Seed Size In Soybean Research Articles

Final Seed Size in Soybean Is Determined during Mid-Seed Filling Stage

Potential seed size in many crops including major cereals is determined during early seed developmental stages. However, the stage at which final seed size is determined in soybean (Glycine max [L.] Merr.) under field conditions is not known. Hence, this study was conducted with the main objective to assess seed growth dynamics under controlled and increased assimilate supply conditions during different seed filling periods using two maturity group soybean cultivars. Treatments consisted of a control, and a de-podding (pod removal) treatment at weekly intervals after the beginning of the seed filling stage up until physiological maturity. Only four to six pods were maintained per plant in de-podding treatments in order to provide a higher assimilate supply to remaining seeds. A higher assimilate supply until around the mid-seed filling stage increased unit seed weight in both the cultivars, indicating that the maximum seed size in soybean crops is determined during the mid-seed filling stage. The increase in seed weight under higher assimilate supply was associated with an extended seed filling duration and a uniform seed filling rate over a longer period. The results also suggested a possible source limitation during the early seed filling stage in soybean, indicating opportunities to improve its yield using supplemental inputs and other improved crop cultivation practices.

Construction of Genetic Map and QTL Mapping for Seed Size and Quality Traits in Soybean (Glycine max L.).

Soybean (Glycine max L.) is the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean yield and quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) mapping for yield and quality traits, as well as for the identification of mining-related candidate genes, is of great significance for the molecular breeding and understanding the genetic mechanism. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiangchun 2 and Yushuxian 2 were selected as the mapping population to construct a molecular genetic linkage map. A genetic map containing 445 SSR markers with an average distance of 5.3 cM and a total length of 2375.6 cM was obtained. Based on constructed genetic map, 11 traits including hundred-seed weight (HSW), seed length (SL), seed width (SW), seed length-to-width ratio (SLW), oil content (OIL), protein content (PRO), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA), palmitic acid (PA), stearic acid (SA) of yield and quality were detected by the multiple- d size traits and 113 QTLs related to quality were detected by the multiple QTL model (MQM) mapping method across generations F2, F2:3, F2:4, and F2:5. A total of 71 QTLs related to seed size traits and 113 QTLs related to quality traits were obtained in four generations. With those QTLs, 19 clusters for seed size traits and 20 QTL clusters for quality traits were summarized. Two promising clusters, one related to seed size traits and the other to quality traits, have been identified. The cluster associated with seed size traits spans from position 27876712 to 29009783 on Chromosome 16, while the cluster linked to quality traits spans from position 12575403 to 13875138 on Chromosome 6. Within these intervals, a reference genome of William82 was used for gene searching. A total of 36 candidate genes that may be involved in the regulation of soybean seed size and quality were screened by gene functional annotation and GO enrichment analysis. The results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean.

Understanding the Molecular Regulatory Networks of Seed Size in Soybean.

Soybean being a major cash crop provides half of the vegetable oil and a quarter of the plant proteins to the global population. Seed size traits are the most important agronomic traits determining the soybean yield. These are complex traits governed by polygenes with low heritability as well as are highly influenced by the environment as well as by genotype x environment interactions. Although, extensive efforts have been made to unravel the genetic basis and molecular mechanism of seed size in soybean. But most of these efforts were majorly limited to QTL identification, and only a few genes for seed size were isolated and their molecular mechanism was elucidated. Hence, elucidating the detailed molecular regulatory networks controlling seed size in soybeans has been an important area of research in soybeans from the past decades. This paper describes the current progress of genetic architecture, molecular mechanisms, and regulatory networks for seed sizes of soybeans. Additionally, the main problems and bottlenecks/challenges soybean researchers currently face in seed size research are also discussed. This review summarizes the comprehensive and systematic information to the soybean researchers regarding the molecular understanding of seed size in soybeans and will help future research work on seed size in soybeans.

Performance of soybean plants in response to seed size and stressful and non-stressful environments

The size of soybean seeds can influence the germination process and seedling growth. Therefore, this study aimed to evaluate the size of soybean seeds during germination and seedling growth under non-stressful conditions and salt and water stress. The design used was completely randomized, arranged in a 2 × 3 × 3 factorial scheme, with two soybean cultivars [BMX Extra IPRO (74i78RSF IPRO) and BMX Desafio RR (8473 RSF)], three seed size classes (5.75; 6.5 and 6.5 mm) and three osmotic stress treatments [control (non-stressful conditions), salt or water stress]. In the control treatment, distilled water was used, and water and salt stresses were used PEG and NaCl solutions with osmotic pressure of –0.3 MPa, respectively. First germination count, germination, radicle length, seedling length, shoot dry matter, and root dry matter were measured. Under non-stressful or stressful environments, soybean seed size does not affect germination rate and seedling growth for the cultivar BMX Extra IPRO. For the BMX Desafio RR cultivar, the larger seeds are more adapted to the saline stress condition. Regardless of seed size and soybean cultivar, water stress reduced germination and seedling growth rate.

CRISPR/Cas9-Mediated Targeted Mutagenesis of GmEOD1 Enhances Seed Size of Soybean

Seed size is a critical agronomic trait that influences the yield and appearance quality of soybeans, making it a primary breeding objective with significant economic value. While the molecular mechanisms that regulate soybean seed size remain largely unknown, several functional molecular targets have been applied in breeding to create larger grain size materials. In this study, we utilized the CRISPR/Cas9 system to induce the targeted mutagenesis of GmEOD1, which encodes the E3 ubiquitin ligase. The resulting homozygous soybean mutant of GmEOD1 exhibited larger seed size and 100-seed weight, with no significant change in the average seed weight per plant. The sum of crude protein and oil content increased significantly in mutants while fatty acid composition remained unchanged. We identified six haplotypes among 156 soybean cultivars, with Hap1 and Hap2 representing the majority of cultivars with relatively higher 100-seed weight, suggesting that sequence variations of GmEOD1 may correlate with seed weight. Transcriptomic analysis across five stages of seed development revealed that stages one–three mainly focused on cell cycle, growth, wall synthesis and modification, photosynthesis, and sugar metabolism; promoting cell growth, reproduction, and carbon accumulation; and providing key intermediates for substance synthesis. Stages four–five focused on polysaccharide catabolism, xylan metabolism, and nutrient pool activity, promoting the accumulation of dry matter, such as sugars, proteins, and lipids in seeds. Weighted gene co-expression network analysis (WGCNA) of modules related to seed size revealed 13 hub genes involved in seed development regulation. This study provides a valuable theoretical basis and excellent opportunities for genetic editing of germplasm cells with subsequent molecular soybean seed size breeding, facilitating easier seed selection to improve soybean quality.

An enhancing effect attributed to a nonsynonymous mutation in SOYBEAN SEED SIZE 1, a SPINDLY-like gene, is exploited in soybean domestication and improvement.

Soybean (Glycine max) was domesticated from its wild relative Glycine soja. One-hundred-seed weight is one of the most important domesticated traits determining soybean yield; however, its underlying genetic basis remains elusive. We characterized a soybean seed size 1 (sss1) mutant featuring large seeds compared to its wild-type background. Positional cloning revealed that the candidate gene GmSSS1 encoded a SPINDLY homolog and was co-located in a well-identified quantitative trait locus (QTL)-rich region on chromosome 19. Knocking out GmSSS1 resulted in small seeds, while overexpressing GmSSS1/Gmsss1 induced large seeds. Modulating GmSSS1/Gmsss1 in transgenic plants can positively influence cell expansion and cell division. Relative to GmSSS1, one mutation leading to an E to Q substitution at the 182nd residue in Gmsss1 conferred an enhancing effect on seed weight. GmSSS1 underwent diversification in wild-type and cultivated soybean, and the alleles encoding the Gmsss1-type substitution of 182nd -Q, which originated along the central and downstream parts of the Yellow River, were selected and expanded during soybean domestication and improvement. We cloned the causative gene for the sss1 mutant, which is linked with a seed weight QTL, identified an elite allele of this gene for increasing seed weight, and provided new insights into soybean domestication and breeding.

Soybean seed size: how does it affect crop development and physiological seed quality?

Abstract: The size of soybean seeds needs further study because its relationships with physiological quality, field establishment, and yield are controversial. The aim of this study was to evaluate the effects of seed size on soybean establishment and seed physiological quality. In the field, a 2x3x3 factorial design was used, with two cultivars (M 5947 IPRO and 59HO124 IPRO), three seed sizes (5.5, 6.0, and 6.5 mm), and three sowing densities (280,000, 320,000, and 360,000 plants.ha-1). Agronomic traits and grain yield were evaluated. After harvest, only seeds from plots with a population of 320,000 plants were classified by size using circular sieves with 5.5-mm, 6.0-mm, 6.5-mm, and 7.0-mm mesh sizes. For the evaluation of physiological quality, a 2x4 factorial design was applied, with two cultivars and four seed sizes. Germination, seedling emergence, accelerated aging, seedling dry matter, and emergence speed index were evaluated. Smaller seeds gave rise to shorter plants with a lower first pod insertion height. Larger seeds had higher physiological quality. The M 5947 IPRO cultivar showed better seed performance and quality.

Simultaneous changes in seed size, oil content and protein content driven by selection of SWEET homologues during soybean domestication.

Soybean accounts for more than half of the global production of oilseed and more than a quarter of the protein used globally for human food and animal feed. Soybean domestication involved parallel increases in seed size and oil content, and a concomitant decrease in protein content. However, science has not yet discovered whether these effects were due to selective pressure on a single gene or multiple genes. Here, re-sequencing data from >800 genotypes revealed a strong selection during soybean domestication on GmSWEET10a. The selection of GmSWEET10a conferred simultaneous increases in soybean-seed size and oil content as well as a reduction in the protein content. The result was validated using both near-isogenic lines carrying substitution of haplotype chromosomal segments and transgenic soybeans. Moreover, GmSWEET10b was found to be functionally redundant with its homologue GmSWEET10a and to be undergoing selection in current breeding, leading the the elite allele GmSWEET10b, a potential target for present-day soybean breeding. Both GmSWEET10a and GmSWEET10b were shown to transport sucrose and hexose, contributing to sugar allocation from seed coat to embryo, which consequently determines oil and protein contents and seed size in soybean. We conclude that past selection of optimal GmSWEET10a alleles drove the initial domestication of multiple soybean-seed traits and that targeted selection of the elite allele GmSWEET10b may further improve the yield and seed quality of modern soybean cultivars.

High-Resolution Mapping in Two RIL Populations Refines Major "QTL Hotspot" Regions for Seed Size and Shape in Soybean (Glycine max L.).

Seed size and shape are important traits determining yield and quality in soybean. However, the genetic mechanism and genes underlying these traits remain largely unexplored. In this regard, this study used two related recombinant inbred line (RIL) populations (ZY and K3N) evaluated in multiple environments to identify main and epistatic-effect quantitative trait loci (QTLs) for six seed size and shape traits in soybean. A total of 88 and 48 QTLs were detected through composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively, and 15 QTLs were common among both methods; two of them were major (R2 > 10%) and novel QTLs (viz., qSW-1-1ZN and qSLT-20-1K3N). Additionally, 51 and 27 QTLs were identified for the first time through CIM and MCIM methods, respectively. Colocalization of QTLs occurred in four major QTL hotspots/clusters, viz., “QTL Hotspot A”, “QTL Hotspot B”, “QTL Hotspot C”, and “QTL Hotspot D” located on Chr06, Chr10, Chr13, and Chr20, respectively. Based on gene annotation, gene ontology (GO) enrichment, and RNA-Seq analysis, 23 genes within four “QTL Hotspots” were predicted as possible candidates, regulating soybean seed size and shape. Network analyses demonstrated that 15 QTLs showed significant additive x environment (AE) effects, and 16 pairs of QTLs showing epistatic effects were also detected. However, except three epistatic QTLs, viz., qSL-13-3ZY, qSL-13-4ZY, and qSW-13-4ZY, all the remaining QTLs depicted no main effects. Hence, the present study is a detailed and comprehensive investigation uncovering the genetic basis of seed size and shape in soybeans. The use of a high-density map identified new genomic regions providing valuable information and could be the primary target for further fine mapping, candidate gene identification, and marker-assisted breeding (MAB).

Determination of the genetic architecture of seed size and shape via linkage and association analysis in soybean (Glycine max L. Merr.)

Seed-size traits, which are controlled by multiple genes in soybean, play an important role in determining seed yield, quality and appearance. However, the molecular mechanisms controlling the size of soybean seeds remain unclear, and little research has been done to investigate these mechanisms. In this study, we performed a genetic analysis to determine the genetic architecture of soybean seed size and shape via linkage and association analyses. We used 184 recombinant inbred lines (RILs) and 219 cultivated soybean accessions to evaluate seed length, seed width and seed height as seed-size traits, and their ratios of these values as seed-shape traits. Our results showed that all six traits had high heritability ranging from 92.46 to 98.47%. Linkage analysis in the RILs identified 12 quantitative traits loci (QTLs), with five of these QTLs being associated with seed size, five with seed shape and two with the two first principal components of our principal component analysis (PCA). Association analysis in the 219 accessions detected 41 single nucleotide polymorphism (SNP)-trait associations, with 20 of these SNPs being associated with seed-size traits, seven with seed-shape traits and 14 with the two first principal components of our PCA. This analysis reveals that seed-size and seed-shape may be controlled by different genetic factors. Our results provide a greater understanding of phenotypic structure and genetic architecture of soybean seed, and the QTLs detected in this study form a basis for future fine mapping, quantitative trait gene cloning and molecular breeding in soybean.

Timing of Fruit Initiation and Seed Size in Soybean

There is substantial variation in seed size (weight per seed) among the seeds produced by a soybean (Glycine max [L.] Merrill) plant. Five field experiments with two cultivars were conducted near Lexington, Kentucky, United States (38°N), to test the hypothesis that variation in seed size was related to the time of fruit initiation during the flowering period. All fruits ≥ 10 mm long on a plant were marked at three-day intervals, harvested at maturity, and separated by the time of marking before seed size was determined. There was substantial variation in seed size, but the time of fruit initiation accounted for only a small proportion of the variation. Fruits that initiated growth at different times often produced the same sized seeds, and there was always substantial variation in seed size among fruits initiated at the same time. The data provide little support to the hypothesis that seed size is related to the timing of fruit initiation. The data suggest that there may be several mechanisms responsible for the variation in seed size on soybean plants.

Effects of Soybean Seed Size on Weed Competition

Organic soybean [Glycine max (L.) Merr.] producers must rely on various, nonherbicidal tactics for weed management. Increased soybean seed size may be one method to increase the competitiveness of the soybean canopy. Soybean varieties Hutcheson, NC‐Roy, and NC‐Raleigh were separated into four or five seed size classes. Seed sizes ranged from 5.15 to 6.75 mm diam. This range of seed size resulted in seed weights of 10 to 20 g per 100 seed. Each seed size class was grown in weedy and weed‐free conditions at Kinston, NC during 2007 and 2008 and at Plymouth, NC during 2008. Redroot pigweed (Amaranthus retroflexus L.) overseeding was done to create uniform weed densities. Increasing soybean seed size resulted in greater soybean canopy coverage with the greatest effect at 3 weeks after emergence (WAE) (P < 0.001, P = 0.003, and P < 0.001 at Kinston 2007, Kinston 2008, and Plymouth 2008, respectively) compared with 5 WAE (P = 0.02, P = 0.07, and P = 0.02 at Kinston 2007, Kinston 2008, and Plymouth 2008, respectively). Plants from larger seed sizes had more soybean biomass in all sites when grown with weeds, but in only two sites under weed‐free conditions. Larger seed size improved soybean competitiveness by increasing petiole length and plant height. In the two sites with higher weed population densities, planting larger soybean seed reduced weed biomass at 7 WAE. Results suggest that use of larger planting seed may improve weed control in organic soybean production.

Developmental Genetic Analysis of Seed Size in Soybean ( Glycine max)

Seed size is one of the important factors of soybean [ Glycine max (L.) Merrill] yield. There have been lots of reports about genetic effects and physiology—ecological researches on seed size, but the genetic behaviors of genes during seeds development were rarely discussed. Analysis of main genetic effects for fresh seed size (FSS) and dry seed size (DSS) of soybean was conducted with diallel cross data by using a seed genetic model. Analyses of unconditional and conditional variances and correlations were used to evaluate the developmental behavior of soybean. The phenotypic means of FSS and DSS in soybean at eight stages among three generations reached the highest value at 9/6 and 9/13, respectively. The means of FSS decreased dramatically after 9/6, but the means of DSS maintained relatively stable tendency at corresponding periods. The unconditional variance analysis showed that FSS and DSS were controlled by embryo, cytoplasmic and maternal effects in the whole growth period. Genetic effects due to cytoplasmic and maternal effects were relatively important for FSS and DSS at most of the growth periods. Conditional variance analysis showed that genes from different genetic system expressed discontinuously in the whole growth period. The net genetic effects due to cytoplasmic and maternal plant on FSS and DSS were larger than those of embryo effects at most of the growth periods. Different genetic system can affect the relationship of various stages to mature solely or simultaneously. Embryo additive effects at 8/16, embryo dominance effects at 8/9 and 8/16, maternal plant dominance effects at 8/2 and 8/16 could ultimately affect the performance of FSS at maturing stage. Embryo additive effects at 8/2 and 9/13, cytoplasm effects at 8/9, maternal plant dominance effects at 8/2 could ultimately affect the performance of DSS.

Quantitative Trait Loci for Seed Protein and Oil Concentration, and Seed Size in Soybean

Soybean [Glycine max (L.) Merr.] is an important crop because of its high oil and protein concentration. However, there is an inverse relationship between seed protein and oil concentration, making it difficult to improve both traits simultaneously. Molecular breeding may be helpful to facilitate a balanced accumulation of desirable alleles. The objective of this study was to identify quantitative trait loci (QTL) governing soybean protein, oil and seed size. To achieve this objective, 101 F6–derived recombinant inbred lines (RIL) from a population developed from a cross of N87‐984‐16 × TN93‐99 were used. Heritability estimates on an entry mean basis for protein and oil concentrations, and seed size were 0.66, 0.54, and 0.71, respectively. A total of 585 simple sequence repeat (SSR) molecular genetic markers were screened and 94 were polymorphic in the RIL. Single factor ANOVA was used to identify candidate QTL, which were then confirmed by composite interval mapping. One novel molecular marker (Satt570) on molecular linkage group (MLG) G associated with a protein QTL was detected. Novel molecular markers (Satt274, Satt420, and Satt479) located on MLG D1b, O, and O respectively and a previously reported marker (Satt317) located on MLG H were associated with oil QTL in this study. Molecular markers Satt002 (MLG D2) and Satt184 (MLG D1a) associated with seed size QTL were verified whereas Satt147 (MLG D1a) was novel. The individual QTL explained 20.2, 9.4‐15, and 10 to 16.5% of the phenotypic variation for protein and oil concentrations, and seed size, respectively. Thus, we identified major loci for improving soybean seed quality.

Molecular Marker Analysis of Seed Size in Soybean

Seed size is an important attribute of soybean [Glycine max (L.) Merr.] for some food uses. The objectives of this study were to identify simple-sequence-repeat (SSR) markers associated with quantitative trait loci for seed size (SSQTL) and to compare the effectiveness of phenotypic selection and marker-assisted selection for seed size among individual F2 plants. Three small-seeded lines were crossed to parents with normal seed size to form three two-parent populations. The parents of the populations were screened with 178 SSR markers to identify polymorphism. Population 1 (Pop 1) had 75 polymorphic SSR markers covering 1306 centimorgans (cM), Pop 2 had 70 covering 1143 cM, and Pop 3 had 82 covering 1237 cM. Seed size of each population was determined with 100 F2 plants grown at Isabela, Puerto Rico, and their F2–derived lines grown in two replications at three environments. Single-factor analysis of variance and multiple regression were used to determine significant marker-SSQTL associations. Population 1 had 12 markers that individually accounted for 8.1 to 14.9% of the variation for seed size combined across environments, Pop 2 had 16 markers that individually accounted for 7.8 to 36.5% of the variation, and Pop 3 had 22 markers that individually accounted for 8.6 to 28.8% of the variation. Three marker loci that had significant SSQTL associations in this study also were significant in previous research, and 13 markers had unique SSQTL associations. The relative effectiveness of phenotypic and marker-assisted selection among F2 plants varied for the three populations. Averaged across the three populations, phenotypic selection for seed size was as effective and less expensive than marker-assisted selection.

Molecular Marker Analysis of Seed Size in Soybean

Seed size is an important attribute of soybean [Glycine max (L.) Merr.] for some food uses. The objectives of this study were to identify simple‐sequence‐repeat (SSR) markers associated with quantitative trait loci for seed size (SSQTL) and to compare the effectiveness of phenotypic selection and marker‐assisted selection for seed size among individual F2 plants. Three small‐seeded lines were crossed to parents with normal seed size to form three two‐parent populations. The parents of the populations were screened with 178 SSR markers to identify polymorphism. Population 1 (Pop 1) had 75 polymorphic SSR markers covering 1306 centimorgans (cM), Pop 2 had 70 covering 1143 cM, and Pop 3 had 82 covering 1237 cM. Seed size of each population was determined with 100 F2 plants grown at Isabela, Puerto Rico, and their F2–derived lines grown in two replications at three environments. Single‐factor analysis of variance and multiple regression were used to determine significant marker‐SSQTL associations. Population 1 had 12 markers that individually accounted for 8.1 to 14.9% of the variation for seed size combined across environments, Pop 2 had 16 markers that individually accounted for 7.8 to 36.5% of the variation, and Pop 3 had 22 markers that individually accounted for 8.6 to 28.8% of the variation. Three marker loci that had significant SSQTL associations in this study also were significant in previous research, and 13 markers had unique SSQTL associations. The relative effectiveness of phenotypic and marker‐assisted selection among F2 plants varied for the three populations. Averaged across the three populations, phenotypic selection for seed size was as effective and less expensive than marker‐assisted selection.

Heritability of Seed Shape and Seed Size in Soybean

Round seeds are desirable for food‐type soybean [Glycine max (L.) Merr.] cultivars and an understanding of the heritability of seed shape would benefit the development of these cultivars. The objectives of this study were to estimate heritability of seed shape and seed size by parent‐offspring regression, parent‐offspring correlation, and realized heritability, and to determine the correlation between seed size and seed shape in germplasm ranging in seed size. From parents differing in seed shape, four populations (three oilseed‐type and one small‐seeded natto‐type) were generated. A total of 694 random F2 plants, grown in 1994 at Ottawa, ON, and their resulting F2:3 progeny, grown in unreplicated rows in 1995 at Ottawa, were used for analysis. Seed shape was quantified by two aspect ratios (the ratio of minimum to maximum seed diameter), each calculated from a different seed orientation with digital image analysis. Seed size (cross‐sectional area) was measured in the same two orientations. Estimates of heritability for seed shape varied across the four populations; parent‐offspring regression coefficients ranged from 0.55 to 0.75, parent‐offspring correlation coefficients ranged from 0.49 to 0.76, and realized heritability estimates ranged from 0.59 to 0.79. Estimates of heritability for seed size ranged from 0.19 to 0.56 across populations. There were significant positive correlations between the aspect ratios calculated from the two different orientations; therefore, selection for round shape in one orientation would result in indirect selection for round shape in the other orientation. There was no consistent association between seed shape and seed size. In the natto population, <5% of the F3 lines were smaller or rounder than the smallest‐ roundest‐seeded parent. Heritability estimates indicate that plant breeders can select for round seed shape, on a single plant basis, in early generations of populations ranging in seed size.

Pink Flower Color Associated with Increased Protein and Seed Size in Soybean

Most soybean [Glycine max (L.) Merr.] cultivars and plant introductions have either purple (Wl) or white (wl) flowers. Pink (wp) flower color results when the homozygous wp alleles are combined with Wl. This study was conducted to determine the effect of pink flower color on agronomic traits in soybean. Pink and near‐isogenic purple‐flowered lines were derived from an F4 plant. Seven homozygous pink‐flowered, three homozygous purple‐flowered, and two lines segregating for pink and purple flower color were evaluated at three locations in Illinois for 2 yr. When pink‐flowered lines were compared to purple‐flowered lines no differences were found for yield, maturity, height, lodging, or seed quality, while significant (P < 0.05) differences were found for seed weight, protein, and oil concentration. Pinkflowered lines averaged 22% higher in seed weight, 4% higher in protein, and 3% lower in oil compared to the purple‐flowered lines. The pink flower trait represents unique germplasm in soybean that can be used in the development of high yielding cultivars with increased seed protein.

Recurrent Selection for Seed Size in Soybean: III. Indirect Effects on Seed Composition

In soybean [Glycine max (L.) Merr.], correlations between seed yield and seed composition are often significant, while correlations between seed size (a component of yield) and seed composition are usually low. In addition, selection for changes in seed composition have often resulted in seed yield changes but usually not changes in seed size. The objective of this research was to examine the indirect effects of recurrent selection for increased seed size on protein and oil concentration in a random mating population that segregates for male sterility. The intermating population N79‐1500 was divided into three subpopulations designated SS1, SS2, and SS3. Male‐slerile (MS) plants were selected for large seed size through four cycles in SS1 and SS2 and three cycles in SS3. Parental composites of each cycle were tested at four locations in North Carolina in 1987 and 1988. In MS seeds of SS1 and SS2, the concentration of protein decreased linearly across cycles of selection. Oil concentration increased in MS seeds of SS1. There was no change in protein or oil concentration in MS seeds of SS3. In male‐fertile (MF) seeds, protein decreased and oil increased in SS1 and SS2, while SS3 was unchanged for both constituents. On a weight per seed basis, there was a linear increase in protein and oil concentration of both MS and MF seeds of all three subpopulations. Total protein (protein concentration × seed yield) increased only SS3 while total oil (oil concentration × seed yield) increased in SS2 and SS3. The identification of a subpopulation (SS3), which did not decrease significantly in protein or oil percentage as seed yield increased and therefore increased in total protein, suggests that selection as practiced in this study can be useful to improve these important traits.

Recurrent Selection for Seed Size in Soybean: II. Indirect Effects on Seed Growth Rate

Seed growth rate (SGR) and effective filling period (EFP) have been associated with both seed size and seed yield in soybean [Glycine max (L.) Merr.]. Three subpopulations (designated SS1, SS2, and SS3) the intermating population N79‐1500, which segregates for male sterility (ms1ms1), were subjected to recurrent selection for increased seed size of male‐sterile (MS) plants. The objective was to examine the relationship between seed size and development, and their effects on seed yield in the materials derived from selection. After four cycles of selection in SS1 and SS2, and three cycles in SS3, a composite of the parents of each cycle was tested at two locations in North Carolina in 1987 and 1988. A random sample of pods was collected on three dates ≈ 10 d apart from the upper third of the canopy beginning at growth stage R5. The SGR was estimated by linear regression of seed weight on sampling day after 31 August, and EFP was calculated as mature seed size divided by SGR. A significant linear increase in SGR occurred in SS2 and SS3 across cycles of selection. Differences in EFP within and among subpopulations were not significant. The SGR apparently was more important than EFP in producing the increases in seed size of male‐fertile (MF) plants. Seed size increased significantly in all three subpopulations and seed yield increased significantly in SS2 and SS3, but there were no significant differences across cycles of selection for seed number (seeds ha−1).