Traits In Soybean Research Articles

Sample size and genetic divergence: a principal component analysis for soybean traits

Biometric techniques, including the principal component analysis, are commonly applied in soybean genetic divergence studies. However, the sample size used in such studies is often determined empirically, neglecting its potential impact on inference interpretation. Therefore, this study aimed (i) to analyze the response of principal components to the number of plants sampled per experimental unit (plot); (ii) to determine the multivariate representative sample size, and (iii) to construct a methodology to predict sample size for principal components as a function of the precision level defined a priori. Six experiments were performed in two locations in Rio Grande do Sul, Brazil, with three experiments being carried out in each location. All experiments were conducted using a complete randomized block design with three repetitions, and 20 soybean genotypes were utilized, resulting in 360 plots (60 plots per experiment). From each plot, twenty plants were sampled, totaling 7200 plants. A resampling bootstrap procedure was applied to the principal component technique for 10 biometric traits. Posteriorly, the sample size was defined based on predefined precision levels, and power logistic models were parametrized to predict the sample size per experimental unit. The precision of the eigenvalues obtained from the principal component analysis gradually improves with larger sample sizes. Eigenvalues that capture a higher variance tend to require smaller sample sizes for accurate estimation. The fitted models demonstrated satisfactory predictive ability in determining the optimal number of plants per experimental unit, serving as a complementary tool for defining sample size at the desired precision level. Eighteen plants per experimental unit are enough to estimate the eigenvalues of the first two soybean principal components reliably. The developed predictive methodology and sample dimensioning per experimental unit can support future research aimed at identifying divergent genotypes, making them useful tools for soybean plant breeding programs.

An assessment of the interaction between sucrose content and seed quality traits in soybeans

AbstractSoybean (Glycine max [L.] Merr.) cultivars with increased protein and sucrose content are desirable to enhance soybean meal quality; however, the complex interactions between soybean traits, mainly trade‐offs, make the plant breeders’ job challenging because traits cannot simultaneously be enhanced. Information about the interactions of seed carbohydrate composition with other seed traits remains inconclusive and contradictory; thus, this study explored the interactions among soluble carbohydrate content with other seed traits, flowering time, and maturity in a diverse panel of 1096 soybean accessions from the USDA Soybean Germplasm Collection. Trait interactions were explored through phenotypic, additive genetic, and residual correlations. We did not identify traits that can be useful in the indirect selection of sucrose. Additive genetic correlations of sucrose with flowering and maturity time suggest that obtaining cultivars with high sucrose content might be easier in earlier flowering and later maturing cultivars. Sucrose correlations with other seed traits were primarily driven by their additive genetic correlations, which make them more stable, whereas correlations of raffinose with oil and maturity were population and environment specific. The two main obstacles to enhancing soymeal quality are the trade‐offs of protein with sucrose and oil.

The genetic basis of shoot architecture in soybean.

Shoot architecture refers to the three-dimensional body plan of the above ground organs of the plant. The patterning of this body plan results from the tight genetic control of the size and maintenance of meristems, the initiation of axillary growth, and the timing of developmental phase transition. Variation in shoot architecture can result in dramatic differences in plant productivity and/or grain yield due to their effects on light interception, photosynthetic efficiency, response to agronomic inputs, and environmental adaptation. The fine-tuning of shoot architecture has consequently been of great interest to plant breeders, driving the need for deeper understanding of the genes and molecular mechanisms governing these traits. In soybean, the world's most important oil and protein crop, major components of shoot architecture include stem growth habit, plantheight, branch angle, branch number, leaf petiole angle, and the size and shape of leaves. Key genes underlying some of these traits have been identified to integrate hormonal, developmental, and environmental signals modulating the growth and orientation of shoot organs. Here we summarize the current knowledge and recent advances in the understanding of the genetic control of these important architectural traits in soybean.

The domestication-associated L1 gene encodes a eucomic acid synthase pleiotropically modulating pod pigmentation and shattering in soybean

Pod coloration is a domestication-related trait in soybean, with modern cultivars typically displaying brown or tan pods, while their wild relative, Glycine soja, possesses black pods. However, the factors regulating this color variation remain unknown. In this study, we cloned and characterized L1, the classical locus responsible for black pods in soybean. By using map-based cloning and genetic analyses, we identified the causal gene of L1 and revealed that it encodes a hydroxymethylglutaryl-coenzyme A (CoA) lyase-like (HMGL-like) domain protein. Biochemical assays showed that L1 functions as a eucomic acid synthase and facilitates the synthesis of eucomic acid and piscidic acid, both of which contribute to coloration of pods and seed coats in soybean. Interestingly, we found that L1 plants are more prone to pod shattering under light exposure than l1 null mutants because dark pigmentation increases photothermal efficiency. Hence, pleiotropic effects of L1 on pod color and shattering, as well as seed pigmentation, likely contributed to the preference for l1 alleles during soybean domestication and improvement. Collectively, our study provides new insights into the mechanism of pod coloration and identifies a new target for future de novo domestication of legume crops.

Formulation, characterization and impact of an ionically cross linked hydrogel of HPMC and Xanthan gum on growth traits of soybean (Glycine max L.) under irrigation levels

Formulation, characterization and impact of an ionically cross linked hydrogel of HPMC and Xanthan gum on growth traits of soybean (Glycine max L.) under irrigation levels

Comparison of Various Drought Resistance Traits in Soybean (Glycine max L.) Based on Image Analysis for Precision Agriculture.

Drought is being annually exacerbated by recent global warming, leading to crucial damage of crop growth and final yields. Soybean, one of the most consumed crops worldwide, has also been affected in the process. The development of a resistant cultivar is required to solve this problem, which is considered the most efficient method for crop producers. To accelerate breeding cycles, genetic engineering and high-throughput phenotyping technologies have replaced conventional breeding methods. However, the current novel phenotyping method still needs to be optimized by species and varieties. Therefore, we aimed to assess the most appropriate and effective phenotypes for evaluating drought stress by applying a high-throughput image-based method on the nested association mapping (NAM) population of soybeans. The acquired image-based traits from the phenotyping platform were divided into three large categories-area, boundary, and color-and demonstrated an aspect for each characteristic. Analysis on categorized traits interpreted stress responses in morphological and physiological changes. The evaluation of drought stress regardless of varieties was possible by combining various image-based traits. We might suggest that a combination of image-based traits obtained using computer vision can be more efficient than using only one trait for the precision agriculture.

Genome-Wide Association Analysis for Resistance to Coniothyrium glycines Causing Red Leaf Blotch Disease in Soybean.

Soybean is a high oil and protein-rich legume with several production constraints. Globally, several fungi, viruses, nematodes, and bacteria cause significant yield losses in soybean. Coniothyrium glycines (CG), the causal pathogen for red leaf blotch disease, is the least researched and causes severe damage to soybean. The identification of resistant soybean genotypes and mapping of genomic regions associated with resistance to CG is critical for developing improved cultivars for sustainable soybean production. This study used single nucleotide polymorphism (SNP) markers generated from a Diversity Arrays Technology (DArT) platform to conduct a genome-wide association (GWAS) analysis of resistance to CG using 279 soybean genotypes grown in three environments. A total of 6395 SNPs was used to perform the GWAS applying a multilocus model Fixed and random model Circulating Probability Unification (FarmCPU) with correction of the population structure and a statistical test p-value threshold of 5%. A total of 19 significant marker-trait associations for resistance to CG were identified on chromosomes 1, 5, 6, 9, 10, 12, 13, 15, 16, 17, 19, and 20. Approximately 113 putative genes associated with significant markers for resistance to red leaf blotch disease were identified across soybean genome. Positional candidate genes associated with significant SNP loci-encoding proteins involved in plant defense responses and that could be associated with soybean defenses against CG infection were identified. The results of this study provide valuable insight for further dissection of the genetic architecture of resistance to CG in soybean. They also highlight SNP variants and genes useful for genomics-informed selection decisions in the breeding process for improving resistance traits in soybean.

Identification of candidate genes for soybean seed coat-related traits using QTL mapping and GWAS.

Seed coat color is a typical morphological trait that can be used to reveal the evolution of soybean. The study of seed coat color-related traits in soybeans is of great significance for both evolutionary theory and breeding practices. In this study, 180 F10 recombinant inbred lines (RILs) derived from the cross between the yellow-seed coat cultivar Jidou12 (ZDD23040, JD12) and the wild black-seed coat accession Y9 (ZYD02739) were used as materials. Three methods, single-marker analysis (SMA), interval mapping (IM), and inclusive composite interval mapping (ICIM), were used to identify quantitative trait loci (QTLs) controlling seed coat color and seed hilum color. Simultaneously, two genome-wide association study (GWAS) models, the generalized linear model (GLM) and mixed linear model (MLM), were used to jointly identify seed coat color and seed hilum color QTLs in 250 natural populations. By integrating the results from QTL mapping and GWAS analysis, we identified two stable QTLs (qSCC02 and qSCC08) associated with seed coat color and one stable QTL (qSHC08) related to seed hilum color. By combining the results of linkage analysis and association analysis, two stable QTLs (qSCC02, qSCC08) for seed coat color and one stable QTL (qSHC08) for seed hilum color were identified. Upon further investigation using Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, we validated the previous findings that two candidate genes (CHS3C and CHS4A) reside within the qSCC08 region and identified a new QTL, qSCC02. There were a total of 28 candidate genes in the interval, among which Glyma.02G024600, Glyma.02G024700, and Glyma.02G024800 were mapped to the glutathione metabolic pathway, which is related to the transport or accumulation of anthocyanin. We considered the three genes as potential candidate genes for soybean seed coat-related traits. The QTLs and candidate genes detected in this study provide a foundation for further understanding the genetic mechanisms underlying soybean seed coat color and seed hilum color and are of significant value in marker-assisted breeding.

Agronomic characteristics of soybean as a function of inoculation, co-inoculation and N doses on eutrophic red latosol

The objective was to evaluate the agronomic traits of soybean as a function of inoculation, co-inoculation and N doses in Eutroferric RED OXSOL. The design was randomized blocks in a 4x4 factorial scheme, with four types of inoculation and four doses of N (0 = 0; 2 = 4.5; 4 = 9 and 8 % = 18 kg ha-1). No significant differences were found for plant height, number of pods per plant, number of grains per pod, nitrogen accumulation in the plant and grain yield. The mean number of nodules was higher at the dose of 2% N, equivalent to 46 nodules per plant inoculated with B. japonicum, and in the variables of dry mass of nodules, roots and shoots, inoculated with A. brasilense at the dose of 8% had higher averages with 486.94 mg plant-1, 11.91 g plant-1, 95.5 g plant-1, respectively. Nodulation efficiency had a linear increase for a dose of 8% N with a value of 72.32 g kg-1. For the number of nodules and nodulation efficiency, there was a significant increase when using the dose of 2% of N. Using the doses of 8%, the dry mass of nodules, root, aerial part and nodulation efficiency, obtained more satisfactory results than the other doses.

Characteristics of the soy sauce taste and koji enzyme profiles as affected by soybean traits

Soybean is the main raw material for soy sauce fermentation and has a significant impact on the quality of soy sauce. Understanding the impact of soybean traits on the soy sauce quality is important for the development of the industry. The present study compared the traits of 12 soybeans and the quality of their fermented kojis and soy sauces, revealing the differences in total sugar and protein content may be the key factors responsible for differences in soy sauce characteristics. On this basis, 6 representative soybeans including 3 high protein and low total sugar content soybeans (HPLS) and 3 low protein and high total sugar content soybeans (LPHS) were selected for further study. Results of the changes in enzyme activities during koji-making fermentation showed that neutral protease and beta-glucosidase activities were higher in HPLS kojis, while acid protease and xylanase activities were higher in LPHS kojis after 24 h of fermentation. Differences in enzyme activity further caused variations in the soy sauce quality and formed some correlations with soy sauce tastes, such as xylanase and umami (r = 0.885), kokumi (r = 0.916). The intensities of umami and kokumi were higher in LPHS soy sauces, which had a higher dipeptides content of X-Glu, X-Thr, X-Ser and Gly-X.

GmJAZ3 interacts with GmRR18a and GmMYC2a to regulate seed traits in soybean.

Seed weight is usually associated with seed size and is one of the important agronomic traits that determine yield. Understanding of seed weight control is limited, especially in soybean plants. Here we show that Glycine max JASMONATE-ZIM DOMAIN 3 (GmJAZ3), a gene identified through gene co-expression network analysis, regulates seed-related traits in soybean. Overexpression of GmJAZ3 promotes seed size/weight and other organ sizes in stable transgenic soybean plants likely by increasing cell proliferation. GmJAZ3 interacted with both G. max RESPONSE REGULATOR 18a (GmRR18a) and GmMYC2a to inhibit their transcriptional activation of cytokinin oxidase gene G. max CYTOKININ OXIDASE 3-4 (GmCKX3-4), which usually affects seed traits. Meanwhile, the GmRR18a binds to the promoter of GmMYC2a and activates GmMYC2a gene expression. In GmJAZ3-overexpressing soybean seeds, the protein contents were increased while the fatty acid contents were reduced compared to those in the control seeds, indicating that the GmJAZ3 affects seed size/weight and compositions. Natural variation in JAZ3 promoter region was further analyzed and Hap3 promoter correlates with higher promoter activity, higher gene expression and higher seed weight. The Hap3 promoter may be selected and fixed during soybean domestication. JAZ3 orthologs from other plants/crops may also control seed size and weight. Taken together, our study reveals a novel molecular module GmJAZ3-GmRR18a/GmMYC2a-GmCKXs for seed size and weight control, providing promising targets during soybean molecular breeding for better seed traits.

Genome-wide association study for biomass accumulation traits in soybean.

The online version contains supplementary material available at 10.1007/s11032-023-01380-6.

Functional consequences of light intensity on soybean leaf hydraulic conductance: Coordinated variations in leaf venation architecture and mesophyll structure

Leaf hydraulic conductance (Kleaf) is a critical determinant of photosynthesis. Prior research has assessed the influence of light intensity on Kleaf by affecting leaf veins. However, whether the mesophyll structure is associated with leaf hydraulic acclimation to different light intensities remains unclear. We investigated the responses of leaf gas exchange and Kleaf to different growth light intensities and checked for the correlation of Kleaf with leaf structural traits in soybean. Low light significantly reduced Kleaf, but Kleaf and stomatal conductance remain coordinated. Low light decreased the stomatal density to match the balance between in water supply and carbon gain capacity. The decline in Kleaf under low growth light condition was partly due to for the reduction of the water movement through leaf veins because of reduced leaf vein thickness and density and xylem conduit size. In addition, low light reduces the mesophyll cell‐to‐cell connectivity and increased the volume fraction of intercellular air space. As a result, the area available for liquid‐phase flow decreases, and subsequently decreased Kleaf. The present study highlights the coordination role between leaf venation architecture and mesophyll structure influencing Kleaf in response to light intensity.

Zinc-finger protein GmZF351 improves both salt and drought stress tolerance in soybean.

Abiotic stress is one of the most important factors reducing soybean yield. It is essential to identify regulatory factors contributing to stress responses. A previous study found that the tandem CCCH zinc-finger protein GmZF351 is an oil level regulator. In this study, we discovered that the GmZF351 gene is induced by stress and that the overexpression of GmZF351 confers stress tolerance to transgenic soybean. GmZF351 directly regulates the expression of GmCIPK9 and GmSnRK, leading to stomata closing, by binding to their promoter regions, which carry two CT(G/C)(T/A)AA elements. Stress induction of GmZF351 is mediated through reduction in the H3K27me3 level at the GmZF351 locus. Two JMJ30-demethylase-like genes, GmJMJ30-1 and GmJMJ30-2, are involved in this demethylation process. Overexpression of GmJMJ30-1/2 in transgenic hairy roots enhances GmZF351 expression mediated by histone demethylation and confers stress tolerance to soybean. Yield-related agronomic traits were evaluated in stable GmZF351-transgenic plants under mild drought stress conditions. Our study reveals a new mode of GmJMJ30-GmZF351 action in stress tolerance, in addition to that of GmZF351 in oil accumulation. Manipulation of the components in this pathway is expected to improve soybean traits and adaptation under unfavorable environments.

Genetic Diversity of Korean Wild Soybean Core Collections and Genome-Wide Association Study for Days to Flowering.

The utilization of wild soybean germplasms in breeding programs increases genetic diversity, and they contain the rare alleles of traits of interest. Understanding the genetic diversity of wild germplasms is essential for determining effective strategies that can improve the economic traits of soybeans. Undesirable traits make it challenging to cultivate wild soybeans. This study aimed to construct a core subset of 1467 wild soybean accessions of the total population and analyze their genetic diversity to understand their genetic variations. Genome-wild association studies were conducted to detect the genetic loci underlying the time to flowering for a core subset collection, and they revealed the allelic variation in E genes for predicting maturity using the available resequencing data of wild soybean. Based on principal component and cluster analyses, 408 wild soybean accessions in the core collection covered the total population and were explained by 3 clusters representing the collection regions, namely, Korea, China, and Japan. Most of the wild soybean collections in this study had the E1e2E3 genotype according to association mapping and a resequencing analysis. Korean wild soybean core collections can provide helpful genetic resources to identify new flowering and maturity genes near the E gene loci and genetic materials for developing new cultivars, facilitating the introgression of genes of interest from wild soybean.

Morphological and microsatellite marker-based characterization and diversity analysis of novel vegetable soybean [Glycine max (L.) Merrill

Vegetable soybean seeds are among the most popular and nutrient-dense beans in the world due to their delicious flavor, high yield, superior nutritional value, and low trypsin content. There is significant potential for this crop that Indian farmers do not fully appreciate because of the limited germplasm range. Therefore, the current study aims to identify the diverse lines of vegetable soybean and explore the diversity produced by hybridizing grain and vegetable-type soybean varieties. Indian researchers have not yet published work describing and analysing novel vegetable soybean for microsatellite markers and morphological traits. Sixty polymorphic SSR markers and 19 morphological traits were used to evaluate the genetic diversity of 21 newly developed vegetable soybean genotypes. A total of 238 alleles, ranging from 2 to 8, were found, with a mean of 3.97 alleles per locus. The polymorphism information content varied from 0.05 to 0.85, with an average of 0.60. A variation of 0.25-0.58 with a mean of 0.43 was observed for Jaccard's dissimilarity coefficient. The diverse genotypes identified can be helpful to understand the genetics of vegetable soybean traits and can be used in improvement programs; study also explains the utility of SSR markers for diversity analysis of vegetable soybean. Here, we identified the highly informative SSRs with PIC > 0.80 (satt199, satt165, satt167, satt191, satt183, satt202, and satt126), which apply to genetic structure analysis, mapping strategies, polymorphic marker surveys, and background selection in genomics-assisted breeding.

Genome-Wide Association Study for Agronomic Traits in Wild Soybean (Glycine soja)

The agronomic traits of soybean are important because they are directly or indirectly related to its yield. Cultivated soybean (Glycine max (L.) Merr) has lost genetic diversity during domestication and selective breeding. However, wild soybean (G. soja) represents a useful breeding material because it has a diverse gene pool. In this study, a total of 96,432 single-nucleotide polymorphisms (SNPs) across 203 wild soybean accessions from the 180K Axiom® Soya SNP array were employed in the association analysis. Wild soybean accessions were divided into four clusters based on their genetic distance using ADMIXTURE, principal component analysis, and neighbor-joining clusters. The linkage disequilibrium decayed rapidly in wild soybean. A genome-wide association study was conducted for days to flowering (DtF), days to maturity (DtM), the number of pods (NoP), and the 100-seed weight (100SW), which are major agronomic traits for wild soybean accessions. A total of 22 significant SNPs were found to be associated with DtF, DtM, and the 100SW. Based on the detected SNP markers, Glyma.12g210400, a gene related to DtF, Glyma.17g115300, a gene related to DtM, and Glyma.14g140200, a gene related to the 100SW, were selected as candidate genes. The SNP markers related to agronomic traits identified in this study are expected to help improve the quality of soybean cultivars through selective breeding.

Diallel analysis of soybean (Glycine max L.) for biomass yield and root characteristics under low phosphorus soil conditions in Western Ethiopia.

Combining ability studies under low soil P conditions provides useful information on the inheritance of important traits to improve soybean for low P tolerance. The study aimed at determining the combining ability and gene actions of biomass yield and root traits in soybean under low phosphorus conditions. Nine parental genotypes and their 36 half diallel F2/F3 progenies were evaluated at two locations in Ethiopia on soils of low P availability. Highly significant (P<0.01) general combining ability (GCA) were found for all the traits and specific combining ability (SCA) for root dry weight and root fresh weight; while the SCA effects of all the rest of the traits were significant (P<0.05). The higher relative contributions of GCA over SCA revealed the preponderance of additive gene action in the inheritance of biomass yield, root dry weight, biomass dry weight, root volume, and root fresh weight with respective relative GCA:SCA contributions of (60.6, 39.4), (50.4, 49.6), (54.9, 45.1), (51.1, 48.9), and (52.1, 47.9); while the narrow-sense heritability was high (34.3%) only for biomass yield. Hardee-1 displayed significant (P<0.05) and positive GCA effects for most of the studied traits, and several crosses involving this parent showed superior performances. The traits i.e., biomass yield, biomass dry weight, root volume and root fresh weight showed highly (P<0.001) correlation with grain yield. Thus, breeding programs aiming to improve soybean for biomass yield and root traits under low-P condition can use Hardee-1 as a parent.

Resistance vs. surrender: Different responses of functional traits of soybean and peanut to intercropping with maize

Resistance vs. surrender: Different responses of functional traits of soybean and peanut to intercropping with maize

Genetic variability, genetic advance and heritability of black and brown seeded soybean [Glycine max (L.) Merrill] lines in Jimma and Bonga Southwest Ethiopia

An experiment was conducted with a simple lattice design with two replications to estimate the genetic variability in 62 soybean genotypes and 2 standard check varieties. The variability parameters such as mean, range of variation, genotypic and phenotypic coefficient of variation, heritability in the broad sense, genetic advance, and genetic advance as percentage of mean were estimated for 11 different traits. The values of the phenotypic coefficient of variation (PCV) were greater than the genotypic coefficient of variation (GCV) for all the traits, revealing the influence of environmental factors. The value of heritability was determined to be high for the traits such as grain yield, harvest index, number of seeds per pod, number of primary branches per plant, number of pods per plant and hundred seed weight. Indicating that the larger portion of total variation would be under genetic control and selection based on phenotypic levels would be useful for the improvement of these traits in soybean. High estimates of heritability together with high genetic advance as percentage of mean were recorded for grain yield, harvest index, number of seeds per pod, number of primary branches per plant, number of pods per plant and hundred seed weight, which may be attributed to the presence of additive gene action and had high selective value. Thus, selection pressure could successfully be applied to these traits for soybean improvement programs. Int. J. Agril. Res. Innov. Tech. 12(2): 14-17, December 2022