat cultivars to boron toxicity. Euphytica, 100, 123-129. Miljkovi} N. (1960): Karakteristike vojvo|anskih slatina i problem bora u njima. Doktorska disertacija, Univerzitet u Novom Sadu, Poljoprivredni fakultet. Nable R. O., BaZuelos G. S., Paull J. G. (1997): Boron toxicity. Plant and Soil, 193, 181-198. Roessner U., Patterson J. H., Forbes M. G., Fincher G. B., Langridge P., Bacic A. (2006): An investigation of boron toxicity in barley using metabolomics. Plant Physiology, 142, 1087-1101. Torun A., Yazici A., Erdem H., Çakmak I. (2006): Genotypic variation in tolerance to boron toxicity in 70 durum wheat genotypes. Turkish Journal of Agriculture & Forestry, 30, 49-58. Ubavi} M., Bogdanovi} D., Dozet D., Hadì} V., ]irovi} M., Sekuli} P. (1993): Sadràj te{kih metala u zemlji{tima Vojvodine. Zbornik radova Instituta za ratarstvo i povrtarstvo, 21, 49-58. Wimmer M. A., Mühling K. H., Läuchli A., Brown P. H., Goldbach H. E. (2003): The interaction between salinity and boron toxicity affects the subcellular distribution of ions and proteins in wheat leaves. Plant Cell and Environment, 26, 1267-1274. Yau S. K., Saxena M. C. (1997): Variation in growth, development, and yield of durum wheat in response to high soil boron. I. Average effects. Australian Journal of Agricultural Research, 48, 945-949.

255



EFFECTS OF FHB TOLERANT WINTER WHEAT VARIETIES (PETRUS, SAKURA, SIMILA) ON YIELD AND QUALITY PARAMETERS UNDER HIGH PATHOGEN PRESSURE K. Rehorova1, O. Veskrna1, P. Horcicka2, T. Sedlacek2 1

2

Selgen a.s., Stupice 24, 25084 Sibrina, Czech Republic, Research Center SELTON s r.o., Stupice 24, 25084 Sibrina, Czech Republic Email: [email protected]

Abstract Winter wheat is the most important crop in the Czech Republic; it is grown in one half of the area of cereals. Fusarium head blight (FHB) causes severe yield losses and decreases baking and food quality. Most of registered winter wheat varieties are middle or high susceptible to FHB. Many results show that it is difficult to reach high resistance level and simultaneously high yield and necessary food quality. Six winter wheat varieties were used in three years 2005-2007 and differed into 2 groups: a) tolerant group (with medium resistant varieties – Sakura, Simila, Petrus), b) susceptible group (Darwin, Mladka, Sulamit). Symptomatic evaluation, yield reduction and deoxynivalenol (DON) accumulation is discussed both from the view of susceptible and medium resistant varieties and by application of different fungicide treatment. Tolerant varieties have with strong infectious pressure significantly (P < 0.05) lower occurrence of pathogen and less DON contain then susceptible varieties. Targeted fungicidal treatment significantly (P < 0.05) influenced mycotoxin accumulation and yield especially in susceptible varieties. These results clearly advert to importance of developing resistant varieties. Key words: Fusarium head blight, deoxynivalenol, fungicide, yield, quality Indtroduction Food safety is nowadays the priority for cereal producers and grain-processing industry. Fusarium head blight causes severe yield losses and decreases baking and food quality (Mesterházy, 2003). The most frequent species in Europe are now F. graminearum and F. culmorum (Logrieco et Bottalico, 2001; Mesterházy, 2003), both of which produce mycotoxins (Joffé 1986, Abramson 1998, Chelkowski 1998). The basic toxins are deoxynivalenol (DON), zearalenone and nivalenol (Logrieco et al., 2003). Most of registered winter wheat varieties are middle or high susceptible to FHB. The results of many researches show us that it is difficult to reach high resistance level and simultaneously high yield and necessary food quality (Mesterházy, 2003). The object of this work is to assess Fusarium Head Blight (FHB) impact on winter wheat symptomatic evaluation, yield reduction and deoxynivalenol (DON) accumulation. These parameters are discussed both from the view of susceptible and medium resistant varieties and by application of different fungicide treatment. Materials and methods The small-parcel experiment was based in the breeding station Stupice in years 2005-2007 and Uhretice in 2007. The experiment used complete randomized blocks in 3 replications; each parcel area was 10m2. Six winter wheat varieties was used and differed into 2 groups: a) susceptible varieties (Darwin, Mladka, Sulamit), b) medium resistant varieties (Sakura, Simila, Petrus). Part of the project was 4 various fungicide treatments: 1) control – without artificial infection and fungicidal treatment, 2) infection – with artificial infection of F. graminearum and F. culmorum, without fungicidal treatment, 3) fungicide - in growing stage DC 37 – 39 spraying with Tango Super (1l/ha, active substances epoxiconazole 84g/ha and fenpropimorph 250g/ha), artificial infection in the flowering period. Tango Super is commonly used preparation without the target of Fusarium suppression. 4) targeted treatment - in DC 37-39 Tango Super, 24 hours before Fusarium infection was used targeted fungicide Caramba (1l/ha, active substance metconazole 60g/ha). Caramba was the most applied fungicide against Fusarium. 256



Inoculum with spore concentrations of 6-7 x 106 spores/ml was prepared and each parcel was infected with 1 liter of inoculum. Infections run up in full flowering period according to each variety term. Symptomatic evaluation was carried in 21st day after the infection. The experiment was harvested by plot harvester. The grain was analyzed; mycotoxin was determined immunochemically using ELISA. Results and discussion Symptomatic evaluation - Head blight symptoms were evaluated on a 1-9 scale (9 - without symptoms, 1 - 100% disease development) (Table 1). The difference between infection and non-targeted fungicide is not significant, while targeted fungicide lead to significantly (P < 0.05) less presence of symptoms. Medium resistant varieties have with strong infectious pressure significantly (P < 0.05) lower occurrence of pathogen then susceptible varieties. The best symptom score of infection variant was evaluated at variety Sakura (7,5). Table 1: Head blight symptoms on a 1-9 scale (9 - without symptoms, 1 - 100% disease development), varieties comparison SYMPTOMATIC

susceptible varieties

medium resistant var.

EVALUATION

MLADKA DARWIN SULAMIT

SIMILA

PETRUS

SAKURA

CONTROL q

8,09

a

8,55

ab

8,50

ab

8,93

b

8,91

b

8,73

b

TARGETED T. q 5,45

a

5,73

a

6,27

ab

7,21

bc

7,86

c

8,14

c

FUNGICIDE q

4,36

a

4,77

ab

5,36

b

7,14

c

7,45

c

7,77

c

INFECTION q

4,00

a

4,14

a

5,18

b

6,79

c

7,41

c

7,50

c

Yield reduction – The difference between infection and non-targeted fungicide is not significant. Targeted treatment was significantly (P < 0.05) effective in susceptible varieties and increased their yield about 13 % compared to infection variant. In medium resistant varieties there is not significant difference between targeted, non-targeted treatment and infection variant; but their yield (compared to susceptible varieties) was about 5 % higher (P < 0.05) with targeted treatment, about 11 % in fungicide variant and about 15 % in infection variant (Fig 1). Yield reduction in the susceptible varieties was 17 % in the targeted treatment, 26 % in the fungicide variant and 30 % in the infection variant. Yield reduction in medium resistant varieties was 14 % on the average irrespective of the treatment (Table 2). Petrus and Sakura have significantly (P < 0.05) higher yield than susceptible varieties, however Simila was somewhere between these two groups (Fig 2). Table 2: Yield reduction (%, t/ha), treatment and genotypes comparison CONTROL Ø TARGETED T. Ø FUNGICIDE Ø INFECTION Ø %

t/ha

SUSCEPTIBLE V.

100

9.43

M. RESISTANT V.

100

9.77

MEAN

100

9.59

%

t/ha

a

83

7.81

a

88

8.57

85

8.17

%

t/ha

b

74

6.93

b

85

8.31

79

7.57

%

t/ha

c

70

6.64

c

b

85

8.30

b

77

7.42

DON content – Medium resistant varieties contain about 3/4 less (P < 0.05) DON than susceptible ones (Table 3). Targeted fungicide treatment takes positive effect both in tolerant and susceptible varieties and reduces the DON content about 2/3. Sakura and Simila have the lowest DON content, Petrus ranges between Sakura and Simila and susceptible varieties (Fig. 3).

257



Fig. 1: The yield difference between susceptible and medium resistant varieties in infection variant.

Fig. 2: Yields after artificial infection (without fungicide treatment) Table 3: DON contend (%, ppm), treatment and genotypes comparison INFECTION Ø FUNGICIDE Ø TARGETED T. Ø CONTROL Ø % ppm % ppm % ppm % ppm SUSCEPTIBLE V. 100 13.4 a 70 9.35 a 25 3.34 b 4 0.48 b M. RESISTANT V. 100 2.35 a 103 2.42 a 29 0.69 b 0 0.00 b MEAN 100 8.03 75 5.98 26 2.05 3 0.24

Fig 3: DON content after artificial infection (without fungicide treatment) Conclusions Development of tolerant varieties is the most effective protection against FHB infection and mycotoxin accumulation. Targeted fungicidal treatment highly influences mycotoxin accumulation and yield in susceptible varieties. However the application date in this work was accurately determined (24 hours before infection), estimation of the application time is doubtful in practice. Non-targeted fungicidal treatment is not explicit. Varieties Petrus, Simila and Sakura approve medium tolerance to FHB, Sakura was found the best in all parameters. Acknowledgements This work was supported by NAZV QG50076 and GA^R 521/05/H013. 258



References Abramson, D. 1998. Mycotoxin formatd environmental factors. In Sinha K.K., Bhatnagar D. (eds), Mycotoxins in Agriculture and Food Safety. Marcel Dekker, New York, pp. 255-277 Chelkowski, J. 1998. Distribution of Fusarium species and their mycotoxins in cereal grains. In: In Sinha K.K., Bhatnagar D. (eds), Mycotoxins in Agriculture and Food Safety. Marcel Dekker, New York, pp. 45-64 Joffé, A.Z. 1986. Fusarium Species: Their Biology and Toxicology. John Wiley and Sons, New York. Logrieco, A., Bottalico, A. 2001. Distribution of toxigenic Fusarium species and mycotoxin associated with head blight of wheat in Europe. In: Proceedings of International Conference: Sustainable systems of cereal crop protection against fungal diseases as the way of reduction of toxin occurence in the food webs. 02.-06.07. 2001, Kromeriz, pp. 83-89 Logrieco, A., Bottalico, A., Mul, G., Moretti, A., Perrone, G. 2003. Epidemiology of toxigenic fungi and their associated mycotoxins for some Mediterranean crops. European Journal of Plant Pathology 109:645-667 Mesterházy, A. 2003. Breeding wheat for Fusarium head blight resistance in Europe. In: Leonard, K.J., Bushnell, W.R. (eds), Fusarium Head Blight of Wheat and Barley. The American Phytopathological Society, St. Paul, MN, USA, 312 pp.

259



POSSIBILITIE STRATEGY FOR DURABLE RESISTANCE TO Puccinia recondita tritici OF WHEAT Mom~ilo Bo{kovi}1, Jelena Bo{kovi}2 1

2

Faculty of agriculture, Novi Sad Megatrend university Belgrade, Faculty of biofarming , Ba~ka Topola, Serbia E-mail: [email protected]

Abstract The new approach in international pathogenicity survey of Puccinia recondita tritici was to provide genetically diverse sources of resistance to be used in a survey of wheat leaf rust pathogen in European-Mediterranean regions and to search for pathogenicity of P. recondita tritici cultures useful in differentiating sources of resistance. New methods have been applied containing Central Field Nursery, Central Seedling Tests, Cooperative Seedling Tests and Regional Field Nurseries (ELRWN). The results have been reported from one year of investigations. ELRWN contained 20 winter wheat hybrid lines with pyramiding resistant genes including strong ones Lr9, Lr19 and Lr24. Also, 16 spring wheat lines were included, as control lines. In that year ELRWN have been realized in 13 countries and cooperative seedling test in 8 countries using 22 pathotypes of P. recondita tritici. The best results obtained by the winter wheat lines NS-66/5´Lr24, NS-77/2´Lr19, NS-37/2´Lr19 and spring wheat lines 647-CMA-14793 and 26TH-ESWYT-10. Key words: Puccinia recondita tritici, International survey, hybrid lines, resistant hybrid wheat lines. Introduction Leaf or brown rust caused by Puccinia recondita Roberge ex Desmaz. f. sp. tritici (Eriks. & E. Henn.) is probably the most important disease on the worldwide basis and yield losses may reach 40% in susceptible cultivars (Kolmer, 1996). Strategy for durability of leaf rust resistance in cultivars after the are released in agriculture is perhaps more important than achieving resistance in the first instance. The objective of cultivar management, regardless of epidemic probability, is to maximize the potential durability of deployed resistance. The global leaf rust population varies in virulence and this variation may result from one or more factors. The essential orientation for the international studies of the rust pathogens where their long distance dissemination as well established phenomenon. Wind is a great uncontrolled carrier of inoculum and urediospores of rust fungi are recognized as international travelers (Roelfs, 1985; Bo{kovi} and Bo{kovi} Jelena, 2007). This was the mean reason why the best method of rust pathogen control was a network of international cooperative studies which would cover large epidemiological areas (Bo{kovi} Jelena et. al., 2001; Mesterházy et al, 2000). The importance and necessity of cooperative international investigations of the wheat rusts was especially emphasized by the European and Mediterranean Cereal Rusts Foundation. That was included first time in resolutions of Cereal Rust Conferences in Cambrige, 1964 and later on the others.Cooperative research of yellow rust of wheat for Europe had been organized in Netherlands, for stem rust in Portugal and Italy, and for leaf rust in Yugoslavia. The European Project of Wheat Leaf Rust Research had been started in Novi Sad dealing primarily with pathogenicity surveys of Puccinia recondita tritici in European-Mediterranean regions and breeding for resistance (Bo{kovi}, 1966). From that time in International surveys for European-Mediterranean regions different sets of Lr lines have been used (Bo{kovi} Jelena et. al., 2001). The same Lr lines used hadn’t any value for European-Mediterranean regions. It was clear, even years ago, that these regions needed new more efficient resistance genes and large testing and crossing program started in that time. The most of these lines had not shown satisfactory efficiency for the surveys. A comparison of pathogenicity of Puccinia recondita in Europe, The United States and Canada has shown big differences (Bo{kovi} and Browder, 1976). At the beginning 18 donors of resistance had been selected after an extensive screening tests of several International rusts nurseries, 260



for crossing with varieties Princ and Starke. Later on, eight of these hybrid lines with the most interesting donor, 66, 77, 26, 32, 46, 94 and 146, have been crossed with only effective genes Lr9, Lr19 and Lr24 (Bo{kovi} Jelena et al., 2008). The main objective within new approach in international patogenicity survey of Puccinia recondita tritici was to provide genetically diverse sources of resistance (wheat lines with pyramiding resistant genes) to be used in a survey of wheat leaf rust pathogen in European-Mediterranean regions and to search for and document pathogenicity of P. recondita tritici cultures useful in differentiating sources of resistance. Emphasis is placed on sources of resistance and their usefulness rather than on description of fungus populations. Materials and Methods The methods are applied according to the following approaches and procedure: Central Field Nursery Each year in this field nursery numerous field materials from International rust nurseries as well as numerous breeding wheat lines from our program have been tested in the condition of artificial inoculations. Central Seeding Test P. recondita tritici collections from regional nurseries (ELRWN) have been sent to Novi Sad where has been cultured and there virulence to the source lines confirmed. When virulence to a given line is found and confirmed by greenhouse tests, that line should be removed from the field nursery and replaced by another line with potential value. This procedure is based on the concept of maximizing the number of sources of resistance to be studied. It is assumed that once virulent cultures are available, these cultures can be used to separate that line from other sources of resistance. Analysis of infection-type data has been done to distinguish between sources of resistance and to evaluate the usefulness of different sources of resistance in various places of the European-Mediterranean regions. Cooperative Seeding Tests Uniform sets in European Leaf Rust Wheat Nursery (ELRWN) and possibly some other potentially useful sources of resistance, should be inoculated with several prevalent cultures by 6-8 cooperators in several countries well-disposed on European-Mediterranean territory. Regional Field Nurseries (ELRWN) This approach should involvee testing of a uniform set of wheat lines to naturally occuring P. recondita tritici populations at 20-30 sites in Europe and Mediterranean regions. The materials included should emphasize only wheat lines previously tested and shown to be highly resistant, and for which there is indication of diverse resistance genotype. Observations of leaf rust severity should be made by cooperators and sent to Novi Sad for assembling and summarization. The materials in these nurseries will also provide a basis for collecting uredial cultures which are virulent to some or all of the wheat lines. These cultures are used in further greenhouse and laboratory studies for differentation sources of resistance. The seedlings in the greenhouse where scored for infection type according to a scale 0-9 and variations were classified for easier computerization. Reaction classes (R, I and S) comprized the following variation of inffections types »R« - 1, 2, 3, 4, (0, 0; 1, 2) »I« – 5, 6, (X-, X+) and »S« - 7, 8, and 9 (3-, 3+, 4). Since the segregation was very frequent in the seedlings and in the field, that was designated by »,« For leaf rust and ather rusts the reactions are recorded by severity (0-99) and response (VR-S). In the field are recorded desease severity, the parentage of the surface of the plant tillers and leavs affected, using the modified Cobb scale (Peterson et al, 1984). Host response, the type of infections observed (R - resistant, I - all intermediate types and S – susceptible). Severity is reduced to a single digit as follows: 0=0; 10=1; 11-25=2; 26-35=3; 36-45=4; 46-55=5; 56-65=6; 66-75=7; 76-85=8; 86-100=9. Host response is changed from R, I and S to 0-9 scale to computerization and deriving coefficient of infection. R= 0-3 or 2; I=4-6 or 5; S=7-9 or 8. As a material have been used our hybrid lines with pyramiding resistant genes and other highly resistant wheat genotypes in ELRWN selected according to above explained procedures. In Central Field Nursery are included complete International Rust Nurseries and numerous of our breeding lines. 261



Results and Discussion In Central Field Nursery have been tested in the field eight International Rust Nurseries with total of 410 entries and seven spring wheat – CIMMYT Nurseries with 708 entries. In addition to Central Nursery have been tested hybrid progenies from the breeding program of accumulation, or pyramiding resistant genes. In breeding material were included 834 hybrid lines. Some selected of all these material have been tested in the greenhouse (seedling stage) to twenty-two international cultures of P. recondita tritici from Regional Field Nurseries (ELRWN). Cooperative Seedling Tests in the second year included selected 36 winter and spring wheat entries in ELRWN. Seedling tests to particular pathotypes of P. recondita tritici have been realized in the following countries: Germany (one pathotype), Czechoslovakia (two pathotypes), Sweden (one path.), China (three path.), France (four path.), Italy (two path.), Bulgaria (four path.) and Israel (five path.) – in total 22 pathotypes. A Regional Field Nursery (ELRWN) comprised in second year twenty of winter wheat hybrid lines with pyramiding resistant genes from our breeding program and sixteen highly resistant spring wheat lines, again selected from tested and analyzed International Wheat Rust Nurseries. Field ELRWN nurseries with 36 entries have been realized in 13 countries and evaluated to P. recondita tritici and some other wheat pathogens: Germany (3 sites), Austria, Holland, Bulgaria, Israel, Sweden, Switzerland, Italy, Poland, Czechoslovakia, Spain, France and Chile. All winter wheat hybrid lines with accumulation of resistant genes containing strong resistant genes Lr9, Lr 19 and Lr24 have shown very good results. But, there is a very slight difference between them in degree of resistance. The best were the lines NS-66/5´Lr24, NS-77/2´Lr19, NS-37/2´Lr19, then NS-66/2´Lr19, NS-77/3´Lr24, NS-66/4´Lr19, NS-26/2´Lr19, and NS-26/1´Lr9, NS-32/2´Lr19, NS-94/4´Lr19. These hybrid lines have had a little better combining ability from the genes of the donors and strong resistant genes Lr9, Lr19 and Lr24, which resulted, with some higher degree of resistance. Within spring wheat lines in ELRWN, the best results obtained were the lines 647-CMA-14793 and 26TH-ESWYT-10. Less resistance have had 26TH-ESWYT-36, 11TH-ESWYT-20 and 26TH-ESWYT-3. For these spring lines it can be supposed that they contain several resistant genes. Other spring lines have had insufficient resistance or quite susceptible reactions. The most typical were the lines Lr9, Lr19 and Lr24 which had been used in our breeding program for accumulation of resistant genes. It is clear that these lines loosed almost complete resistance as Lr9 and Lr24, but much less Lr19. It is important to compare these results of twenty wheat lines containing accumulated resistant genes with the same lines where have been reported the segregation ratios of F2 generations (Bo{kovi} Jelena et al, 2001; 2008). The number of resistant genes of these twenty lines in the table is very good correlated with results obtained in the seedlings and adult plants in ELRWN nurseries in Table 1. That means, correlation of degree of resistance of cooperative seedling tests to particularly pathotypes of P. recondita tritici, as well as to degree of resistance in the field of the ELRWN in corresponding countries to the number of resistant genes in F2 generations of each breeding combination. Recently has been reported that pathogenicity studies of European populations of Puccinia recondita tritici using pathogenicity and molecular markers resulted in 35 pathotypes identified from 68 isolates examined, all of which were avirulent for the genes Lr9, Lr19 and Lr24, as well as to the other Lr’s Lr21, Lr25 an Lr29 (Park et al, 1996; Lukasz et al., 2003; Hysing, 2007; Pathan and Park, 2006). Conclusions It is well known in the last time that combining or pyramiding of resistance genes into individual cultivars has had considerable success in reducing the rate of evolution of pathogens particularly in the situations where the pathogen does not reproduce sexually, as in the case of P. recondita tritici. Considerable arguments for durability of cultivars with pyramided race-specific resistance genes have been already reported Samedifferences in F2 generation concerning the number of resistance genes related to particular pathotypes of P. recondita tritici was already reported by other authors stating that differences can depend from different donors and pathotypes used. 262



In the time when we used the lines with strong genes Lr9, Lr19 and Lr24 in our breeding program that lines have had very high resistance on the large epidemiological territory, meanwhile, these lines loosed almost complete resistance, as Lr9 and Lr24 and much less Lr19. Acknowledgements The authors are grateful for financial support by ineternational and national projects and cooperators in projects. References Bo{kovi} Jelena, Bo{kovi}, M., Babovi}, M., Jerkovi}, Z., Pe{i}, V. (2001): Pramiding strategy for durable resistance to wheat leaf rust pathogen. Wheat in a Global Environment. Developments in Plant breeding, Volume 9, Eds. Z. Bedo and L. Lang. Kluwer A Academic Publishers, p.804. Hardcaver, May 31, 2001, I edition ISBN: 0792367227; p. 337-343. Bo{kovi} Jelena, Bo{kovi} M., Priji} @eljana (2008): Pyramiding major genes for resistance to leaf rust pathogen of wheat. Proc. Of the International Scientific Conference on Multifunctional agriculture. University of Szeged, Faculty of agriculture, Hungary. p. 24. Bo{kovi}, M. M. (1966): The European Project of Wheat Leaf Rust Research. Contemporary Agriculture, Vol. 14, No. 11-12, p. 607-611. Bo{kovi}, M, Browder, L. E. (1976): A comparison of pathogenicity of Puccinia recondita f. sp. tritici in Europe, the United States and Canada, Plant Dis. Report 60: 278-280. Bo{kovi} M., Bo{kovi} Jelena (2007): Sistem nomenklature u analizi populacije Puccinia recondita tritici. Str. 287-321. Poglavlje. Nau~na publikacija. NAUKA OSNOVA ODR@IVOG RAZVOJA. Izdava~ Dru{tvo geneti~ara Srbije. ISBN 978-86-87109-00-1.Str. 339. Lukasz, S., Golka, L., Chelkowski J. (2003): Leaf rust resistance genes of wheat:identification in cultivars and . resistance sources. J. Appl Genet. 44 (2):139-49. Hysing, S.C. (2007): Genetic resources for disease resistance breeding in wheat: caracterization and utilization. Ph.D. ISSN. 1652-6880; ISBN 978-91-576-7308-4. p. 55. Kolmer, j. A. (1996): Genetic of resistance to wheat leaf rust. Annual Rewiew of Phytopathology. Vol. 34. p. 267-271. Mesterházy, Á., Pavel Barto{, P., Goyeau, H., Rients E. Niks, R. E., Csösz, M. (2000): European virulence survey for leaf rust in wheat. Agronomie 20 (7). p793-804. Park, R. F, Jahoor, A, Felsenstein, F. G, (1996): Genetic variation in European populations of Puccinia recondita f. sp. tritici using pathogenicity and molecular markers.Proc. of the 9th European and Mediterranean Cereal Rusts&Powdery Mildwes Conference. Lunteren, The Netherlands. 92-94. Roelfs, A. P. (1985): Epidemiology in North America. p. 403-434 in A. P. Roelfs and W. R. Bushenell. eds. The Cereal Rusts Vol. II; Diseases, Distribution, Epidemiology and Control. Academic Press, Orlando. Pathan, A.K. and Park, R.F. (2006). Evaluation of seedling and adult plant resistance to leaf rust in European wheat cultivars. Euphytica 149: 327-342.

263

Self-pollinated crops Breeding for Resistance to Biotic and Abiotic Stresses Poster Presentation CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008

CLASSIFICATION OF TURKISH WHEAT AND WILD RELATIVES FOR THEIR RUST DISEASE (Puccinia spp.) RESISTANCE GENE PROFILE Mahmut Can Hiz1, Yeliz Yilmaz1, Balkan Canher1, Alptekin Karagoz2 and Muge Turet Sayar1 1

Bogazici University, Department of Molecular Biology and Genetics, 34342 Istanbul, Turkey 2 Aksaray University, Department of Biology, 68100 Aksaray, Turkey E-mail:[email protected]

Abstract Folial fungal pathogens of Puccinia species cause the rust diseases in wheat and their management continues to be a major challenge to the wheat breeders Worldwide. Thus, knowledge about the types of resistance genes within the vast number of wheat collections available to breeders becomes the major factor in the application and success of durable resistance breeding programmes. Recent emergence of new stem rust pathogen race, Ug99, has alarmed all wheat growing countries. For this, 41 selected wheat germplasm collections majorly from (ARI) Agricultural Research Institutes in Eskisehir and Ankara and 13 wild relative species (covering 80 accessions) were screened by PCR-based molecular markers linked to resistance genes. Total of 19 resistance loci (8 Lr loci, 7 Sr loci and 4 Yr loci) covering for all Puccinia species have been targeted. Results have shown that 56% of all wheat germplasm were positive for all screened loci when Lr35, Sr2 and Sr39 loci were excluded. Among the wild relatives majority of them were positive for Lr29, 37, 50, Sr2, 22, 26, 38, and Yr15, 17, 26 loci. Key words: STS-PCR markers, rust disease resistance, wheat, wheat wild relatives Introduction Wheat is the most consumed (604 million metric tons) and the most grown (217 million hectare) food grain worldwide than any other crop (FAO, 2006). Major challenge in management of wheat production is the continuous battle against the wheat fungal pathogens mainly the rust diseases caused by Puccinia species (Kolmer, 2005). During epidemy, the loss of yield can reach up to 40% in susceptible cultivar plantation (Kosina et al., 2007,). Recently such outbreak alarm has emerged for stem rust race Ug99, initially detected in Uganda in 1999 but the wind-borne fungus spores have managed to spread to Kenya and Ethiopia in 2004, Yemen in 2007 and countries expected on its path are Egypt, Syria, Turkey and Iran (BGRI, 2008; Mackenzie, 2007). To combat with the wheat rust fungus and in hope to reduce the estimated 1-2 billion US$ damage cost in Asia alone, the Borlaug Global Rust Initiative has been established in 2005 with the objective to maximize the potential durability of deployed resistance in plants by breeding strategies using resistant varieties and wild relatives. Highly accepted approach is to develop wheat varieties carrying combination of several resistance genes against various pathogen races. Several researchers have indicated the importance of combination of certain stem rust resistance genes such as Sr2, 22, 24, 36, 39 to achieve effective resistance to stem rust (Singh et al., 2006; Jin et al., 2007). The lack of prior knowledge about the types of resistance genes within wheat collections available to breeders becomes the major limiting factor in the application and success of durable breeding programmes. However, continuously developed PCR-based molecular markers, highly linked to resistance genes, can facilitate genotyping in less time and more cost effectively (Reynolds et al., 2007; Sorrells 2007). Therefore, this study was aimed to screen 19 rust disease resistance loci by putting special emphasis on those effective for Ug99 race on wheat germplasm collection and wild relatives from Turkey to evaluate their resistance genotype diversity for future durable resistance breeding programmes. Materials and Methods Wild accessions of Triticeae used in this study cover the South-Southeast and Central Anatolian Regions of Turkey (Table 1). The wheat germplasm collected from ARI contains wheat cultivars (no. 1-17), advanced stage breeding lines (no. 48-59) and undescribed rust resistant genetic source wheat stock (no.18-33) (Table 2). From all the plant material, 3 seeds were selected and germinated until they reached to tiller stage in 20ml germination trays containing sand:torf:soil mixture in 1:1:1 ratio. During this period, all plants were kept in temperature and 264


light controlled growth chamber. For DNA extraction, leaf samples of 3mg were collected and grinded in mortar/pestle containing liquid nitrogen. Table 1. The origin and the number of accessions for the wild species Wild species Ae. mutica Ae. triuncialis Ae. Triaristata Ae.speltoides var. speltoides Ae.speltoides var. liguistica Ae.ovata Ae.caudata Ae. kotschyi T. turgidum var. Dicoccoides T.urartu T.araraticum T. monococcum var. Aegilopoides T. turgidum var. diccocon

Acc*. 2 4 2 20 5 2 3 1 17 4 3 15 2

Origin Haymana Haymana/ Hatay/K.maras/Cankiri D.bakir/Adiyaman S.urfa/Mardin/Adiyaman/G.antep/K.maras/Adana S.urfa/ G.antep S.urfa/ K.maraþ Haymana/S.urfa/ G.antep Hatay D.bakir/S.urfa/Kars/G.antep/K.maras G.antep/S.urfa G.antep G.antep/Hatay/S.urfa/G.Antep/D.bakir Sinop/kastamonu

*: Number of accessions for each wild species

Table 2. The wheat germplasm collections from Agricultural Reseach Centers of Turkey No. Wheat germplasm 1 Yakar 99 2 Bayraktar 2000 3 Mizrak 4 Demir 2000 5 Aksel 2000 6 Seval 7 Yayla 305 8 Altay 2000 10 Alpu 2001 11 Kinaci 97 12 Goksu 99 14 Yildirim 15 Bezostaya 1 16 Pamukova 97 17 Tahir ova 18 Bdk 2004 19 Bdk 2004 21 Bdk 2004 22 Bdk 2004 23 Bdk 2004 24 Bdk 2004

Origin Ankara Ankara Ankara Ankara Ankara Ankara Eskisehir Eskisehir Eskisehir Konya Konya Erzurum Sakarya Sakarya Sakarya Ankara Ankara Ankara Ankara Ankara Ankara

No. Wheat germplasm 25 Bdk 2004 26 Bdk 2004 27 Bdk 2004 28 Bdk 2004 29 Bdk 2004 30 Bdk 2004 32 Bdk 2004 33 Bdk 2004 48 Es00-ke3 49 Es03-ke12 50 Es03-se18 51 Eskiþehir-04kvd-20 52 Eskiþehir-04kvd-26-05bvd13 53 Eskiþehir-04kvd33-05bvd14 54 Eskiþehir-04kvd49 55 Eskiþehir-04kvd62-05bvd4 56 Eskiþehir-04kvd109-05bvd8 57 Eskiþehir-04svd13-05sbvd-b2 58 Eskiþehir-04svd34-05sbvd-k3 59 Eskiþehir-04svd47-05sbvd-k8 59 Eskiþehir-04svd47-05sbvd-k8

Origin Ankara Ankara Ankara Ankara Ankara Ankara Ankara Ankara Eskisehir Eskisehir Eskisehir Eskisehir Eskisehir Eskisehir Eskisehir Eskisehir Eskisehir Eskisehir Eskisehir Eskisehir Eskisehir

Powdered leaf extracts were kept in deep freezers (-70oC) prior to DNA isolation. DNAeasy Plant Kit (Qiagen) were used to isolate DNA from frozen leaf extracts using instructions in the kit manual. Nineteen rust disease resistance loci which include stem rust (Sr), leaf rust (Lr and yellow 265


rust (Yr) PCR-based molecular markers used were given in the Table 3. PCR reactions and cycles were optimized for each primer sets (Table 3) according to the suggestions of the literature. PCR cycles were performed in C1000 Thermal cycler (BioRad). PCR results were run at 1.5% agarose gel containing 0.5mg/ml EtBr and visualised under UV illumination. For the analysis of PCR results, a binary data matrix was created by scoring the presence (1) and the absence (0) of the bands on agarose gels. For wild species covering more than four accessions, the percentage of the positive scores were calculated and graded from 0-4 for each 20% interval (Table 5). Table 3. List of PCR-based molecular marker primers linked to resistance genes Primer Name SCS73719 F/R Lr28-01/Lr280-2 Lr29 F/R Sr39 F/R VENTRIUP-LN2 SC Yr15 F/R WMS382 F/R GWM533 F/R CFA2019 F/R Sr24#12 F/R Sr26#43 F/R WMS319 F/R WE210 F/R WMC44 F/R Lr21 F/R

resistance gene Lr24 Lr28 Lr29 Lr35, Sr39 Lr37, Yr17, Sr38 Yr15 Lr50 Sr2 Sr22 Sr24 Sr26 Sr36 Yr26 Yr29/Lr46 Lr21

References Gupta et al. 2005 Naik et al. 1998 Procunier et al. 1995 Gold et al. 1999 Helguera et al. 2003 Robert et al. 1999, 2000 Brown-Guedira et al. 2003 Spielmeyer et al. 2003 Sourdille et al. 2001 Mago et al. 2005 Mago et al. 2005 Tsilo et al. 2007 Wang et al. 2008 Singh et al. 2005 Fritz et al. 2001

Results and Discussion Among 41 wheat materials listed in Table 2, 56% were positive for resistance markers for all 19 resistance loci except Lr35, Sr2 and Sr39. The cultivars Yakar, Mizrak, Demir, Seval and Altay had the lowest marker coverage (52-68%) especially for Lr and Yr gene loci, did not show any amplification products for Lr21, 29, 35, 50, Sr38, 39, Yr15,17 and 26 markers (data not shown). It is very promising to observe the presence of marker for Lr46/Yr29 loci in all of the samples which were considered to be highly linked genes that provide slow rusting, non-race specific-adult plant resistance (Rosewarne et al., 2006) similar to Sr2 and Lr34/Yr18 loci (Lagudah et al.,2006; Jin et al. 2007) that also considered slow rusting genes. Combination of such slow rusting genes in wheat cultivars during breeding were considered to be the best approach to obtain durable, broad-spectrum resistance worldwide (Singh et al., 2000). Moreover, currently accepted strategy for Ug99 threat was to create boosting effect collectively by stacking such slow rusting gene complexes (Sr complex) in the same genetic background. In this study, lack of Sr2 locus marker in 34% of wheat material majorly covering the wheat cultivar and the advance breeding line group was alarming. When the wild accessions were examined, markers for Lr50, Sr22, 26, 38, Yr15, 17 and 26 were detected in almost all of them. Among all accessions of Lr loci, except Lr50, also Sr24 and Yr29 loci markers (except T. turgidum var. dicoccon and T. turgidum var. dicoccoides) were missing (Table 5). Despite low sample number, those accessions unique to Hatay region (Ae. kotschyi) and Central Anatolia region (Ae. mutica) (Dr. A. Karagoz pers. Comm.) contained valuable Ug99 effective Sr2, 26 and 38 gene markers (Table 4). Presence of Sr loci markers (T. turgidum var. dicoccon, T. turgidum var. dicoccoides, T. urartu, T.monococcum var aegilopoides) and Yr29 locus marker (T. turgidum var. dicoccon, T. turgidum var. dicoccoides ) in the evolutionary ancestor species of the wheat are valuable knowledge for future durable resistance breeding programmes. 266

267 +

+ +

+

+ +

+

+ +

+ + +

+

+ + + + + + + + + + + + + + +

+ +

+

+ +

+

+

+ + + + +

+ +

+

+

+ + + + +

+ +

+

+

+ + + + +

+ +

+ + + + + + +

+ + + +

0= 0-20%; 1= 20-40%; 2= 40-60%; 3= 60-80%; 4= 80-100%.

Screened Resistance Loci Wild species Lr21 Lr24 Lr28 Lr29 Lr 35 Lr37 Lr46 Lr50 Sr2 Sr22 Sr24 Sr26 Sr36 Sr38 Sr39 Yr15 Yr17 Yr26 Yr29 0 2 3 3 1 1 0 4 2 1 0 4 4 4 1 4 4 4 0 Ae. speltoides var. liguistica 0 2 2 4 1 1 1 4 2 2 0 4 3 4 1 4 4 4 1 Ae. speltoides var. speltoides 1 0 2 0 0 4 1 3 1 1 0 4 2 1 0 1 1 4 1 Ae. triuncialis 0 0 2 0 2 0 4 0 3 0 4 0 1 0 1 1 4 0 T. monococcum var. aegilopoides 1 0 0 3 4 0 3 0 3 3 4 0 4 3 4 0 4 4 4 0 T. turgidum var. araraticum 0 0 4 1 0 1 4 3 4 4 0 4 3 4 0 4 4 4 4 T. turgidum var. dicoccoides 0 0 3 1 0 1 1 4 0 4 0 4 1 4 0 4 4 4 1 T. urartu

+ +

Sr2 Sr22 Sr24 Sr26 Sr36 Sr38 Sr39 Yr15 Yr17 Yr26 Yr29

Table 5. PCR-based molecular marker screening results of the rust disease resistance loci for wild species covering more than four accessions.

Acc. Wild species Location Lr21 Lr24 Lr28 Lr29 Lr35 Lr37 Lr46 Lr50 No 0007 Ae. caudata Haymana + 5375 Ae. caudata Sanliurfa + + 5383 Ae. caudata Gaziantep + + + 5459 Ae. kotschyi Hatay 0004 Ae. mutica Haymana + + 5466 Ae. mutica Ankara + + + 5370 Ae. ovata Sanliurfa + 5444 Ae. ovata K.maraþ + + 5325 Ae. triaristata Diyarbakir + + + + 5363 Ae. triaristata Ad2yaman + + + + 2440 T. turgidum var. dicoccon Kastamonu + + 2453 T. turgidum var. dicoccon Kastamonu + +

Screened Resistance Loci

Table 4. PCR-based molecular marker screening results of the rust disease resistance loci for wild species covering less than four accessions.




Conclusions Despite the geographical advantages of Turkey as a member of Fertile Crescent Region in terms of its diverse genetic sources, our results indicate that these genetic sources can still be under great danger for new pathogen races such as Ug99, due to lack of gene combinations especially for non-race specific, durable resistance genes. Together with field responses of cultivated wheats, the results of the molecular markers should be integrated quickly in future breeding strategies. Acknowledgement This study has been supported by Bogazici University Scientific Research Projects Fund (BAP 07 HB108). References: BGRI (2008): The Borlaug Global Rust Initiative, Cornell University Ithaca, NY 14853 USA, http://www.globalrust.org Brown-Guedira GL, Singh S, Fritz AK (2003) Performance and mapping of leaf rust resistance transferred to wheat from Triticum timopheevii ssp. Armeniacum Phytopathology, 93, 7, 784-789 FAO (2006): Food, Agriculture Organization of the United Nations FAOSTAT Production Statistics. FAO, Rome, Italy, http://www.fao.org/ Gold J., Harder D., Townley-Smith F., Aung T., Procunier J. (1999): Development of a molecular marker for rust resistance genes Sr39 and Lr35 in wheat breeding lines. Electronic Journal of Biotechnology, 2 (1). Gupta S.K., Charpe A., Koul S., Prablu K.V. Haq Q.M.R. (2005): Development and validation of molecular markers linked to an Ae. Umbellulata derived leaf rust resistance Lr9 for marker-assisted selection in bread wheat. Genome, 48, 823-830. Helguera M., Khan, I. A., Kolmer J., Lijavetzky D., Zhong-qi L., Dubcovsky J. (2003): PCR Assays for the Lr37-Yr17-Sr38 Cluster of Rust Resistance Genes and Their Use to Develop Isogenic Hard Red Spring Wheat Lines Crop Science, 43, 1839–1847. Jin Y., Pretorius Z., Singh, R. (2007): New virulens within race TTKS (Ug99) of the stem rust pathogen and effective resistance genes. Phytopathology, 97, S137 Kolmer J.A. (2005): Tracking wheat rust on a continental scale. Current Opinion in Plant Biology, 8,441–449 Kosina P., Reynolds M., Dixon J., Joshi A. (2007): Stakeholder perception of wheat production constraints, capacity building needs, and research partnerships in developing countries. Euphytica, 157, 475–483 Lagudah E. S., Mcfadden H., Singh R. P., Huerta-Espino J., Bariana H. S., Spielmeyer W. (2006): Molecular genetic characterization of the Lr34/Yr18 slow rusting resistance gene region in wheat. Theoretical and Applied Genetics, 114, 1, 21-30 Mackenzie D. (2007): Billions at risk from wheat super-blight. New Scientist Magazine, 2598, 6-7 Mago R., Bariana H. S., Dundas I. S., Spielmeyer W., Lawrence G. J., Pryor A. J., Ellis J. G. (2005): Development of PCR markers for the selection of wheat stem rust resistance genes Sr24 and Sr26 in diverse wheat germplasm. Theoretical and Applied Genetics, 111, 3. Naik S., Gil K.S., Prakasa R.V.S., Gupta V.S., Tamhankar S.A., Pujar S., Gill B.S., Ranlekar, P.K. (1998): Identification of a STS marker linked to the Aegilops speltoides–derived leaf rust resistance gene Lr28 in wheat. Theoretical Applied Genetics, 97, 535-540. Procunier J.D., Townley-Smith T.F., Fox S., Prashar S., Gray M., Kim WK., Czarnecki E., Dyck P.L. (1995): PCR-based RAPD/DGGE markers linked to leaf rust resistance genes Lr29 and Lr25 in wheat (Triticum aestivum L.). Journal of Genetics and Breeding, 49, 87-92. Reynolds M. P., Braun H. J., Pietragalla J., Ortiz R. (2007): Challenges to international wheat breeding Euphytica, 157, 281–285 Robert O., Abelard C., Dedryver F. (1999): Identification of molecular markers for the detection of the yellow rust resistance gene Yr17 in wheat. Molecular Breeding, 5, 167–175. Robert, O., Dedryver F., Leconte M., Rolland B., De Vallavie Pope C. (2000): Combination of resistance tests and molecular resistance to postulate the yellow rust resistance gene Yr17 in bread wheat. Plant Breeding, 119, 467–472. Rosewarne G. M., Singh R. P., Huerta-Espino J., William H. M., Bouchet S., Cloutier S., McFadden H., Lagudah E. S.(2006): Leaf tip necrosis, molecular markers and â1-proteasome subunits associated with the slow rusting resistance genes Lr46/Yr29. Theoretical and Applied Genetics, 112, 3, 500-508 Singh R. P., Huerta-Espino J., Rajaram S. (2000): Achieving near-immunity to leaf and stripe rusts in wheat by combining slow rusting resistance genes. Acta Phytopathologica et Entomologica Hungarica, 35, 133—139. Singh R. P., Huerta-Espino J., William H. M. (2005): Genetics and Breeding for Durable Resistance to Leaf and Stripe Rusts in Wheat. Turkish Journal of Agriculture and Forestry, 29, 121-127. Singh R.P., Hodson D.P., Jin Y., Huerta-Espino J., Kinyua M., Wanyera R., Njau P., Ward R.W. (2006): Current status, likely migration and strategies to mitigate the threat to wheat production from race Ug99 (TTKS) of stem rust pathogen CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources 1, 054.

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Self-pollinated crops Breeding for Resistance to Biotic and Abiotic Stresses Poster Presentation CONVENTIONAL AND MOLECULAR BREEDING OF FIELD AND VEGETABLE CROPS Novi Sad, 24-27 November 2008 Sorrells M.E. (2007): Application of new knowledge, technologies and strategies to wheat improvement. Euphytica, 157, 299-306 Sourdille P., Guyomarc’h H., Baron C., Gandon B., Chiquet V., Artiguenave F., Edwards K., Foisset N., Dufour P., (2001): Improvement of the Genetic maps of wheat using new microsatellite markers. Plant & Animal Genome IX, Final Abstracts Guide. Applied Biosystems Press, Foster City, CA, 167 Spielmeyer W., Sharp P.J.,Lagudah E.S. (2003): Identification and validation of markers linked to broad spectrum stem rust resistance gene Sr2 in wheat. Crop Science, 43,333-336 Talbert L.E., Blake N.K., Chee P.W., Blake T.K., Magyar G.M. (1994) Evaluation of “sequence-tagged-site” PCR products as molecular markers in wheat. Theoretical and Applied Genetics, 87(7), 789-794. Tsilo T. J., Jin Y., Anderson J. A. (2008): Diagnostic microsatellite markers for the detection of stem rust resistance gene sr36 in diverse genetic backgrounds of wheat. Crop Science 48, 253-261. Wang C., Zhang Y., Han D., Kang Z., Li G., Cao A., Chen P. (2008): SSR and STS markers for wheat stripe rust resistance gene Yr26. Euphytica, 159,3. BGRI (2008): The Borlaug Global Rust Initiative, Cornell University Ithaca, NY 14853 USA, http://www.globalrust.org

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EVALUATION OF COMMON WHEAT CULTIVARS OF DIFFERENT GEOGRAPHIC ORIGIN FOR RESISTANCE TO LEAF RUST AND POWDERY MILDEW IN THE CONDITIONS OF NON-CHERNOZEM ZONE OF RUSSIA Inna Lapochkina1, Maria Rudenko1, Nail Gajnullin, Irina Makarova1, Vasiliy Kuzlasov1, Irina Iordanskaya1, Elizavetta Kovalenko2, Albina Zemchuzhina2, Harold Bockelman3 1

Agriculture Research Institute of Non-Chernozem Zone, Moscow Region, Russia; e-mail: [email protected] 2 All-Russian Institute of Phytopathology, Moscow Region, Russia; e-mail: [email protected] 3 U.S. Department of Agriculture - Agricultural Research Service, Aberdeen, Idaho, USA; e-mail: [email protected]

Abstract More than 600 spring wheat cultivars and breeding lines and 580 winter wheat cultivars and breeding lines from different geographic zones of the world were evaluated for reaction to leaf rust and powdery mildew in the Non-Chernozem Zone of Russia (Moscow Region). These lines were received from National Small Grains Collection (USDA-ARS, Idaho, USA). The potential donors of resistance to these dangerous pathogens were selected based on the results of three-year tests. Sixty-six lines of spring and 43 lines of winter wheat were identified with resistance to powdery mildew, and 100 lines of spring and 48 lines of winter wheat were identified with resistance to leaf rust. The lines with complex resistance to both pathogens and others economic characteristics (early date of heading, shot stem and height productivity) are valuable for breeding. Some lines were tested with the use of STS and SSR markers to genes of resistance to leaf rust and powdery mildew. The lines with one to several effective genes of resistance to leaf rust and powdery mildew in the Non-Chernozem Zone were selected: Cltr 14465, Cltr 15586, PI 519658, PI 519705 (USA), PI 547266 (England), PI 337156, PI 422299 (Argentina), PI 345461 (Bosnia). Key words: common wheat, leaf rust, Lr genes, powdery mildew, Pm genes, STS and SSR markers Introduction Wheat is the main food crop in Russia. It makes up more than 40% of the total grain production. Most losses in wheat production are due to diseases. Among numerous harmful wheat diseases, the most important are leaf rust, Septoria leaf spot diseases, and powdery mildew. The success of breeding of cultivars resistance to diseases entirely depends on initial material and donors. Such genotypes can be selected at study of world germplasm of wheat. Materials and Methods More than 600 spring wheat cultivars and breeding lines and 580 winter wheat cultivars and breeding lines from different geographic zones of the world were evaluated for reaction to leaf rust and powdery mildew in the Non-Chernozem Zone of Russia (Moscow Region). These lines were received from National Small Grains Collection (USDA-ARS, Idaho, USA). The intensity of powdery mildew was estimated in provocative environment. In the case of leaf rust, plants were infected with a population including the total spectrum of races characteristic of Moscow Region. Estimates were obtained according to Peterson et al. (1948). To identify the resistance genes, we used molecular markers linked to the known leaf rust resistance genes Lr1, lr9, Lr10, Lr21, Lr24, Lr28, Lr35, Lr37, Lr39, Lr50 and Pm2, Pm13, Pm4b, Pm16 genes. PCR analysis was conducted according to the primer protocol. The amplification products were electrophoretically separated in 2% agarose gel in Tris-borate. The main agronomic characteristics such as plant height (cm), productivity of ear (g), thousand seed mass (g) and date of heading were take into consideration. Results Sixty-six lines of spring and 43 lines of winter wheat were identified with resistance to powdery mildew, and 100 lines of spring and 48 lines of winter wheat were identified with resistance to 270



leaf rust. The lines with complex resistance to both pathogens and with other economic characteristics (early date of heading, shot stem and height productivity) are valuable for breeding. The description of spring and winter wheat lines with the best complex of economically valuable features is given in Tables 1 and 2. Table 1. The description of the best samples of spring common wheat with complex resistance to diseases sample

country

PI 282900 Argentina PI 337156 Argentina C1tr 15852 Mexico PI 519304 Mexico PI 520375 Mexico S1tr 15777 USA(N.D) S1tr 15810 USA(N.D) PI 519425 USA(N.D) PI 518658 USA(N.D) PI 520284 USA(N.D) PI 520527 USA(N.D) PI 520528 USA(N.D) PI 520529 USA(N.D) S1tr 15716 USA(MS) PI 519699 USA(MS) PI 532150 USA(MS) PI 346811 Yugoslavia Rodina (St) Russia

affection, % powdery leaf rust mildew 0 20/1 5 10/2 5 1/1 1 10/1 5 10/2 5 1/1 5 15/2 1 10/2 0 20/2 0 40/2 1 0 5 0 5 0 5 5/1 5 10/1 5 10/1 5 0 60 80 LSD P