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SOYBEAN

Yield Components as Indirect Selection Criteria for Late-Planted Soybean Cultivars

^a Dep. of Agronomy, Louisiana Agric. Exp. Stn., LSU Agric. Ctr., Baton Rouge, LA 70803
^b EEA Oliveros INTA, 2206 Oliveros, Santa Fe, Argentina

^* Corresponding author (jboard{at}agctr.lsu.edu)

Received for publication March 12, 2002.

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSION REFERENCES

 
Cultivar selection for late-planted soybean [Glycine max (L.) Merr.] in the wheat–soybean doublecropping system is an important production problem. Top-yielding cultivars for late plantings could be selected more efficiently by identification of yield components that indicate top yield, compared with the traditional combine-harvested plot yield method. Our objective was to identify yield components that could be used as indirect selection criteria to identify top-yielding cultivars for late planting dates. A 2-yr study (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 different cultivars was conducted for 1 yr at Los Oliveros, Santa Fe Province, Argentina (32°48' S, 62° W), planted in early January 1999. Experimental 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 1183 to 2992 kg ha^-1, while yields in Argentina ranged from 1688 to 2809 kg ha^-1. Yield at Baton Rouge increased with maturity group, whereas in Argentina there was no relationship between yield and maturity group. For both phenotypic and genotypic levels, selection for either seed m^-2 or pods m^-2 identified top-yielding cultivars, although seed m^-2 was more accurate.

Abbreviations: MG, maturity group

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSION REFERENCES

 
THE WHEAT–SOYBEAN doublecropping system has gained wide acceptance in the southeastern USA, as well as other soybean-growing regions such as Argentina, because of greater profitability compared with monocropped soybean (Larreche and Brenta, 1999; Wesley et al., 1994, 1995). Besides greater profitability, doublecropping also provides for better erosion and pollution control (Elmore et al., 1992; Kessavalou and Walters, 1997), avoidance of some diseases (Whitam, 1996), and better seed quality and viability (Purcell and Vories, personal communication, 2001). However, acceptance of doublecropping has been limited by low yields for 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 little vegetative growth for optimum yield (Egli et al., 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 reduced crop growth rate and dry matter accumulation during the period emergence to R5, yield losses at late planting dates are linked to lower pod number per area (pods m^-2), mediated by reproductive node m^-2 and/or pods per reproductive node (Board et al., 1999). Another problem with late-planted soybean is reduced plant height and lower height to the lowest pod (Ouattara and Weaver, 1995). This problem is more severe in determinate vs. indeterminate cultivars and can result in combine yield losses. Cultural practices that increase light interception and crop growth rate during the emergence to R5 period resulting in greater yield are narrow-row culture (Board and Harville, 1994), increased plant population (Ball et al., 2000a), and avoidance of stresses such as waterlogging (Linkemer et al., 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 from 29 to 276%, depending on range of cultivars and lateness of planting (Board, 2002). Cultivar recommendations for late-planted soybean are hampered by significant cultivar x planting date interactions (Carter and Boerma, 1979; Boquet et al., 1982). Therefore, recommendations based on state-wide trials at normal planting dates are not 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 al., 1991). Cultivar recommendations for late-planted culture, as well as cultivar–genotype development, would be enhanced by the identification of yield components that indicate high genetic yield potential. Identification of such markers would be helped by a greater understanding of what explains cultivar yield differences at late plantings. Although it is well established that environmental factors regulate yield through seed m^-2 rather than seed size (Egli, 1998), the relative importance of seed m^-2 and seed size in affecting genotypic yield differences is less well known. Salado-Navarro et al. (1985) cited several reports showing a positive relationship between length of the seed-filling period and yield among soybean genotypes. Since longer seed-filling period increases seed size, these reports suggested that seed size was an important yield component influencing genotypic yield differences. However, the study by Salado-Navarro et al. (1985) concluded that usefulness of seed-filling period as an indirect selection criterion for top-yielding genotypes was limited by highly significant genotype x environmental interactions. Thus, the importance of seed size 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 indicated that for many crops, negative correlations, on both the phenotypic and genotypic levels, occurred between yield components affecting yield (Adams, 1967). This phenomenon, when a phenotypic or genotypic increase in one yield component (e.g., seed m^-2) results in a decline in some other yield component (e.g., seed size), such that final yield is unaffected, is referred to as yield component compensation. For example, Hartwig and Edwards (1970) backcrossed genotypes having a range of seed size into near-isogenic lines, and determined that small-seeded lines produced more pods and seed per plant, whereas large-seeded lines produced 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 components, but the studies involved a relatively small number 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 influenced by number of nodes and pods per plant, whereas 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 al., 1997, 1999). Because of limited data and divergent results, the objective of this research was to analyze data sets from Louisiana and Argentina involving a wider range of cultivars relative to previous studies to 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) have the greatest influence on final seed yield.

	MATERIALS AND METHODS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSION REFERENCES

 
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 July 1999 on a Commerce silt loam soil (fine-silty, mixed, nonacid, thermic Aeric Fluvaquents). Length of the growing season (emergence to R7) in 1998 averaged 91 d for MG IV and V cultivars; and averaged 94 d for MG VI cultivars. In 1999, the growing season was a little shorter for MG IV and V (89 d) and VI (93 d) cultivars. Harvest maturity (R8) was consistently about 1 wk after R7. Experimental units were four-row plots having a row spacing of 75 cm and 6.1 m row length (18.3 m²). Plant population, based on stand counts taken at R5, was 225 000 plants ha^-1. Fertilizer was applied according to soil test recommendations at the rate of 0–0–107 kg ha^-1 (N–P–K), and soil pH was within the optimal range. Weeds, diseases, and insects were controlled with recommended practices. Experimental design at Baton Rouge was a randomized complete block with one factor (26 cultivars, Table 1 section I), four replications, and 2 yr.

1. Seed size (g per 100 seed) was determined in both years by counting 300 seed from each yield sample with an automatic seed counter, drying the seed for 3 d to constant weight at 60°C in a forced-air dryer, weighing the sample, and then dividing the weight by three.
   
2. Seed number per area (seed m^-2) was determined in both years by first converting yield in kg ha^-1 at 130 g kg^-1 moisture to dry yield in g m^-2 at 30 g kg^-1 (the same moisture content for seed size), and then dividing dry yield by seed size (as g per seed). Thus, g m^-2 (dry yield)/g seed^-1 (individual seed size) calculates seed m^-2.
   
3. Seed per pod (no.) was determined in both years from a 10-plant sample taken randomly from interior portions of the plot between R6 and R7 after final pod and seed m^-2 were determined (Board and Tan, 1995; Pigeaire et al., 1986). The number of bulging locules in a subsample of 100 randomly selected pods were counted to determine seed per pod.
   
4. Pod number per area (pods m^-2) was calculated in both years by dividing seed m^-2 by seed per pod (seed m^-2/seed per pod = pods m^-2).
   
5. Pods per reproductive node (determined only in 1999) was determined from the same sample used for determination of seed per pod. All reproductive nodes (a reproductive node is defined as a node bearing at least one pod having at least one seed) and pods in the samples were counted and pods per reproductive node determined by dividing pod number by reproductive node number.
   
6. Reproductive node number per area (reproductive node m^-2) was also determined in 1999 by dividing pods m^-2 by pods per reproductive node (pods m^-2/pods per reproductive node = reproductive node m^-2).
   

Analysis of variance was performed with the SAS General Linear Models Procedure (SAS Inst., Cary, NC) with mean separation according to LSD. Cultivar means were considered similar if they fell within the LSD (P < 0.05) range for the top-yielding cultivar. Correlation and path analyses at the phenotypic and genotypic levels were applied using all data observations within years. The phenotypic level involves correlation and path analyses that include both genotypic and environmental factors, whereas genotypic analyses exclude environmental factors and focus strictly on genetic effects. Thus, the genotypic correlations and path analyses define more 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^-2 affected the secondary response variable seed m^-2; and tertiary predictor variables reproductive node m^-2 and pods per reproductive node affected the tertiary response variable pods m^-2. 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 were solved for direct path coefficients by a PROC IML (SAS Inst., Cary, NC) version of a computer program given by Kang (1994). Indirect path coefficients were determined by multiplying appropriate r (correlation coefficient) and path coefficient values. The unaccounted 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).
   

View larger version (11K): [in this window] [in a new window]   Fig. 1. Path diagram showing interrelationships among primary level traits (traits 1, 2 3), secondary level traits (traits 4, 5 2), and tertiary level traits (6, 7 5). X, Y, and Z represent residual effects, in the primary, secondary, and tertiary levels, respectively.

	RESULTS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSION REFERENCES

 
Baton Rouge Study
ANOVA
Significant effects (P < 0.05) for year and cultivar occurred for yield and seed m^-2, but year x cultivar interactions were not significant. Seed size showed significant effects for cultivar and year x cultivar interaction. Therefore, yield and all yield component data were presented separately for the 2 yr. Seed per pod was significantly affected by years, cultivars, and the year x cultivar interaction, whereas pods m^-2 was significantly affected only by year and cultivar. Cultivar effects were also significant for pods per reproductive node and reproductive node m^-2.

Yield vs. Seed m^-2 and Seed Size
Cultivars that were top-yielding in both years of the study were ‘DP3640’ (MG VI), ‘HYP574’ (MG V), and ‘P9692’ (MG VI) (Tables 2 and 3). Cultivars ‘DP3627’ (MG VI), ‘H6255RR’ (MG VI), and ‘A5885’ (MG V) were top-yielding in the second year (1999) (Table 3). In both years, top-yielding cultivars were generally those having high numbers of seed m^-2, whereas seed size and seed per pod were unrelated with yield. Pods m^-2 also appeared related with yield, although not as closely as seed m^-2 (Tables 2 and 3). Observations made in Tables 2 and 3 were confirmed by correlation and path analyses (Tables 4 and 5). In 1998, yield on both phenotypic and genotypic levels was much more strongly influenced by seed m^-2 than seed size (Table 4). Seed m^-2 accounted for 85 and 72% (r² values) of the variability in yield on the phenotypic and genotypic levels, respectively. In contrast, seed size accounted for only 5 and 7% of the variability in the same comparison. Reflecting the correlation analyses, the direct phenotypic and genotypic path effects of seed m^-2 on yield were about two to three times greater than those for seed size (Table 4). Seed m^-2 had little negative indirect effect on yield through seed size on either the phenotypic or genotypic levels. In contrast, whatever positive direct path effect seed size had on seed yield was partially reversed by a negative indirect effect of seed size on yield through seed number (i.e., yield component compensation).

Seed m^-2 vs. Seed per Pod and Pods m^-2
For both phenotypic and genotypic levels in 1998, pods m^-2 showed much greater influence over seed m^-2 than did seed per pod (Table 4). Seed per pod was not positively correlated with seed m^-2 on either level, whereas pods m^-2 accounted for 86 and 85% (r² values) of the variation in seed m^-2 for phenotypic and genotypic levels, respectively. The direct path coefficient for pods m^-2 on seed m^-2 was almost three times greater than that for seed per pod for both levels. Pods m^-2 demonstrated only a small negative indirect effect on seed m^-2 through seed per pod, whereas any positive direct path effect of seed per pod on seed m^-2 was nullified by a large negative indirect path effect of seed per pod on seed m^-2 through pods m^-2 (i.e., yield component compensation). These effects were manifested on both phenotypic and genotypic levels.

Yield component relationships in 1999 were very similar to 1998. Pods m^-2 was again the dominant factor affecting seed m^-2 (Table 5). Seed per pod was not significantly correlated with pods m^-2 on either phenotypic or genotypic levels, whereas pods m^-2 accounted for 74 and 76% (r² values) of the variability in seed m^-2 on the phenotypic and genotypic levels, respectively. Direct path phenotypic and genotypic effects for pods m^-2 on seed m^-2 were twice as great as those for seed per pod. Furthermore, the positive direct path effect of seed per pod on seed m^-2 was nullified by a large negative indirect path effect of seed per pod through pods m^-2 on seed m^-2 for both phenotypic and genotypic levels (i.e., yield component compensation). In contrast, negative indirect path effects for pods m^-2 through seed per pod on seed m^-2 were small.

Pods per reproductive node and reproductive node m^-2 were obtained only in 1999 (Table 5). On the phenotypic level, both yield components contributed equally to increased pods m^-2, as shown by similar r values, direct path effects, and indirect path effects. However, on the more important genotypic level, pods per reproductive node demonstrated greater influence (r² = 0.72) over pods m^-2 than did reproductive node m^-2 (r² = 0.12). The direct path effect of pods per reproductive node on pods m^-2 was almost twice as great as that for reproductive node m^-2 with only a small negative indirect path effect of pods per reproductive node through reproductive node m^-2 on pods m^-2.

Argentina Study: Yield and Yield Components
Significant cultivar effects occurred for yield and all yield components. Top-yielding cultivars at the Argentina location were ‘FACA502’ (MG V), ‘DM57’ (MG V), ‘A6401’ (MG VI), ‘Haskell’ (MG VII), ‘DM48’ (MG IV), ‘CAM64’ (MG VI), ‘A6445’ (MG VI), ‘ACA560’ (MG V), ‘MAR55RR’ (MG V), ‘P661G’ (MG VI), ‘K1014G’ (MG VI), and ‘HM360RR’ (MG VI) (Table 6). Among the various yield components, seed m^-2, pods m^-2, and reproductive node m^-2 showed the greatest association with yield, whereas seed size, seed per pod, and pods per reproductive node appeared unrelated with yield. These observations were supported by correlation and path analyses (Table 7). Yield was highly significantly correlated with seed m^-2 for both phenotypic and genotypic levels, whereas seed size was not positively correlated with yield for either level. On the phenotypic level, the direct path effect for seed m^-2 on yield was much greater than that for seed size and the negative indirect path effect for seed m^-2 through seed size on yield was very small. The genotypic direct path effect of seed m^-2 on yield was greater than that for seed size (1.52 vs. 0.98). The positive direct path effect of seed size was completely nullified by a large (-1.19) negative indirect path effect of seed size through seed m^-2 on yield. Seed m^-2 also had a negative indirect path effect through seed size (-0.76) on yield, but it was not great enough to negate the positive genotypic effect of seed m^-2 on yield.

In contrast to the Baton Rouge study, reproductive node m^-2 affected pods m^-2 more than did pods per reproductive node (Tables 5 and 7) for both phenotypic and genotypic levels. Both phenotypic and genotypic correlations between reproductive node m^-2 and pods m^-2 were highly significant, whereas correlations between pods per reproductive node and pods m^-2 were nonsignificant or slightly negatively significant (Table 7). Phenotypic and genotypic direct path effects for reproductive node m^-2 on pods m^-2 were over twice as great as those compared with pods per reproductive node. Furthermore, phenotypic and genotypic negative indirect path effects for reproductive node m^-2 through pods per reproductive node on pods m^-2 were small, whereas any phenotypic or genotypic positive direct effects of pods per reproductive node on pods m^-2 were negated by negative indirect effects of pods per reproductive node through reproductive node m^-2 on pods m^-2 (Table 7).

	DISCUSSION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSION REFERENCES

 
Consistent with previous studies conducted at Baton Rouge (Board, 2002; Board et al., 1996), yield tended to increase with maturity group. Fifty percent of the MG VI cultivars were in the top-yielding group in either one or both years of the study. In contrast, only 18% of MG V and 0% of MG IV cultivars were in the top-yielding group in either one or both years. When cultivar means were averaged across years and within MG, MG VI cultivars produced a yield of 2325 kg ha^-1, compared with 2026 kg ha^-1 for MG V and 2018 for MG IV. In contrast, results from the Argentina study indicated no relationship between MG and yield. Top-yielding cultivars in that study randomly represented MG IV through VII. Despite this difference in results, phenotypic and genotypic correlation and path analysis patterns were similar between the two sites. For purposes of identifying indirect selection criteria for top-yielding cultivars, analysis at the genotypic level gives a clearer understanding of what yield components to use as indirect selection criteria, since it identifies genetic relationships only, without the confounding influences of environmental and cultural practices.

On the genotypic level, seed m^-2 clearly met the three criteria specified in Materials and Methods for acceptance as an indirect selection criterion for top-yielding cultivars at late planting dates (Tables 4, 5, and 7); that is: (i) strong positive genotypic correlation between the trait and yield; (ii) large positive direct path effects on yield; and (iii) small negative indirect effects on yield through seed size (i.e., lack of yield component compensation). Results were similar for both Louisiana and Argentina locations. Results in the current study are similar to those reported by Lal and Haque (1971) in India, but contrast with those of Adams (1967), Hartwig and Edwards (1970), and Board et al. (1997)( 1999). Different results compared with previous studies are probably due to the greater number of cultivars and locations involved in this study. Although determination of seed m^-2 may appear to be a time-consuming and laborious task, the method can be rapid and accurate. Seed number is determined at about the R6 stage before rapid seed filling (Pigeaire et al., 1986). Thus, between the R6 and R7 stages, a 0.5-m² sample can be taken from a small one-row plot. Pods m^-2 can be determined by counting out a random 50-pod sample and using weight ratios between the 50-pod sample and the entire sample to calculate total pod number; and then multiplying by 2 to determine pods m^-2. Seed per pod can be determined by counting the bulges in the locules of the 50-pod sample. Consequently, seed m^-2 can then be determined by multiplying seed per pod x pods m^-2.

Results from the genotypic secondary level of yield component analysis (pods m^-2 and seed per pod affecting seed m^-2) clearly indicated that pods m^-2 exerted greater influence over seed m^-2 than did seed per pod (Tables 4, 5, and 7). Increased pods m^-2 resulted in greater seed m^-2 and compensation between pods m^-2 and seed per pod was small. These results indicate that pods m^-2 could also be used as an indirect selection criterion for top-yielding cultivars. Data presented in Tables 2, 3, and 6 demonstrated that pods m^-2 was somewhat less accurate at identifying top-yielding cultivars as was seed m^-2. In the 1998 Baton Rouge study, seed m^-2 identified all three top-yielding cultivars while pod m^-2 identified only one. However, in the 1999 Baton Rouge study seed m^-2 identified four of the six top-yielding cultivars, while pods m^-2 identified five. In the 1999 Argentina study, eight of the top 12 cultivars were identified as top-yielding by seed m^-2, while pods m^-2 identified six. Determination of pods m^-2 is less time-consuming compared with seed m^-2, and the sacrifice in accuracy for greater efficiency may be acceptable.

Yield components controlling pods m^-2 differed between sites (Tables 5 and 7). At the Baton Rouge site, pods per reproductive node, for both phenotypic and genotypic levels, was the major factor controlling pods m^-2. These results are supported by previous research at Baton Rouge (Board et al., 1997, 1999). Yield component compensation between pods per reproductive node and reproductive node m^-2 was small. Despite its importance in controlling pods m^-2, pods per reproductive node did not show promise as an indirect selection criterion for high-yielding cultivars (Table 3). In contrast to the Baton Rouge site, reproductive node m^-2 was the dominant yield component affecting pods m^-2 in Argentina (Table 7). Little yield component compensation occurred between reproductive node m^-2 and pods per reproductive node in affecting pods m^-2. Reproductive node m^-2 identified six of 12 top-yielding cultivars. Because pods m^-2 did not demonstrate a consistent pattern of control by either pods per reproductive node or reproductive node m^-2 between Argentina and Louisiana, it was concluded that across sites, either seed m^-2 or pods m^-2 would be more acceptable indirect selection criteria for top-yielding cultivars at late planting dates.

Explanations for why pods m^-2 was controlled by pods per reproductive node among Louisiana cultivars and by reproductive node m^-2 among Argentinean cultivars are not obvious. However, a possible reason could be the phenological differences between the two locations. Although the total growing seasons (emergence to R7) were similar between locations, days to R5 for Argentinean cultivars were longer compared with cultivars grown in Louisiana. Soybean planted in early July in Louisiana (a date comparative to the planting date for the Argentina study) will typically have about 52, 55, and 56 d between emergence and R5 for MG V, VI, and VII cultivars, respectively. In contrast, days to R5 for the Argentina study were 65, 67, and 68 d for MG V, VI, and VII cultivars, respectively. Longer days to R5 for the Argentina study were probably induced by the longer daylengths (10–15 min., Argentinean Meteorological Dep. website) during the first month of the summer growing season compared with Baton Rouge. Even slight increases in daylength during this growth period have been shown to increase days to R5 (Board and Settimi, 1986). With fewer days to R5 for the Baton Rouge vs. Argentina location resulting in less time for vegetative dry matter accumulation and node development, cultivars having greater pods per reproductive node would have more of a yield advantage at Baton Rouge.

	CONCLUSION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSION REFERENCES

 
Across a range of 26 cultivars grown for 2 yr at Baton Rouge, LA, and 27 cultivars grown for 1 yr at Los Oliveros, Santa Fe Province, Argentina, yield components demonstrating the greatest influence over yield on both phenotypic and genotypic levels were seed m^-2 and pods m^-2. Neither yield component demonstrated compensation with its counterpart; that is, increased seed m^-2 on either phenotypic or genotypic levels did not result in a corresponding decrease in seed size and increased pods m^-2 on either phenotypic or genotypic levels did not result in a corresponding decrease in seed per pod. In contrast, genotypic increases in seed size or seed per pod were compensated for by decreases in seed m^-2 and pods m^-2, respectively. Seed m^-2 or pods m^-2 could be used as indirect selection criteria for top-yielding cultivars at late planting dates. Seed m^-2 is more accurate, but is also more time-consuming. In summary, indirect selection criteria can be used in lieu of the traditional combine-harvested plot-yield method to identify top-yielding cultivars at late planting dates.

	NOTES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSION REFERENCES

 
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.

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