Grasspea agronomic traits

Lathyrus Lathyrism Newsletter 4 (2005)

Characterization of grass pea (Lathyrus sativus L.) entries by means of agronomically useful traits G. B. Polignano1 1*, P. Uggenti1, G. Olita1, V. Bisignano1, V. Alba2 and P. Perrino1 1. Istituto di Genetica Vegetale, C.N.R., Via Amendola 165/A, 70126 Bari, Italia 2. Dipartimento di Biologia Difesa e Biotecnologie Agro Forestali, Università della Basilicata, Potenza *E-mail: [email protected]

distribution of the residual genetic variation is recommended for the benefit of both direct users and crop improvement programmes (12).

Introduction Grass pea or chickling pea (Lathyrus sativus L.) is a diploid (2n=14), self-pollinated annual with branched, straggling, or climbing habit, blue (sometimes violet or white) flowers and characteristic smooth seed with pressed sides (16). The center of origin and diversification of the Lathyrus gene pool is in the Mediterranean region (15). The earliest archaeological remains of Lathyrus appear in the Neolithic in the Balkans and Near East of Bulgaria, Cyprus, Iraq, Iran and Turkey (4). According to Kupicha (8), the genus Lathyrus contains about 150 species but only L. sativus is widely cultivated for human consumption, particularly in Bangladesh, China, Ethiopia, India, Nepal and Pakistan (10). In Italy, this crop has mostly disappeared and today it is no longer seen as the ‘food of the poor’ as it was in the past. Fortunately, grass pea is still used by local populations in marginal areas, and sold in some marketplaces.

In this regard it is important to underline that the consumption of L. sativus seeds by humans and animals has been limited by presence of a neurotoxin known as β-N-oxalyl-L-α,β-diaminoproprionic acid (β-ODAP) in the seeds, which when taken in large quantity can lead to “lathyrism” a disease causing paralysis of the limbs (3). With that premise, breeding programmes evolving genotypes combining high yield with high protein content and low neurotoxin (ODAP) are in progress all over the world (7). At the same time it was felt that it was necessary to evaluate and describe the genetic diversity available in the grass pea collections (2,6,10,11,12). In other words there is a need to survey, collect, conserve and characterise the valuable resources of the Lathyrus species germplasm for the benefit of both users and crop improvement programmes.

Emerging global and national strategies on sustainable farming systems, sustainable development and the preservation of biological diversity reflect concern at adequate quantification of local biodiversity. Consequently, researchers, farmers and policy makers have focused their attention on the neglected and/or underutilised crops to improve the food security, nutrition and economic welfare of humans all around the world (5). In Italy, among these species the grain legume grass pea has received renewed attention as a local and typical product, it is becoming an exclusive and fashionable food for which discerning consumers are prepared to pay a higher price than for other pulse products. In addition, the most interesting agronomical feature of the species are drought tolerance, resistance to pests and diseases, adaptability to different types of soil as well as to adverse climatic conditions (9). Despite these and other advantages, L. sativus is inadequately exploited and studied. In fact, it is well known that this crop is grown mainly as landraces; their genetic diversity is used and maintained largely by a small number of farmers in very limited areas of central southern Italy. In other words, valuable genetic resources of L. sativus are exposed to the threat of genetic erosion and disappearance. Therefore collection and storage of germplasm and deeper knowledge of the nature, entity, and geographical

The main objective of the present research was to study the variation in a collection of grass pea entries with respect to yield capacity and other important agronomic traits (such as biomass) with the aim of a direct utilisation of the most promising material and their use in cross combinations for breeding purposes. Material and Methods Seventy-six grass pea entries of different geographical origin were used. These were subset of the whole collection including entries characterized by desirable traits: erect plants, high podded node, early flowering, high seed yield, big and light seeds, high biomass, low ODAP content and high protein content. All entries were grown in 2002-2003 winter season on clay-sand soil at the experimental farm “Pantanello”, belonging to the Basilicata region, at Metaponto (Matera) in southern Italy. Generally the climate in the Metaponto area (0-300m a.s.l.) is a strong Mediterranean type with an annual rainfall less than 600 mm and an annual temperature trend consisting of mild or absent winters and hot summers. Sowing was done in mid November after a deep summer plowing and two secondary tillages. During summer tillage 120 kg/ha

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of correlation among traits for these entries. The first principal component accounted for 31% of variation reflected mostly influence on pod and seed traits. The second component accounts for 17% of the variance and thus is comparable in importance to the first. The traits with the largest coefficients and which contribute to it are the length of longest stem, biomass, seed yield and pedicel length. Time to flowering, leaf length, seed thickness, length of internode, leaf width, time to emergence and height of first podded node have some importance in the other components. Although there is no clear demarcation between important and unimportant principal components, it is interesting to note that yield and some yield components appear strongly in the first two components.

of P2O5 was applied. Harvest occurred at the end of June at full maturity stage. Five randomly chosen plants from each entry from a single row plot were scored for the 18 quantitative and qualitative descriptors reported in Table 1. Frequency distributions for the qualitative descriptors flower and seed colour were also determined. Multivariate data analysis followed three steps: a) estimation of standardized entry means of 16 quantitative traits; b) derivation of orthogonal, uncorrelated traits for each entry using Principal Component Analysis (PCA); c) clustering entries into similarity groups using uncorrelated traits (PCA coefficients). The SAS procedure PRINCOMP computed the correlation matrix and determined the principal components (SAS Institute, 1987). The sum of the first eight PC axes, representing 88% of total variation were used in subsequent analyses. Entries were clustered using Ward’s minimum-variance method (SAS Institute, 1987). The cluster routine was stopped to form five discrete clusters looking for a consensus among the four statistics R2 (RSQ), cubic clustering criterion (CCC), pseudo-F (PSF) and pseudo-t2 (PST2). Results of this clustering were combined with results of the PCA analysis as a visual aid in discerning clusters.

Clustering entries based on similarity of the first eight principal components identified five large groups accounting for a 31% share of variance. Cluster memberships are reported in Table 3. Cluster I included the highest number of Italian entries; while a large number of Cyprus entries were in cluster II. Entries from the other less represented origins spread over all five groups. Table 1. Means, minimum and maximum values, and coefficient of variation (C.V.) for 16 quantitative descriptors and frequency distributions for 2 qualitative descriptors observed in 76 grass pea landraces.

Results and Discussion Means, minimum and maximum values, coefficients of variation for 16 quantitative traits and the frequency distributions of the flower colour and seed colour are reported in Table 1. Entries showed a wide range of variation as evidenced by coefficients of variation. The most variable traits were seed yield, biomass, leaf width and seeds/pod; and the lowest values of variation were estimated for time to flowering and time of emergence; all the other traits showed intermediate values. The variability of means for yield components was lower than variability for seed yield. Extreme values for seed yield and biomass were 7.0214.0 and 13.0-481.0g respectively. The distribution in frequency classes for flower colour showed that nearly 51% of entries were characterized by violet flowers; while the prevalent seed colour was beige (68.4%). The eigenvalues representing the variance of the principal components, and the cumulative percent of the eigenvalues indicating percentage contribution to the total variance attributable to each principal component are given in Table 2. Eigenvectors indicating the degree of association among original data and each principal components are also reported. The first two PC axes accounted for >48% of the multivariate variation among entries and the first eight axes >88% of variation, indicating a moderate degree

Descriptora Time to emergence (d) Time to flowering (d) Length of longest stem (cm) Height first podded node (cm) Length of internode (cm) Leaf lenght (cm) Leaf width (cm) Pod lengthb (cm) Pod widthb (cm) Pedicel lengthb (cm) Seeds/podb (no.) Seed lengthc (cm) Seed widthc (cm) Seed thicknessc (cm) Seed yield (g) Biomass (g)

Mean 23.9 79.5 74.0 22.2 3.9 7.9 0.7 3.8 1.3 5.0 2.6 0.8 0.8 0.5 82.4 201.7

Flower colour Frequency (%) Seed colour Frequency (%) a

C.V. 5.8 3.1 18.9 24.1 24.6 23.9 34.3 12.4 17.7 23.0 33.8 25.0 23.0 16.0 48.7 44.0

White 37.6

Min Max 21.0 33.0 74.0 90.0 25.0 98.0 8.0 48.0 2,0 9.0 0.7 9.9 0.2 1.5 2.7 5.2 0.8 2.0 1.7 8.5 1.0 5.0 0.4 1.5 0.4 1.3 0.2 1.0 7.0 214.0 13.0 481.0 Colour Violet Pink 51.1 11.3

White

Beige

Brown

3.9

68.4

5.5

Green -grey 7.9

-

Data collected on single plant; b Average of 5 dry pods/plant; c Average of 5 seeds/ plant.

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Table 2. Principal component analysis (PCA) of descriptors associated with 76 grass pea landraces showing eigenvalues and proportion of variation associated with the first eight axes and eigenvectors of descriptors.

Eigenvalues Variation (%) com. Descriptora Time to emergence (d) Time to flowering (d) Length of longest stem (cm) Height of 1° podded node (cm) Length of internode (cm) Leaf lenght (cm) Leaf width (cm) Pod lengthb (cm) Pod widthb (cm) Pedicel lengthb (cm) Seeds/podb (n.) Seed lengthc (cm) Seed widthc (cm) Seed thicknessc (cm) Seed yield (g) Biomass (g) a

1 5.01 31

2 2.61 48

3 1.67 58

-0.12 -0.11 0.17 0.25 0.11 0.08 0.06 0.38 0.42 -0.03 -0.33 0.42 0.41 0.12 0.18 0.20

0.15 0.04 0.45 0.13 0.21 0.11 -0.05 -0.04 -0.09 0.42 0.31 -0.11 -0.14 -0.05 0.43 0.44

0.40 0.61 -0.18 0.18 -0.23 0.21 -0.41 0.13 0.07 -0.01 -0.07 0.06 0.07 -0.31 -0.02 0.06

PC axis 4 5 1.38 1.06 67 73 Eigenvectors 0.27 0.17 0.04 -0.07 0.00 0.11 0.36 0.28 0.23 0.64 0.20 -0.52 -0.34 -0.01 -0.15 -0.06 -0.06 0.00 -0.31 0.24 0.02 -0.08 -0.01 0.01 -0.00 0.04 -0.21 0.46 0.12 -0.40 -0.05 -0.40

6 0.98 79

7 0.71 84

8 0.62 88

0.44 0.09 0.00 0.20 -0.14 0.42 0.60 -0.10 -0.07 -0.19 0.08 -0.01 0.02 0.38 -0.01 -0.02

-0.45 0.31 -0.03 -0.16 0.26 0.52 -0.31 -0.10 -0.05 -0.11 0.04 -0.04 0.03 0.44 0.11 -0.08

0.35 0.05 -0.40 -0.49 0.20 -0.13 0.03 0.14 0.01 0.50 -0.08 0.11 0.13 0.32 0.07 0.01

Data collected on single plant; b Average of 5 dry pods/plant; c Average of 5 seeds/ plant.

Table 4. Cluster means of 16 quantitative descriptors observed in 76 grass pea landraces.

Table 3. Cluster memberships: entry number and geographical origin of 76 grass pea landraces. Entry1

Origin2

100263 100288 115099 100291 115242 115795 100287

ITA ESP ITA MAR ITA BGR AUS

106529 112414 112403 112415 112408 112410

AUS CYP CYP CYP CYP CYP

Cluster I (n=19) Entry Origin 112411 106531 112252 103641 103203 100041

CYP AUS ITA ITA ITA Unk.3

Cluster II (n=16) 111982 ITA 112418 CYP 112399 CYP 112417 CYP 112412 CYP

Descriptor

Entry

Origin

115243 113090 100290 112390 113874 100042

ITA ITA ITA CYP ITA Unk.3

112401 116171 112407 112419 116170

CYP ALB CYP CYP ALB

Time to emergence (days) Time to flowering (days) Length of longest stem (cm) Height of 1st podded node (cm) Length of internode (cm) Leaf length (cm) Leaf width (cm) Pod length (cm) Pod width (cm) Pedicel length (cm) Seeds/pod (n.) Seed length (cm) Seed width (cm) Seed thickness (cm) Seed yield (g) Biomass (g)

Cluster III (n=15) 110435 ITA 110437 ITA 115833 HUN 110955 ITA 110262 ITA 111986 ITA 111985 ITA 115097 ITA 100043 Unk.3 103585 ETH Cluster IV (n=17) 112400 CYP 112416 CYP 113873 ITA 115653 ITA 103244 ITA 103376 ITA 103468 ETH 103579 ETH 113949 HUN 115093 ITA 115094 ITA 100293 Unk.3 103212 ITA 110957 ITA 112251 ITA 116250 ALB 113089 ITA Cluster V (n=9) 100044 Unk. 112413 CYP 115096 ITA 100292 FRA 103237 ITA 106385 AUS 106434 ITA 106530 AUS 115241 ITA 1 Mediterranean Germplasm number (MG); 2ISO Country code ; 3Unknown 110434 110492 109680 100289 115834

I 24 80 67 20.7 3.7 7.3 0.7 4.0 1.3 4.8 2 0.9 0.9 0.5 83.5 195

II 24 99 74 19.2 3.9 8.3 0.7 3.5 1.0 5.4 3 0.6 0.6 0.5 81.9 197

Cluster III 23 79 75 21.8 3.7 11.0 0.8 3.9 0.8 5.1 2 0.9 0.8 0.4 73.1 206

IV 24 79 79 25.0 3.9 8.0 0.8 4.0 1.2 4.9 3 0.9 0.8 0.5 94.9 228

V 24 79 76 25.0 4.5 7.5 0.6 4.0 1.2 5.0 2 0.9 0.9 0.4 70.0 163

The mean values of the original traits for each cluster are listed in Table 4. For some traits it was impossible to clearly differentiate the phenotypic diversity among clusters, such as the time to emergence and seed thickness; while, by the other traits the clusters were better differentiated. In particular, means indicate shorter plants with larger pods and seeds in cluster I. Entries in cluster II with smaller seeds and shorter pods flower nearly three weeks later. Highest yield and biomass means characterize entries in cluster IV, which also showed taller plants and higher first podded node. On the contrary, cluster V grouped entries with longer internode and lower mean values for yield and biomass. Entries in cluster III had larger leaves; indicated by leaf length and width.

ITA ITA ESP RUS HUN

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Plot of PCAs and clusters using the first two axes, PRIN1 and PRIN2 3 2 1 0 -1 -2 -3 -3

-2

-1

Cluster 1

0

Cluster 2

1

Cluster 3

2

Cluster 4

3

4

Cluster 5

Fig 1. Plot of principal component analysis and clusters using the first two axes PRIN1 and PRIN2. Each cluster is represented by a different symbol. production (for example MG 113089, MG 112416) or to use them in future selection programs. As reported in previous experiences (1,14) grouping germplasm entries into morphologically similar and presumably genetically similar groups is useful when little is known about the crop history and the population structure; as is the case for the grass pea collection. It is evident that entries clustered together are more alike than entries from other clusters. However, the data must be considered with caution because they are an expression of linked genetic and environmental effects. So, it is important to emphasise that the groups were defined on the basis of results from in a single location of southern Italy. The clusters could be different if the examination took place elsewhere.

A combined spatial distribution of entries and clusters can be represented in two-dimensional scatter diagrams as shown in Figure 1. Conclusions The phenotypic diversity among grass pea entries was well defined by both Principal Component and Cluster analyses. Considering the different morpho-bioagronomic descriptors, it has been possible to observe a remarkable inter and intra-group diversity. The covariation structure in the material studied revealed a different association between traits. The traits with dominant roles in the first two components are closely related to yield and yield components; while, vegetative traits like flowering time, height of first podded node and leaf traits were separately linked to other components. This suggests the possibility of obtaining, though selection, suitable genotypes combining high yield with desirable traits for direct release as cultivars in marginal areas of southern Italy.

There seems to be no significant differences in relation to the origin of entries, most of which were from Italy and distributed in all groups. However, the entries from Cyprus with some exception were found to form a distinct group (II), which was characterized by entries showing smaller pods and seeds, longer pedicels and later flowering time. A more detailed geographical differentiation was impossible with many origins underrepresented, with the exception of Italy and Cyprus. In fact, at the level of five clusters, the proportion of variance accounted for by the clusters is 31%. This is a low percentage for the variance explained by the identified groups. Thus the differentiation according to these clusters can only be considered as a preliminary approach until more detailed analysis and information is available. Finally, the observed wide diversity in the Italian grass pea entries distributed in all groups suggests the use of this adapted material to breed new improved grass pea varieties.

Cluster analysis also helped us to differentiate entries on the ground of their different levels of similarity. Five groups were identified with clear-cut differences according to the first principal component, which mostly accounted for yield and yield components. Smaller differences among groups were seen according to the second principal component, which accounted for vegetative traits. Compared with other groups, group IV show highest mean values for yield, biomass, seed size and height of first podded node, which are useful agronomic traits to breed new grass pea varieties. With the exception of group V, which included the less productive entries, groups I, II and III were moderately similar. Among the entries tested the analysis provides useful information in order to utilise directly the most promising materials for

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