Soybean Breeding Research Articles

Estimation of soybean yield based on high-throughput phenotyping and machine learning.

Soybeans are an important crop used for food, oil, and feed. However, China's soybean self-sufficiency is highly inadequate, with an annual import volume exceeding 80%. RGB cameras serve as powerful tools for estimating crop yield, and machine learning is a practical method based on various features, providing improved yield predictions. However, selecting different input parameters and models, specifically optimal features and model effects, significantly influences soybean yield prediction. This study used an RGB camera to capture soybean canopy images from both the side and top perspectives during the R6 stage (pod filling stage) for 240 soybean varieties (a natural population formed by four provinces in China: Sichuan, Yunnan, Chongqing, and Guizhou). From these images, the morphological, color, and textural features of the soybeans were extracted. Subsequently, feature selection was performed on the image parameters using a Pearson correlation coefficient threshold ≥0.5. Five machine learning methods, namely, CatBoost, LightGBM, RF, GBDT, and MLP, were employed to establish soybean yield estimation models based on the individual and combined image parameters from the two perspectives extracted from RGB images. (1) GBDT is the optimal model for predicting soybean yield, with a test set R2 value of 0.82, an RMSE of 1.99 g/plant, and an MAE of 3.12%. (2) The fusion of multiangle and multitype indicators is conducive to improving soybean yield prediction accuracy. Therefore, this combination of parameters extracted from RGB images via machine learning has great potential for estimating soybean yield, providing a theoretical basis and technical support for accelerating the soybean breeding process.

Determination of flavonoid and anthocyanin contents, and antioxidant activity of selected Philippine soybean (Glycine max) genotypes

Soybeans contain flavonoids and anthocyanins that are associated with health benefits related to antioxidant activities. In this study, the total flavonoid content (TFC), total anthocyanin content (TAC), and the relative antioxidant activities (AOA) of selected Philippine soybean genotypes were screened in order to select and recommend promising genotypes that may be used for further breeding and varietal development. Using the aluminum trichloride method, the genotypes POP 1-44 (TFC = 0.619 g/100 g), PHL 29272 (TFC = 0.616 g/100 g), and Tiwala 6 (TFC = 0.608 g/100 g) were determined to have the highest calculated TFC values. pH differential and 2,2-diphenyl-1-picrylhydrazyl (DPPH) assays distinguished all three black-seeded soybean genotypes PHL 29272 (TAC = 177.010 mg/100 g; AOA = 24.476%), PHL 29502 (TAC = 143.750 mg/100 g; AOA = 25.745%), and PHL 29552 (TAC = 123.572 mg/100 g; AOA = 29.297%) with the highest anthocyanin contents and relative antioxidant activities. Genotype PHL 29272 was consistently found among those with the highest results for the three tests. Significant correlations (α = 0.05) were found between flavonoid content and antioxidant activity (p < 0.0001), and between anthocyanin content and antioxidant activity (p < 0.0001). In conclusion, the study was able to identify genotypes that can be recommended as the most suitable candidates for soybean breeding activities.

Understanding the molecular mechanisms of drought tolerance in wild soybean (Glycine soja) through multi-omics-based alternative splicing predictions

The absence of adequate moisture resulting from drought poses a significant threat to both the viability and productivity of soybean cultivation. Genetic variation in common soybeans has been noticeably reduced through continuous breeding, and wild relatives with wider genetic diversity are one of the best tools in the search for new tolerance genes. In this study, we selected 139 genes co-expressed at transcript and protein levels in response to drought in Glycine soja through a multi-omics analysis. Drought stress induced co-expression of transcripts and proteins involved in dopamine synthesis within tyrosine metabolism. Polyphenol oxidase, involved in the dopamine synthesis process, was uniquely identified in both DEGs and DEPs, with its protein abundance increased. Co-expression of 9-lipoxygenase during linoleic acid metabolism was confirmed, along with consistent protein accumulation. The co-expression profiling of transcripts and proteins suggests that they may influence their regulatory feedback loops or unknown regulatory mechanisms. Additionally, we predicted the regulation of alternative splicing (AS) in response to drought. AS was predicted for 139 co-expressed genes, and four drought-tolerance-related gene candidate groups were selected. The expression levels of four genes, FT1, CCR1L, RPL18, and uncharacterized LOC114422617, varied depending on their transcript isoforms under drought stress. The occurrence of AS under drought stress may play a role in eliminating susceptibility genes or inducing tolerance genes to adapt to drought stress. Overall, this study reveals a novel mechanism of drought adaptation in wild soybean by predicting the regulation of metabolic pathways and AS events at the transcriptome and proteome levels and presents potential targets for soybean breeding.

Physiological and Molecular Analysis of Soybean Seed Longevity and Validation of Candidate Markers

Background: Seed longevity is a major constraint in soybean seed production. The major focus of this study is to analyze the physiological and molecular changes associated with seed longevity and identify promising germplasm which are good storers for soybean breeding program. Methods: Nineteen genotypes were studied for seed longevity using accelerated ageing test and genetic integrity based on SSR marker data. Genotypes were clustered into distinct groups based on seed morphological and physiological parameters (Mahalanobis D2 analysis). SSR markers for seed longevity were validated in the germplasm. Result: Per cent reduction in germination after accelerated ageing was significantly and positively correlated with traits associated with seed storability such as seed length, seed width, seed thickness and 100 seed weight and negatively correlated with seedling vigour indices. Hence, it would be worthwhile to rely upon these parameters for enhancing the seed storability in soybean. Genetic integrity of the germplasm was evaluated based on SSR markers in accelerated ageing seeds. SSR markers (Satt 285, Satt 534, Satt 538, Satt 281, Satt 162, Satt 631 and Satt 371) revealed significant association for the seed longevity characters such as seed length, seed width, seed thickness and seed weight. Candidate markers (Satt 371, Satt 281, Satt162, Satt 285, Satt 534) which can differentiate the soybean genotypes for storability have been identified in this study. The genotypes were grouped into seven clusters with monogenotypic cluster III (PSPB23) having minimum reduction in germination after accelerated ageing.

Genome-Wide Association Analysis of Yield-Related Traits and Candidate Genes in Vegetable Soybean.

Owing to the rising demand for vegetable soybean products, there is an increasing need for high-yield soybean varieties. However, the complex correlation patterns among quantitative traits with genetic architecture pose a challenge for improving vegetable soybean through breeding. Herein, a genome-wide association study (GWAS) was applied to 6 yield-related traits in 188 vegetable soybean accessions. Using a BLINK model, a total of 116 single nucleotide polymorphisms (SNPs) were identified for plant height, pod length, pod number, pod thickness, pod width, and fresh pod weight. Furthermore, a total of 220 genes were found in the 200 kb upstream and downstream regions of significant SNPs, including 11 genes encoding functional proteins. Among them, four candidate genes, Glyma.13G109100, Glyma.03G183200, Glyma.09G102200, and Glyma.09G102300 were analyzed for significant haplotype variations and to be in LD block, which encode MYB-related transcription factor, auxin-responsive protein, F-box protein, and CYP450, respectively. The relative expression of candidate genes in V030 and V071 vegetable soybean (for the plant height, pod number, and fresh pod weight of V030 were lower than those of the V071 strains) was significantly different, and these genes could be involved in plant growth and development via various pathways. Altogether, we identified four candidate genes for pod yield and plant height from vegetable soybean germplasm. This study provides insights into the genomic basis for improving soybean and crucial genomic resources that can facilitate genome-assisted high-yielding vegetable soybean breeding.

Comparative Transcriptomics of Soybean Genotypes with Partial Resistance Toward Phytophthora sojae, Conrad, and M92-220 to Moderately Susceptible Fast Neutron Mutant Soybeans and Sloan.

The breeding of disease-resistant soybeans cultivars to manage Phytophthora root and stem rot caused by the pathogen Phytophthora sojae involves combining quantitative disease resistance (QDR) and Rps gene-mediated resistance. To identify and confirm potential mechanisms of QDR toward P. sojae, we conducted a time course study comparing changes in gene expression among Conrad and M92-220 with high QDR to susceptible genotypes, Sloan, and three mutants derived from fast neutron irradiation of M92-220. Differentially expressed genes from Conrad and M92-220 indicated several shared defense-related pathways at the transcriptomic level but also defense pathways unique to each cultivar, such as stilbenoid, diarylheptanoid, and gingerol biosynthesis and monobactam biosynthesis. Gene Ontology pathway analysis showed that the susceptible fast neutron mutants lacked enrichment of three terpenoid-related pathways and two cell wall-related pathways at either one or both time points, in contrast to M92-220. The susceptible mutants also lacked enrichment of potentially important Kyoto Encyclopedia of Genes and Genomes pathways at either one or both time points, including sesquiterpenoid and triterpenoid biosynthesis; thiamine metabolism; arachidonic acid; stilbenoid, diarylheptanoid, and gingerol biosynthesis; and monobactam biosynthesis. Additionally, 31 genes that were differentially expressed in M92-220 following P. sojae infection were not expressed in the mutants. These 31 genes have annotations related to unknown proteins; valine, leucine, and isoleucine biosynthesis; and protein and lipid metabolic processes. The results of this study confirm previously proposed mechanisms of QDR, provide evidence for potential novel QDR pathways in M92-220, and further our understanding of the complex network associated with QDR mechanisms in soybean toward P. sojae.

Identification of soybean mosaic virus strain SC7 resistance loci and candidate genes in soybean [Glycine max (L.) Merr.

Soybean [Glycine max (L.) Merr.] is an important legume crop worldwide, which provides abundant plant protein and oil for human beings. Soybean mosaic virus (SMV) can cause serious damage to the yield and quality of soybean, but it is difficult to control SMV with chemicals, breeding SMV-resistant varieties has become the most effective way to control the disease. Therefore, it is important to identify SMV resistance genes from soybean resources and apply them to soybean breeding. In this study, the disease rates (DRs) of 219 soybean accessions to SMV strain SC7 in two environments were investigated. A high-density NJAU 355K SoySNP array was used for genome-wide association study (GWAS) of DR. A 274kb region on chromosome 15 (1,110,567bp to 1,384,173bp) was repeatedly detected in two environments. Six new significant single nucleotide polymorphisms (SNPs) on chromosome 15 were identified. Four of these six SNPs were located within two candidate genes, Glyma.15G015700 and Glyma.15G015800. The elite haplotype Glyma.15G015700Hap I with low DR exhibited strong resistance to SC7. The expression of Glyma.15G015700 in the SMV-resistant accession increased significantly after inoculation with SC7. Furthermore, most of the proteins predicted to interact with Glyma.15G015700 are heat shock proteins, which have been shown to be related to disease resistance. In summary, new SMV resistance loci and a new candidate gene, Glyma.15G015700, were identified and might be utilized in further soybean disease resistance breeding.

Developing an SNP dataset for efficiently evaluating soybean germplasm resources using the genome sequencing data of 3,661 soybean accessions

BackgroundSingle nucleotide polymorphism (SNP) markers play significant roles in accelerating breeding and basic crop research. Several soybean SNP panels have been developed. However, there is still a lack of SNP panels for differentiating between wild and cultivated populations, as well as for detecting polymorphisms within both wild and cultivated populations.ResultsThis study utilized publicly available resequencing data from over 3,000 soybean accessions to identify differentiating and highly conserved SNP and insertion/deletion (InDel) markers between wild and cultivated soybean populations. Additionally, a naturally occurring mutant gene library was constructed by analyzing large-effect SNPs and InDels in the population.ConclusionThe markers obtained in this study are associated with numerous genes governing agronomic traits, thus facilitating the evaluation of soybean germplasms and the efficient differentiation between wild and cultivated soybeans. The natural mutant gene library permits the quick identification of individuals with natural mutations in functional genes, providing convenience for accelerating soybean breeding using reverse genetics.

Biochemical characterization and metabolic reprogramming of amino acids in Soybean roots under drought stress.

Amino acids play important roles in stress resistance, plant growth, development, and quality, with roots serving as the primary organs for drought response. We conducted biochemical and multi-omics analyses to investigate the metabolic processes of root amino acids in drought-resistant (HN44) and drought-sensitive (HN65) soybean (Glycine max) varieties. Our analysis revealed an increase in total amino acid content in both varieties, with phenylalanine, proline, and methionine accumulating in both. Additionally, several amino acids exhibited significant decreases in HN65 but slight increases in HN44. Multi-omics association analysis identified 13 amino acid-related pathways. We thoroughly examined the changes in genes and metabolites involved in various amino acid metabolism/synthesis and determined core genes and metabolites through correlation networks. The phenylalanine, tyrosine, and tryptophan metabolic pathways and proline, glutamic acid and sulfur-containing amino acid pathways were particularly important for drought resistance. Some candidate genes, such as ProDH and P4HA family genes, and metabolites, such as O-acetyl-L-serine, directly affected up- and downstream metabolism to induce drought resistance. This study provided a basis for soybean drought resistance breeding.

Discovery and genome-wide characterization of a novel miniature inverted repeat transposable element reveal genome-specific distribution in Glycine.

Miniature inverted repeat transposable elements (MITEs) are a dynamic component responsible for genome evolution. Tourist MITEs are derived from and mobilized by elements from the harbinger superfamily. In this study, a novel family of Tourist-like MITE was characterized in wild soybean species Glycine falcata. The new GftoMITE1 was initially discovered as an insertional polymorphism of the centromere-specific histone H3 (CenH3) gene in G. falcata. Using polymerase chain reaction, cloning and sequencing approaches, we showed a high number of copies of the GftoMITE1 family. Extensive bioinformatic analyses revealed the genome-level distribution and locus-specific mapping of GftoMITE1 members in Glycine species. Our results provide the first extensive characterization of the GftoMITE1 family and contribute to the understanding of the evolution of MITEs in the Glycine genus. Genome-specific GftoMITE1 was prominent in perennial wild soybean species, but not in annual cultivated soybean (Glycine max) or its progenitor (Glycine soja). We discuss that the GftoMITE1 family reveals a single rapid amplification in G. falcata and could have potential implications for gene regulation and soybean breeding as an efficient genetic marker for germplasm utilization in the future.

Identification of QTNs, QTN-by-environment interactions, and their candidate genes for salt tolerance related traits in soybean

BackgroundSalt stress significantly reduces soybean yield. To improve salt tolerance in soybean, it is important to mine the genes associated with salt tolerance traits.ResultsSalt tolerance traits of 286 soybean accessions were measured four times between 2009 and 2015. The results were associated with 740,754 single nucleotide polymorphisms (SNPs) to identify quantitative trait nucleotides (QTNs) and QTN-by-environment interactions (QEIs) using three-variance-component multi-locus random-SNP-effect mixed linear model (3VmrMLM). As a result, eight salt tolerance genes (GmCHX1, GsPRX9, Gm5PTase8, GmWRKY, GmCHX20a, GmNHX1, GmSK1, and GmLEA2-1) near 179 significant and 79 suggested QTNs and two salt tolerance genes (GmWRKY49 and GmSK1) near 45 significant and 14 suggested QEIs were associated with salt tolerance index traits in previous studies. Six candidate genes and three gene-by-environment interactions (GEIs) were predicted to be associated with these index traits. Analysis of four salt tolerance related traits under control and salt treatments revealed six genes associated with salt tolerance (GmHDA13, GmPHO1, GmERF5, GmNAC06, GmbZIP132, and GmHsp90s) around 166 QEIs were verified in previous studies. Five candidate GEIs were confirmed to be associated with salt stress by at least one haplotype analysis. The elite molecular modules of seven candidate genes with selection signs were extracted from wild soybean, and these genes could be applied to soybean molecular breeding. Two of these genes, Glyma06g04840 and Glyma07g18150, were confirmed by qRT-PCR and are expected to be key players in responding to salt stress.ConclusionsAround the QTNs and QEIs identified in this study, 16 known genes, 6 candidate genes, and 8 candidate GEIs were found to be associated with soybean salt tolerance, of which Glyma07g18150 was further confirmed by qRT-PCR.

Registration of ‘S16‐16814R’: A glyphosate‐tolerant, high‐oleic soybean cultivar

AbstractThere is a demand for soybean [Glycine max (L.) Merr.] cultivars with more functional soybean oil for food and industrial applications. Soybean breeding programs have devoted more efforts to developing high‐yielding soybean cultivars with elevated oil content and improved fatty acid profiles. The University of Missouri – Fisher Delta Research, Extension, and Education Center soybean breeding program has developed and released the high‐oleic soybean cultivar ‘S16‐16814R’ (Reg. no. CV‐561, PI 704911). It is a maturity group 4‐late (relative maturity 4.9), glyphosate‐tolerant (Roundup Ready 1) soybean cultivar with high oleic (84.0%) acid content and a reduced linolenic (3.5%) acid content. S16‐16814R is resistant to multiple nematode species, including soybean cyst nematode races 2 (HG Type 1.2.5.7), 3 (HG Type 5.7), and 5 (HG Type 2.5.7); southern root‐knot nematode; and reniform nematode. S16‐16814R was evaluated from 2017 to 2020 in 61 environments across eight southern US states. It averaged 92% of the check mean for yield, indicating competitive yield performance across multiple environments.

Soybean (Glycine max L. Merrill): A Multipurpose Legume Shaping Our World

Soybean (Glycine max L. Merrill), indigenous to East Asia, has assumed a pivotal role as a global substantial crop, substantially contributing to food security, a wide spectrum of product lines and rigorous scientific exploration. This unassuming legume, bearing the scientific nomenclature Glycine max L. Merrill, has transcended its East Asian origins to become a cornerstone in supplying 25% of the world's edible oil and approximately two-thirds of the global livestock protein concentrate. The significance of soybeans extends beyond their utility in direct human consumption; they serve as an indispensable component in crop rotation, thereby fostering soil health and averting erosion. This comprehensive review embarks on a profound exploration of soybeans, encompassing their historical significance, botanical attributes, geographical distribution, climatic influence and reproductive biology. Furthermore, it provides a detailed account of advancements in genetic enhancement and biotechnological applications within soybean breeding, emphasizing the importance of transgenic soybean production. Disease resistance efforts, including the identification of resistance loci, markers and mutations, are thoroughly discussed, with a specific focus on the improvement of Indian soybean varieties.

Impacts of short-term increased CO2 levels on the composition of amoA-type nitrifying and nirS-type denitrifying bacterial communities in soybean rhizosphere in Mollisols

Increased atmospheric carbon dioxide (CO2) concentrations cause climate change, affecting the stability of agricultural ecosystems. Soil nitrification and denitrification, which are fundamental N cycling processes, determine soil N availability for plants, nitrous oxide (N2O) emissions, and N flow in ecosystems. However, the responses of specific nitrifying and denitrifying soil microorganisms to increased CO2 levels remain unknown. In this study, four soybean [Glycine max (L.) Merr.] varieties (Xiaohuangjin [XHJ], Suinong 14 [SN14], Mufeng 5 [MF5], and Dongsheng 1 [DS1]) were planted in open-top chambers containing Mollisols under ambient CO2 (aCO2, 410 ppm) and elevated CO2 (eCO2, 550 ppm) conditions. The abundance, composition, and potential activity of ammonia mono‑oxygenase subunit A gene (amoA) of ammonia oxidise bacteria (AOB) and nitrite reductase S gene (nirS)-type denitrifiers under increased atmospheric CO2 levels were investigated. The results showed that eCO2 decreased the nitrification potential in XHJ and MF5 rhizospheres, whereas increasing it in the SN14 rhizosphere. Denitrification potential decreased in the rhizosphere of all soybean cultivars, except XHJ, under eCO2 conditions. The decreased nitrification and denitrification potentials imply that eCO2 conditions may slow N2O emission. Principal co-ordinate analysis revealed that the composition of amoA and nirS communities was not altered by eCO2, but rather by the presence of different soybean cultivars. The eCO2-induced variations in the nitrification and denitrification potentials of microbes in the rhizosphere among different cultivars can affect the N cycle and should be considered in future soybean breeding programmes.

Knockout of miR396 genes increases seed size and yield in soybean.

Yield improvement has long been an important task for soybean breeding in the world in order to meet the increasing demand for food and animal feed. miR396 genes have been shown to negatively regulate grain size in rice, but whether miR396 family members may function in a similar manner in soybean is unknown. Here, we generated eight soybean mutants harboring different combinations of homozygous mutations in the six soybean miR396 genes through genome editing with clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated nuclease (Cas)12SF01 in the elite soybean cultivar Zhonghuang 302 (ZH302). Four triple mutants (mir396aci, mir396acd, mir396adf, and mir396cdf), two quadruple mutants (mir396abcd and mir396acfi), and two quintuple mutants (mir396abcdf and mir396bcdfi) were characterized. We found that plants of all the mir396 mutants produced larger seeds compared to ZH302 plants. Field tests showed that mir396adf and mir396cdf plants have significantly increased yield in growth zones with relatively high latitude which are suited for ZH302 and moderately increased yield in lower latitude. In contrast, mir396abcdf and mir396bcdfi plants have increased plant height and decreased yield in growth zones with relatively high latitude due to lodging issues, but they are suited for low latitude growth zones with increased yield without lodging problems. Taken together, our study demonstrated that loss-of-function of miR396 genes leads to significantly enlarged seed size and increased yield in soybean, providing valuable germplasms for breeding high-yield soybean.

Genomic Prediction of Root Traits via Aerial Traits in Soybean Using Canonical Variables

The phenotypic evaluation of root traits in soybeans presents challenges in breeding due to its high cost and the requirement for experimental plot destruction. Establishing relationships between aerial and root traits is crucial, given the relative ease of phenotypic evaluations for aerial traits. Therefore, this study aims to utilize the canonical correlation technique to estimate latent variables, subsequently employing GBLUP for the genomic prediction of the root traits (length, volume, surface area, and dry mass) using phenotypic information from aerial part traits (hypocotyl diameter and dry mass). Our results demonstrate the effectiveness of the technique in predicting the root part, even when not directly evaluated. The agreement observed between the top 10% of individuals selected based on the canonical variable and each root trait individually was considered moderate or substantial. This enables the simultaneous selection of genotypes based on both trait groups, providing a valuable approach for soybean breeding programs.

Identification of superior and rare haplotypes to optimize branch number in soybean

Key messageUsing the integrated approach in the present study, we identified eleven significant SNPs, seven stable QTLs and 20 candidate genes associated with branch number in soybean.Branch number is a key yield-related quantitative trait that directly affects the number of pods and seeds per soybean plant. In this study, an integrated approach with a genome-wide association study (GWAS) and haplotype and candidate gene analyses was used to determine the detailed genetic basis of branch number across a diverse set of soybean accessions. The GWAS revealed a total of eleven SNPs significantly associated with branch number across three environments using the five GWAS models. Based on the consistency of the SNP detection in multiple GWAS models and environments, seven genomic regions within the physical distance of ± 202.4 kb were delineated as stable QTLs. Of these QTLs, six QTLs were novel, viz., qBN7, qBN13, qBN16, qBN18, qBN19 and qBN20, whereas the remaining one, viz., qBN12, has been previously reported. Moreover, 11 haplotype blocks, viz., Hap4, Hap7, Hap12, Hap13A, Hap13B, Hap16, Hap17, Hap18, Hap19A, Hap19B and Hap20, were identified on nine different chromosomes. Haplotype allele number across the identified haplotype blocks varies from two to five, and different branch number phenotype is regulated by these alleles ranging from the lowest to highest through intermediate branching. Furthermore, 20 genes were identified underlying the genomic region of ± 202.4 kb of the identified SNPs as putative candidates; and six of them showed significant differential expression patterns among the soybean cultivars possessing contrasting branch number, which might be the potential candidates regulating branch number in soybean. The findings of this study can assist the soybean breeding programs for developing cultivars with desirable branch numbers.

SoybeanTracer: An In-Field scene property-based framework for high-throughput soybean canopy coverage extraction and evaluation

Soybean is a crucial plant-based protein and vegetable oil source for the global population and a significant cereal-oil dual-purpose crop. Extracting soybean canopy coverage, subsequently implementing evaluation in a low-cost, high-throughput and accurate manner, is highly valuable for soybean breeding and yield increase. Although the utilization of RGB remote sensing images for soybean analysis offers distinct advantages in terms of its cost effectiveness, there are still issues to be addressed. Specifically, the in-field scene properties of soybean canopy data have rarely been developed and there is a gap in automatic evaluation of soybean canopy coverage. For purpose of tackling these pending issues, this study proposed SoybeanTracer, a novel framework designed to achieve accurate soybean canopy coverage extraction and enable specialized evaluation with low cost and high throughput. The proposed framework comprised two components: Soybean Canopy Segmentation Network (SCSNet) and an agronomic soybean coverage evaluation system. Specifically, SCSNet employed a feature extraction network integrating the homogeneity within plot regions and soybean distribution characteristics. To further address the segmentation challenge of soybean plants with sparse growth posed by genotypes, a soybean multiscale feature fusion module was designed. As a result, SCSNet achieved a mean intersection over union (mIoU) and mean pixel accuracy (mPA) of 89.39% and 94.42%, respectively, on soybean canopy segmentation. Therefore, accurate and low-cost extraction of soybean canopy coverage was achieved through the use of RGB remote sensing data. Furthermore, the soybean canopy coverage evaluation system proposed in this study encompassed five levels, characterized by wider spacing at the two ends and narrower spacing in the middle. This agronomic evaluation system had been effectively implemented on 196 plots. The variance in the pairwise levels of the coverage evaluation results demonstrated the robustness of the evaluation system. SoybeanTracer could indeed help to extract soybean canopy coverage and provide valuable reference for implementing soybean genotype selection, laying a useful foundation for other crops in similar scientific tasks. The source code and trained models were available at https://github.com/KLoAS-Research/SCSNet-SoybeanTracer.

Using agro-ecological zones to improve the representation of a multi-environment trial of soybean varieties.

This research introduces a novel framework for enhancing soybean cultivation in North America by categorizing growing environments into distinct ecological and maturity-based zones. Using an integrated analysis of long-term climatic data and records of soybean varietal trials, this research generates a zonal environmental characterization which captures major components of the growing environment which affect the range of adaptation of soybean varieties. These findings have immediate applications for optimizing multi-environment soybean trials. This characterization allows breeders to assess the environmental representation of a multi-environmental trial of soybean varieties, and to strategize the distribution of testing and the placement of test sites accordingly. This application is demonstrated with a historical scenario of a soybean multi-environment trial, using two resource allocation models: one targeted towards improving the general adaptation of soybean varieties, which focuses on widely cultivated areas, and one targeted towards specific adaptation, which captures diverse environmental conditions. Ultimately, the study aims to improve the efficiency and impact of soybean breeding programs, leading to the development of cultivars resilient to variable and changing climates.

Integrated Transcriptomic and Proteomic Characterization of a Chromosome Segment Substitution Line Reveals the Regulatory Mechanism Controlling the Seed Weight in Soybean

Soybean is the major global source of edible oils and vegetable proteins. Seed size and weight are crucial traits determining the soybean yield. Understanding the molecular regulatory mechanism underlying the seed weight and size is helpful for improving soybean genetic breeding. The molecular regulatory pathways controlling the seed weight and size were investigated in this study. The 100-seed weight, seed length, seed width, and seed weight per plant of a chromosome segment substitution line (CSSL) R217 increased compared with those of its recurrent parent ‘Suinong14’ (SN14). Transcriptomic and proteomic analyses of R217 and SN14 were performed at the seed developmental stages S15 and S20. In total, 2643 differentially expressed genes (DEGs) and 208 differentially accumulated proteins (DAPs) were detected at S15, and 1943 DEGs and 1248 DAPs were detected at S20. Furthermore, integrated transcriptomic and proteomic analyses revealed that mitogen-activated protein kinase signaling and cell wall biosynthesis and modification were potential pathways associated with seed weight and size control. Finally, 59 candidate genes that might control seed weight and size were identified. Among them, 25 genes were located on the substituted segments of R217. Two critical pathways controlling seed weight were uncovered in our work. These findings provided new insights into the seed weight-related regulatory network in soybean.