SOYBEAN Yield Components as Indirect Selection Criteria for Late-Planted Soybean Cultivars J.
E. Board^'r' M. S. Kang. and M. L. Bodrero
ABSTRACT
iittle vegetative grou,th for optimum yield (Egli et al..
Cultivar selection for late-planted soy'bean lGlycine max (L.\ Merr.l in the wheat-soybean doublecropping system is an important production problem. Top'yielding cultivars for late plantings could tre selected more efficiently by identification of rield components that indicate top 1ield, compared Nith the traditional combine-haryested plot yield method. Our objective rvas to identify yield components
1987). Drought stress during mid-July to late August is another problem for late-planted soybean in the southeastern USA (Morrison and Rabb, 1996). Associated with rcduced crop growth rate and dry matter accumulation during the pcriod emergence to R5, yieid losses at late planting dates are linked to lowcr pod number per area (pods m-r). mediated by reproductive node m 2 and/or pods per reproductive node (Board et al.. 1999). Another problem with late-planted soybcan is reduced plant height and lowcr height to the lowest pod (Ouattara and Weaver, 199-5). This problem is more severe in determinatc vs. indetermiualc cultivars and can result in combine vield losses. Cultural pracLices that increase light interception and crop grorvth ratc during the emergence to R5 period resulting in greater
as indirect selection criteria to identify top-yielding cultivars for late planting dates. A 2-yr studl'(1998 and 1999) with 26 cultivars was conducted at a mid-July planting at Baton Rouge, LA (30' N, 90" W). A similar study involving 27 difl'erent cultivars was conducted for I yr at Los C)liveros, Santa Fe Province, Argentina
that could be used
(32",18' S, 62" W), planted in early January 1999. Experirnental designs
were randomized complete blocks with four replications and one factor (cultivar). Data were obtained on combine-harvested plot yield, seed m 2, seed size, seed per pod, pods m 2, pods per reproductive node, and reproductive node m 2. Across years, yields at Baton Rouge ranged from ll.83 to 2992 kg ha--r, while yields in Argentina ranged from 1688 to 2809 kg ha 1. Yield at Baton Rouge increased x'ith maturity group, whereas in Argentina there *as no relationship behveen yield and maturity group. For both phenotl.pic and genot.rpic levels, selection for either seed m : or pods m : identilied top-lielding cultivars, although seed m. 2 was more accurate.
yield are narrow-row culture (Board and Harville, 1994). increased plant population (Ball et al.. 2000a). and avoidance of stresses such as waterlogging (Lin-
a1., 1998) and drought (Ball et al., 2000b). Although cultural practices to increase late-planted yield have been identified, determination of genetic methods is less clear. Previous studies demonstrated large yield increases through proper cultivar selection for late plantings, with potential yield improvement ranging from29 to 2J6"/", depending on range of cultivars and lateness of planting (Board, 2002). Cultivar recommendations for late-planted soybcan are hampered by significant cultivar x planting date interactions (Carter and Boerma,1979; Boquet et a1., 1982). There-
kemer et
Tr" wHEAr-soyBEAN doublecropping svstem has I gained wide acceptance in the southeastern USA, well as other soybean-growing regions such as Argentina, because of greater profitability compared with monocropped soybean (Larreche and Brenta, 1999; Wesley et aI., 1994, 1995). Besides greater profitability, doublecropping also provides for better erosion and pollution control (Elmore et aL.,1992; Kessavalou and Walters, L997), avoidance of some diseases (Whitam, 1996), and better seed quality and viability (Purcell and Vories, personal communication, 2001). Flowever, acceptance of doublecropping has been limited by low yields for as
fore, recommendations based on state-wide trials at nor-
mal planting dates are nol. generally applicable to late planting dates. Incorporation of the long-juvenile trait (Tomkins and Shipe, 1996) and development of indeterminate late-maturing [Maturity Group VII (MG VII)] cultivars have not been promising avenues for improving late-planted soybean yields. Late-planted studies in Louisiana among MG V, VI, and VII cultivars showed yield to increase with maturity group (Board, 2002). Currently, cultivar recommendations for late planting in the southeastern USA are based on state-wide cultivar trials similar to those conducted for normal planting dates (Bowman. 1993; Thurlow et a1.. 1991). Cultivar recommendations for late-planted culture, as well as cultivar-genotype development, would be enhanced by the identificalion of yield components that indicate high genetic vield potential. Identification of such markers would be helpcd by a grcater understanding of what explains cultivar yield differences at late plantings. AI-
late-planted soybean (planted at mid-June or later) (Boerma and Ashley, 1982). Reduced yields at late planting dates mainly result from shorter daylengths at late vs. normal planting dates during vegetative and early reproductive periods (Board and Settimi, 1986). This decreases the period emergence to R5 (stages according to Fehr and Caviness, 1977) resulting in too J.E. Board and M.S. Kang, Dep. of Agronoml,, Louisiana Agric. Exp. Stn., LSU Agric. Ctr., Baton Rouge, LA 70803; and M.L. Bodrero. EEA Oliveros INTA. 2206 Oliveros, Santa Fe, Argentina. Research support provided in part by the Louisiana Soybean Promotion Board.
Approved for publication by the Director of the Louisiana Agric. Exp. Stn. as manuscript no. 02-09-0113. Received 12 Mar.2002. 'tCorresponding author (
[email protected]). Published in Agron. 1.95:420429 (2003).
Abbreviations: MG. rnaturitv group.
420
121
BOARD ET AL.: SELECTION CRITERIA FOR LATII-PLANTED SOYtsEAN.
though it is well established that environmental factors r reguiatc yield through seed m rather than seed sizc
(Egfi, f qgS), the relitive importance ol sccd m-r and ieed size in affecting genotvpic vield differences is less well known. Salado-Navarro et al. (1985) cited several reports showing a positive relationship betrveen length of the secd-filling period and yield among soybean geno-
types. Since longer sced-lilling period increases seed siie, thesc reports suggested that seed size was att important yicld component influencing genotypic yield diffcrc"t. Ho*ever. the studl' by Salado-Navarro et al' "t (198-5) concluded that usefulness of seed-filling period as an indirect sclection criterion for top-yielding genotypes
was limited by highly significant genotype / t:nvirorlmental interactions. Thus. the importance of seed sizc as an indirect selection criterion for top-yielding cultivars
remains in doubt. Little research concerning the influence of other Yield components on yield at the genotypic level has been done. Early studies indicatcd that for many crops, negative correlitions, on both thc phenotypic and genotypic levels, occurred between yield components affecting This phenomenon, when a phenoyield -typic (Adams,1967). or genotypic increase in one yield component (e'g', l) results in a decline in some other yield compos-eed m ncnt (e.g.. seed size), such that final yield is unafl'ectcd, is referied to as yield component compensotion' For example, Hartwig and Edwards (1970) backcrossed genotypes having i range of seed size into near-isogenic linei. and determined that small-seeded lines produced morc pods and seed per plant. whereas large-secded lines pioduced small numbers of pod and seed per plant' Thus, genotypic changes in seed size or seed per plant had no effect on final Yield. Some research involving genotypic correlation and path analyses has been conducted among yield and yield but the studies involved a relatively small "o*pon".,tt. ,r*b", of genotypes and/or cultivars, and results varied between studies. Among a set of 36 cultivars grown in
India (Lal and Haque, 1971), yield for both phenotypic and genotypic levels was found to be positively influby number of nodes and pods per plant, whereas "n."d seed size did not affect yield. Another more recent study involving 12 cultivars indicated that pods per reproductive node was the only yield component showing promise as an indirect selection criterion for top-yielding cultivars (Board et a1.,1997.1999). Because of limited
data and divergent results, the obiective of this researcl.t was to analyzi data sets from Louisiana and Argentina involving a wider range of cultivars relative to previous
studies io determine which morphological factors or yield components (seed m-2. seed size, seed per pod' pods
m
2,
pods per reproductive node, and reproductive
node m-2) havi the greatest influence on final seed yield.
MATERIALS AND METHODS Late-Planted Cultivar Studies in Louisiana Studies in Louisiana were conducted at the Ben Hur Research Farm near Baton Rouge, LA (30' N, 90" W) during
1998 and 1999. The Baton Rouge study was machine-planted
on 13 July 1998 and 21 Jnly 1999 on a Commerce silt loam soil (fine-silty, mixed, nonacid, thermic Aeric Fluvaquents)' Length of the growing season (emergence to R7) in 199! averiged 91 d for MG IV and V cultivars; and averaged -94-d for Mb VI cultivars. In 1999. the growing season was a little
shorter for MG IY and \'(89 d) and VI (93 d) cultivars' Harvest maturit\' (R8) sas consistentlv about 1 wk after R7' Experimental units sere four-rou plots haring a row spacing of 75 cm and 6.1 m ro$ lensth tlS j m:t Plant population' based on stand counts taken at R5. rras ll-< 0(-Nl plants ha Fertilizer was applied accordins to soil test re;or'mendations : at the rate of O+1OZ kg ha (\-P-Kt. al'j sorl pH *as within the optimal range. Weeds. disea:es. anc rr-il;'t: '1 :r; controlled with recommende d practice s. Erpe rlne nt'l : : s - ::' at Baton Rouge was a randomized complete L'loik r\li:- :-r factor (26 cultivars, Table 1section I). four r'plL:'ii;:":: 2 vr.
'Yield
(kg ha ') was determined bl comL'in= L=' 'sl '-: r*'-r interior rows (6.5 mr) of each plot that had L'ce n =n:-:l-':i:l:d : to 4.3 m and corrected to 130 g kg moistur; \-r'i: '-":rp"nents were determined as follo*'s:
1. Seed size (g per 100 seed) u'as determins; 1; f"i[ r'ears by counting 300 seed from each rielc s':::p1' s'ith an automatic seed counter, drying the seei :'ri l' c ttt con-*;iqhing the stant weight at 60'C in a forced-air cln er. sample, and then dividing the rleight L'r thrce' r) 2. Seed number per area (seed m \\li c'!3r:Trined in both years by first converting vield rn kg ha at 130 g kg Imoisture to dry yield in g m :at -1r '' k- (the sime moisture content for seed size i. and rhe n diriding : dry yield by seed size (as g per seedr Thus. g m ldryr' L yietd)lgseea (individualieed sizet calculat:s seedm 3. Seed per pod (no.) was deterrnined rn t'oth rears from a 10-planfsample taken randomll from rnlenor portions of th^e plot between R6 and R7 after irnal poci and.seed
m 'were determined (Board and Tan. 1995: Pigeaire et rn a subsample 1986). The number of bulging locules 100 randomly selected pods rrere counted mine seed per pod. a1.,
of
to deter-
:1 4. Pod number per area (pods m ua: calculated in both : per pod (seed m-r/ seed bl years by diviiing seed m. r)' ieed per pod : pods m 5. Pods perieproductive node (determi-ned onlv rn 1999) was ditermined from the same 5ample used ior determi-
nation of seed per pod.
A11
reproductive nodes (a repro-
ductive node is defined as a node beanng at least one pod having at least one seed) and podr in the samples were counted and pods per reproductive node determined by dividing pod number bl reproductive node number.
6. Reproductive node number per area (reproductive nodel * i) *ut also determinea in fSSg b1' disiding pods m by pods per reproductive node (pods m-lpods per reProductive node
= reproductive node m
r).
Analysis of variance was performed with the SAS General
Linear Models Procedure (SAS Inst., Cary, NC) with mean separation according to I-SD. Cultivar means were considered similar if they fell *ithin the LSD (P < 0.05) range for the
top-fielding iultivar. Correlation and path analyses at,the phenotvpiJand genotypic Ievels were applied.using all data bbren'itioo. lr'ithiri years. The phenotypic levelinvolves corre-
lation and path anali'ses that include both genotypic and environmental factors. ti.hereas genotypic analyses exclude environmental factors and focus strictly on genetic effects. Thus, the genott'pic correlations and path analyses define more
422
AGRONOMY JOURNAL. VOI-. 95. NIARCH_APRIL
clearly what factors affect yield genetically than do the phenotypic analyses. Both analyses were applied to the data within primary, secondary, and tertiary yield components. Primary predictor variables seed m 2 and seed size affected the primary response variable yield; secondary predictor variables seed per pod and pods m r affected the secondary response variable seed m 2; and tertiary predictor variables reproductive node m I and pods per reproductive node affected the tertiary response variable pods m r. A diagram describing the path analyses for the various yield components is shown in Fig. 1. This diagram indicates direct and indirect pathways of influence for predictor variables on a response variable. Within each trait level, simultaneous equations rn'ere solved for direct path coefficients by a PROC IML (SAS Inst., Cary, NC) version of a computer program given bv Kang (1994). Indirect path
coefficients were determined by multiplying appropriate r (correlation coefficient) and path coefficient values. The unacTable
L
2OO3
counted for residual effect and coefficient of determination were computed in accordance with Kang (1994). The path analyses were done additively. Our criteria for identifying the importance of a specific trait in affecting its response variable were: 1. Positive correlation between the trait and the response variable.
2. Large positive direct effect by the trait on the response variable.
3. Small or nonexistent negative indirect effects by the trait on the response variable via other traits (i.e., lack of yield component compensation). Late-Planted Cultivar Study in Argentina This study was machine-planted 6 Jan. 1999 at the Oliveros
INTA (National Institute for Agricultural Technology) exper-
Formal names and corresponding abbreviated names for entries in late-planted soybean cultivar sfudies at Baton Rouge, LA,
--:4 lel 9_l*"191 tqll_rg 3:g"'lq"1 l,__gs_l_gr Formal cultivar name
Abbreviated cultiyar name
I. Asgrow A5601 Asgrow A5602 Asgrow A5885 Asgrow A6101 Asgrow A6961 Buckshot 55 Deltapine DP3627 Deltapine DP3640 DSna-Gro 3495
A-s602
A5885 A6101 A6961 BS55
DP3627 DP36-10
DG3.l95 DG3576 H4994RR H4998RR
Hartz variety H4994RR Hartz variety H4998RR Hartz variety H5000RR Hartz variety H5088RR Hartz variety H6255RR Hornbeck HBK49 Hlperformer HYP498 Hyperformer HYP574 Mycogen 470 Northrup King Brand 55711 Northrup King Brand S6X6 Pioneer 9511 Pioneer 96B01RR Pioneer 9692 Terral TV4975 Terral TV5466RR
HsOOORR
H5O88RR H6255RR
HBK49 HYP498 HYP574 MYC.l70 NKS5711 NKS6266 P9511
96BOIRR P9692 TV4975
TV5466RR
II.
ACA
A4657 A5435
45634
A6401 A6444 A6445 Campeona
Camila 64
Don Mario 4{l Don Mario 57 Don Mario 501 Dyna-Gro
36E2
FACA 502 Hartz variety H6900RR Haskell
HM ETNT
v v v
VI VI
v
VI VI
IV
v
IV IV
v v
VI IV IV
v IV v VI v VI VI IV
v
1999 late-planted cultivar study at Los Oliveros, Santa Fe Province, Argentina
560
Asgrow Asgrow Asgrow Asgrow Asgrow Asgrow
Maturity group
to 1999 late-planted cultivar studies at Baton Rouge A5601
D5ma-Gro 3576
ACA
1998
36ORR
44
HM 541RR K882 (advanced breeding genotype) K1014G (advanced breeding genotlpe) K1619G (advanced breeding genotype)
560
VI IV
4{6,57 A5435 A5634 A6401
v v
46444
1'I
A6445
CAMP CAM 64 DM4s DM57 DMSOI DG3682 FACASO2 H69OORR
Haskell H}I36ORR l{Nt46/l
VI
\T \T
vI IV v v vII v VI
\1I \T \T
HII{54IRR
v
K882 K1014G K1619G
VI
Maria 55RR
MAR55RR
P661G (advanced brecding genotlpe)
P661G
Pioneer 9.1{l2RR
P9ZE2RR
Spring 53 Stonewall
Spring53
STWALL
vII
\T
v
VI IV
v vII
+.L-1
SOYBEAN BOARD ET AL.: SELECTION CRITERIA FOR LATE-PI-AN'|ED
Seed size
iment station near Los Oliveros, Santa Fe Province, Argentina (i''+t'S, 62" w) on a silt loam (thermic typic Argiudoll Ma-
(1)
Seed/Pod
iiel). Length of the growing season (em91g^e19e to R7) averg3 MG V cultivars' 97 d Ga'88 d"for MG IV cultivirs, d for VII cultivars' Harvest MG d for 100 and cultivars, VI VfG iJr
(4)
Pods/rep. node
I |
(R8) was consistently about 1 wk after R7' Experimental units were eight-row plots with a 70-cm row spaclng ;rd 6-r, row length (33.6 ml). Plant population (based-on ,iuna.ourtt averiged'from 0.5-mr samples taker atr'20 d after
;;t*rty
R1, R5; and R7) was 340 000 plants
"-"ig.n.", ;h";;;--".ded
ha This
was
v
YI
P9692 A6961
VI
v VI v
A58E5
DP3627 BS55 ItvIYC470
TV
Y VI
DG3576 H6255RR DG3495
TV
w
TV4975
VI
96BO1RR P9s11
NKS571L H4998RR
TV5466RR NKS6266 A6101
HBK49 A5601 H5OE8RR
H4994RR A5602 HsOOORR
+
\/I
w VI w
HYP498
t MG :
v v IV v
v v w v v
t |
m
l.
In both years. top-r'ieldins cuitir.arss ere gencrally those
:' having irigh numbcrs ol' scs-d m uhereas seed sizer ,"JtE"O [er pod s'cre unrcli'tted sith vield' Pods m utro upp"rt"d related u ith vi.'ld' ahhough not as closely ur r"",i m-2 (Tables 2 and -1 ). Observations made in Tables 2 and 3 were confirmed t"r correlation and path
analyses (Tables 4 and 5). In 1996'.t ield on both phenotvoic and'eenotypic lcvels u as much more strongly influ-r .'J..a Uv"t.ea m-t than seed sizc (Table'1)' Seed m accounted for 85 and 72'/. (f r.alues) of the variability in yield on the phenotypic and eenotr.piclevels, respectivlly. In contrast, seed size accounted for only 5 and
near Baton Rouge, LA, 1998.
for 26 soybean cultivars
Seed size
Yield
g (100 seed)
t
Seed per pod
Pods m-2
no.
no.m l
kgha'
no.m
264/+
18091 15ss+
13.15
r.98
t4.61+
2.09
9t6i 74
1s84i
12.6t 12.4t
2.31
687
2.01
77ti
12.80
2.54r
58,1
14.26i
2.07
643
73.32 13.45 10.64
ro+
617
2.36+
587
t 1,
818+
1262
14.37i
1260
13.82
1.93 2.31+
1235
11.09;
13s4 1164 1190 1190 1113 1218 1234
12.79
1.9.1
14.53i
2.07
11.10; 13.35
, 17+ ,ro
686 544 s36 699 s63 506
12.54 12.21
2.08
5E7
r094
1-1.79
2.35+
473
t641
1062
1529 1458
2.26 2.05 2.14
470
1251
t-1.9-1i 11.02
2s13+
,rrli2t36
2ll5 2095 2087 2073 2051 2032 1941 1936 1922 1882
t872 1755
1719
t701 1681 1673
t420
t392 1183
2
1ss0+ 1482+ 1320
1{02 1378 1736+
1-1.957
,
2.30i
,17+
,1r-:
5M 486
(ro 612 429 516
1052 1063
12.{9
tt32
I 1.10
2.t9
521
1{.09+
2.10
367
762
maturit-r grouP. simitar according to LSD ar thc 0.05 proha'ility le'cl.
iia-i*t"i rr"rni i.e
I
Y
Yieltl vs. Seed m I and Seed Size Cuitivars that lrere rtrp-rielding in both Ycars o[ the 'g1 p-57-1' (MG V), and studv g'ere 'DPi610' (\1G VI ,. (Tables l). Cultivars 'DP3627' I and 'Pg692' (NlG VIt \ l). and'A5885'(MG Y) (MG VI).'H62-55RR'(\lG (1999) (Table 3)' iear second the ln top-yielding iere
Significant effects (P < 0.05) for ycar and cultivar 2, occu?.ed for yield and seed m but year x cultivar interactions were not significant. Seed size showed significant effects for cultivar and ycar X cultivar interaction. Therefore, yield and all yield component data were presented t"pu.ut"ly for thc 2 yr' Seed per pod was and the year x iignificantly iffected by years, cultivars, 2 significantly was m pods intLraction, wheieas effccts were "riltiuu, Cultivar cultivar' and year affected only by
Id}?574
t
x
z
productive node
ANOVA
VI
I
(3)
also significant for pods per reproductir.e node and re-
RESULTS Baton Rouge StudY
DP3640
_--/ n
Yield
level Fig. 1. Path diagram sho*'ing interrelationships antong,primary 'traits (traits i 2 3), seiondarl' level trails (traits 4' 5 -- 2)' and i".tirty'f"t"f ti"its (6, ? .- 5). X, i and Z represent residual effects' in theirirnary, secondary, and tertiarl levels' respectivelr''
Analyses of variances, mean separation, correlation analyses' used and path analyses were also done with the same methods for the Baton Rouge studY'
MGt
seed n'z (2\
m'z (5)
m'2(7\
I (no' m :)' ,i"ia frcha'),seedsize (gper 100 seed),seedm ')' l..Jp.ipoO [no.), pods * " (no. m pods perr)reproductile una."pioOr.tive node m ' (lo' m were deter"ta.ino1l, same manner as in the Baton Rouge study' in.the mined
Cultivar
-
/ Rep. node
plant population for late-planted soybean in not the area. Fertilizei was noi applied because soil tests did insects and diseases, Weeds, i"uJ u"y mineral deficiencies. we." corri.otted with recommended practices' Experimental factor (27 i"G;;;t a randomized complete utoct wlttr one 1 yr' Plot and replications, four II), 1 section Table ;itfi,;^.
Table 2. Yield and Yield
(6)
i t ---.-- Pods
i
\\* -=-
l2.M
2.tt
424
AGRONONI\'JOL RNAL. VOL. 95. MARCH_APRIL
2OO3
Table 3. Yield and yield components for 26 soybean cultivars gorwn near Baton Rouge, LA, 1999.
I\IG'|
Cultivar
Yield
Sced
kghar
vI
DP3627 H6255RR
\-I
\l
DP-1640
\.I
P9692 A5885
\-
\' v
HYP574 DG3s76
Iv
HYP498 H5088RR
\,
vI
NKS6266
I\I\-
HBK49 TV4975
I\'
MYC,t70 P9511
\-
DG3495 NKS5711 96BOIRR A6961
IY
A610r
YI
\' \t \t v
BS55
v \' Iv
H5OOORR
T\'-i466RR H4994RR H4998RR A5601 As602
i i
IY
no.
ml
nt
2992:
18887
29-19:i
2860+
1916; 2107i
l+
281
2628i;
g (100 sccd)
1917i
2.,15
1644
14.53:i 13.49
2501 2495 2472 2440
1950+ 18337
1516 1526
11.66 12.33 13.12 13.63 12.59 13.96 73.79
l{38
1{.-
