Soybean Cultivars Research Articles

Genetic diversity and genome-wide association study of partial resistance to Sclerotinia stem rot in a Canadian soybean germplasm panel.

Developing genetically resistant soybean cultivars is key in controlling the destructive Sclerotinia Stem Rot (SSR) disease. Here, a GWAS study in Canadian soybeans identified potential marker-trait associations and candidate genes, paving the way for more efficient breeding methods for SSR. Sclerotinia stem rot (SSR), caused by the fungal pathogenSclerotinia sclerotiorum, is one of the most important diseases leading to significant soybean yield losses in Canada and worldwide. Developing soybean cultivars that are genetically resistant to the disease is the most inexpensive and reliable method to control the disease. However, breeding for resistance is hampered by the highly complex nature of genetic resistance to SSR in soybean. This study sought to understand the genetic basis underlying SSR resistance particularly in soybean grown in Canada. Consequently, a panel of 193 genotypes was assembled based on maturity group and genetic diversity as representative of Canadian soybean cultivars. Plants were inoculated and screened for SSR resistance in controlled environments, where variation for SSR phenotypic response was observed. The panel was also genotyped via genotyping-by-sequencing and the resulting genotypic data were imputed using BEAGLE v5 leading to a catalogue of 417K SNPs. Through genome-wide association analyses (GWAS) using FarmCPU method with threshold of FDR-adjustedp-values < 0.1, we identified significant SNPs on chromosomes 2 and 9 with allele effects of 16.1 and 14.3, respectively. Further analysis identified three potential candidate genes linked to SSR disease resistance within a 100Kb window surrounding each of the peak SNPs. Our results will be important in developing molecular markers that can speed up the breeding for SSR resistance in Canadian grown soybean.

Soybean crop yield estimation using artificial intelligence techniques

It is common to observe conventional methods for estimating soybean crop yields, making the process slow and susceptible to human error. Therefore, the objective was to develop a model based on deep learning to estimate soybean yield using digital images obtained through a smartphone. To do this, the ability of the proposed model to correctly classify pods that have different numbers of grains, count the number of pods and grains, and then estimate the soybean crop yield was analyzed. As part of the study, two types of image acquisition were performed for the same plant. Image acquisition 1 (IA1) included capturing the images of the entire plant, pods, leaves, and branches. Image acquisition 2 (IA2) included capturing the images of the pods removed from the plant and deposited in a white container. In both acquisition methods, two soybean cultivars, TMG 7063 Ipro and TMG 7363 RR, were used. In total, combining samples from both cultivars, 495 images were captured, with each image corresponding to a sample (plant) obtained through methods AI1 and AI2. With these images, the total number of pods in the entire dataset was 46,385 pods. For the training and validation of the model, the data was divided into subsets of training, validation, and testing, representing, respectively, 80, 10, and 10% of the total dataset. In general, when using the data from IA2, the model presented errors of 7.50 and 5.32% for pods and grains, respectively. These values are considerably lower than when the model used the IA1 data, where it presented errors of 34.69 and 35.25% for pod and grain counts, respectively. Therefore, the data used from IA2 provide better results to the model.

Validation of Molecular Markers for Low Kunitz Trypsin Inhibitor Content in European Soybean (Glycine max L. Merr.) Germplasm.

Trypsin inhibitors (TI) in raw soybean grain, mainly represented by the Kunitz trypsin inhibitor protein (KTI), prevent the normal activity of the digestive enzymes trypsin and chymotrypsin in humans and monogastric livestock. The inactivation of TI is achieved through costly and time-consuming heat treatment. Thermal processing also impairs the solubility and availability of the soybean grain protein. Therefore, the genetic elimination of KTI has been proposed as a suitable alternative to heat treatment. The aim of this study was to screen the collection of European soybean cultivars with six genetic markers (one SSR marker and five SNP markers) previously proposed as tightly linked to the KTI3 gene encoding the major Kunitz trypsin inhibitor seed protein of soybean and validate their usability for marker-assisted selection (MAS). The six markers were validated on a subset of 38 cultivars with wide variability in KTI content and in the F2 and F3:5 progenies of two crosses between the known high- and low-KTI cultivars. Three genetic markers (SSR Satt228 and two SNP markers, Gm08_45317135_T/G and Gm08_45541906_A/C) were significantly associated with KTI content in a subset of 38 cultivars. Low-KTI alleles were detected in both low- and high-KTI genotypes and vice versa, high-KTI alleles were found in both high- and low-KTI genotypes, indicating a tight but not perfect association of these markers with the KTI3 gene. The genetic marker SSR Satt228 showed a significant association with KTI content in the F2 progeny, while the SNP markers Gm08_45317135_T/G and Gm08_45541906_A/C allowed significant discrimination between progeny with high- vs. low-KTI progenies in the F3:5 generation. These three markers could be applied in MAS for low-KTI content but not without the additional phenotyping step to extract the desired low-KTI genotypes.

Allelic variability in the Rpp1 locus conferring resistance to Asian soybean rust revealed by genome-wide association

Soybean is a crucial crop for the Brazilian economy, but it faces challenges from the biotrophic fungus Phakopsora pachyrhizi, which causes Asian Soybean Rust (ASR). In this study, we aimed to identify SNPs associated with resistance within the Rpp1 locus, which is effective against Brazilian ASR populations. We employed GWAS and re-sequencing analyzes to pinpoint SNP markers capable of differentiating between soybean accessions harboring the Rpp1, Rpp1-b and other alternative alleles in the Rpp1 locus and from susceptible soybean cultivars. Seven SNP markers were found to be associated with ASR resistance through GWAS, with three of them defining haplotypes that efficiently distinguished the accessions based on their ASR resistance and source of the Rpp gene. These haplotypes were subsequently validated using a bi-parental population and a diverse set of Rpp sources, demonstrating that the GWAS markers co-segregate with ASR resistance. We then examined the presence of these haplotypes in a diverse set of soybean genomes worldwide, finding a few new potential sources of Rpp1/Rpp1-b. Further genomic sequence analysis revealed nucleotide differences within the genes present in the Rpp1 locus, including the ULP1-NBS-LRR genes, which are potential R gene candidates. These results provide valuable insights into ASR resistance in soybean, thus helping the development of resistant soybean varieties through genetic breeding programs.

Temporal variability in soybean sowing and harvesting according to K-means and silhouette scores

Understanding the impact of seasonal variations on soybean productivity is crucial for optimizing agricultural practices. Given the influence of climatic factors such as temperature and rainfall on crop phenology, this study aims to analyze the effects of sowing and harvesting soybean cultivars in different seasons. This research investigates whether sowing soybeans in November and December leads to varying outcomes in terms of productivity and morphological characteristics, focusing on identifying the most stable cultivars across different climatic conditions. The study employed a comprehensive methodology, including data standardization, statistical tests (Levene, Shapiro-Wilk, ANOVA, Wilcoxon), and K-means clustering, to analyze 40 soybean cultivars across two seasons. Statistical preprocessing ensured data accuracy, while clustering helped identify cultivars with consistent responses to climatic changes. All computational analyses were performed using Python in the Google Colab environment. The findings revealed no significant difference in productivity between the two seasons, despite variations in temperature and rainfall. However, the moisture content of the grains (MTG) showed significant differences, influenced by higher rainfall in March and April and increased temperatures in December. K-means clustering highlighted SYN2282IPRO as the most stable cultivar and 77HO111I2X-GUAPORÉ as the most sensitive to climatic changes. The results emphasize the need for careful cultivar selection based on specific adaptability to seasonal variations. This study underscores the potential of computational tools like K-means clustering in agricultural optimization, offering a data-driven approach to selecting stable soybean cultivars. The adaptable methodology can be tailored to different geographical regions, soil types, and climate conditions, enhancing its relevance and applicability. These insights contribute to a better understanding of the complex interactions between climatic variables and soybean phenology, providing a foundation for improving agricultural practices in the face of climate change.

Assessment of the genetic parameters of soybean genotypes for precocity and productivity in the various cultivation conditions

Soybean (Glycine max [L.] Merr) plays a crucial role in the advancement of agriculture in Kazakhstan, serving as a promising food crop and feed source. The primary challenge in boosting soybean production in Northern Kazakhstan lies in the absence of soybean cultivars suited to the region's conditions. As such, the foremost focus of breeding initiatives should be on creating soybean varieties that possess both early maturity and satisfactory yield potential. The objective of this research was to assess the impact of maturity time (MT) on both the yield formation and the adaptive characteristics of soybean varieties from different origins. This evaluation was conducted by analyzing the outcomes of their testing under diverse cultivation conditions in the northern region of Kazakhstan. The soybean cultivars that were examined, originating from various sources, were classified into three primary groups. These groups varied in terms of their growing season duration as well as their yield levels. The way the alleles of the E1–E4 flowering genes were spread out in the identified clusters showed that for soybean varieties where recessive alleles of the E1–E4 genes build up, the growing season usually shorter. Cultivars of Chinese, Russian, and domestic selections isolated as a result of the research were good initial material for use in local breeding programs. Within the framework of the clusters, an environmental assessment of soybean accessions was carried out, which made it possible to determine their degree of plasticity and, in general, their adaptive potential in the conditions of Northern Kazakhstan. The best cultivars were the Chinese selection ‘Dongnong 63’ and the Russian selection ‘SIBNIIK 315’. Hence, the present study successfully discovered soybean cultivars that possess exceptional adaptability and flexibility. These cultivars hold significant potential for cultivation and practical use in the specific environmental circumstances of northern Kazakhstan.

The MADS-box transcription factor GmFULc promotes GmZTL4 gene transcription to modulate maturity in soybean.

Flowering time and maturity are crucial agronomic traits that affect the regional adaptability of soybean plants. The development of soybean cultivars with early maturity adapted to longer days and colder climates of high latitudes is very important for ensuring normal ripening before frost begins. FUL belongs to the MADS-box transcription factor family and has several duplicated members in soybeans. In this study, we observed that overexpression of GmFULc in the Dongnong 50 cultivar promoted soybean maturity, while GmFULc knockout mutants exhibited late maturity. Chromatin immunoprecipitation sequencing (ChIP-seq) and RNA sequencing (RNA-seq) revealed that GmFULc could bind to the CArG, bHLH and homeobox motifs. Further investigation revealed that GmFULc could directly bind to the CArG motif in the promoters of the GmZTL3 and GmZTL4 genes. Overexpression of GmZTL4 promoted soybean maturity, whereas the ztl4 mutants exhibited delayed maturity. Moreover, we found that the cis element box 4 motif of the GmZTL4 promoter, a motif of light response elements, played an important role in controlling the growth period. Deletion of this motif shortened the growth period by increasing the expression levels of GmZTL4. Functional investigations revealed that short-day treatment promoted the binding of GmFULc to the promoter of GmZTL4 and inhibited the expression of E1 and E1Lb, ultimately resulting in the promotion of flowering and early maturation. Taken together, these findings suggest a novel photoperiod regulatory pathway in which GmFULc directly activates GmZTL4 to promote earlier maturity in soybean.

Temperature and elevated CO2 alter soybean seed yield and quality, exhibiting transgenerational effects on seedling emergence and vigor.

Environmental conditions play a prime role in the growth and development of plant species, exerting a significant influence on their reproductive capacity. Soybean is sensitive to high temperatures during flowering and seed developmental stages. Little is known about the combined environmental effect of temperature and CO2 on seed yield and quality and its future generation. A study was conducted to examine the effect of temperature (22/14°C (low), 30/22°C (optimum), and 38/30°C (high)), and CO2 (420 ppm (ambient; aCO2) and 720 ppm (elevated; eCO2)) on seed yield, quality, and transgenerational seedling vigor traits of soybean cultivars (DS25-1 and DS31-243) using Soil-Plant-Atmospheric-Research facility. A significant temperature effect was recorded among yield and quality attributes. At high-temperature, the 100-seed weights of DS25-1 and DS31-243 declined by 40% and 24%, respectively, over the optimum temperature at aCO2. The harvest index of varieties reduced by 70% when exposed to high temperature under both aCO2 and eCO2, compared to the optimum temperature at aCO2. The seed oil (- 2%) and protein (8%) content altered when developed under high temperature under aCO2. Maximum sucrose (7.5%) and stachyose (3.8%) accumulation in seeds were observed when developed under low temperatures and eCO2. When the growing temperature increased from optimum to high, the seed oleic acids increased (63%), while linoleic and linolenic acids decreased (- 28% and - 43%, respectively). Significant temperature and CO2 effects were observed in progenies with the highest maximum seedling emergence (80%), lesser time to 50% emergence (5.5 days), and higher seedling vigor from parents grown at low-temperature treatment under eCO2. Exposure of plants to 38/30°C was detrimental to soybean seed yield, and eCO2 levels did not compensate for this yield loss. The high temperature during seed developmental stages altered the chemical composition of the seed, leading to an increased content of monounsaturated fatty acids. The findings suggest that parental stress can significantly impact the development of offspring, indicating that epigenetic regulation or memory repose may be at play.

Assessment of Germination and Seedling Development Factors of Soybean Cultivars in Different Salinity Levels

Salinity poses a significant abiotic stress factor that exerts detrimental effects on plant growth during germination and early seedling stages. The global prevalence of high salt concentration has transformed salinity into a serious problem, impacting vast expanses of land worldwide. This experiment aims to examine the effects of various concentrations of Sodium chloride (NaCl), including 200 mM, 150 mM, 50 mM, and 50 mM, on the seed development at early stage and germination of different cultivars of soybean to determine the variety with the highest value of tolerance, while exploring the underlying mechanisms responsible for salt tolerance in these plants. The parameters considered for measurement included relative injury rate, mean germination time, germination percentage, water uptake percentage, seedling height reduction, seedling biomass, and salt tolerance. Among these parameters, seedling height was highly affected with up to 72.58% reduction in 200 mM, followed by fresh weight and water uptake percentage. The parameters with minimum changes from 0 mM to 200 mM were mean germination time and relative injury rate. By assessing these parameters, a comprehensive understanding of the effects of salinity on soybean genotypes can be obtained. In conclusion, the study suggests that seedling traits are a reliable way to identify genotypes with increased tolerance to salinity stress by farmers according to the salinity situation in their soils.

A sucrose-binding protein and β-conglycinins regulate soybean seed protein content and control multiple seed traits.

Expanded agriculture production is required to support the world's population but can impose substantial environmental and climate change costs, particularly with intensifying animal production and protein demand. Shifting from an animal- to a plant-based protein diet has numerous health benefits. Soybean (Glycine max [L.] Merr.) is a major source of protein for human food and animal feed; improved soybean protein content and amino acid composition could provide high-quality soymeal for animal feed, healthier human foods, and a reduced carbon footprint. Nonetheless, during the soybean genome evolution, a balance was established between the amount of seed protein, oil, and carbohydrate content, burdening the development of soybean cultivars with high proteins (HPs). We isolated 2 high-seed protein soybean mutants, HP1 and HP2, with improved seed amino acid composition and stachyose content, pointing to their involvement in controlling seed rebalancing phenomenon. HP1 encodes β-conglycinin (GmCG-1) and HP2 encodes sucrose-binding protein (GmSBP-1), which are both highly expressed in soybean seeds. Mutations in GmSBP-1, GmCG-1, and the paralog GmCG-2 resulted in increased protein levels, confirming their role as general regulators of seed protein content, amino acid seed composition, and seed vigor. Biodiversity analysis of GmCG and GmSBP across 108 soybean accessions revealed haplotypes correlated with protein and seed carbohydrate content. Furthermore, our data revealed an unprecedented role of GmCG and GmSBP proteins in improving seed vigor, crude protein, and amino acid digestibility. Since GmSBP and GmCG are present in most seed plants analyzed, these genes could be targeted to improve multiple seed traits.

Growth and Yield Dynamics in Three Japanese Soybean Cultivars with Plant Growth-Promoting Pseudomonas spp. and Bradyrhizobium ottawaense Co-Inoculation.

Co-inoculation of soybeans with Bradyrhizobium and plant growth-promoting bacteria has displayed promise for enhancing plant growth, but concrete evidence of its impact on soybean yields is limited. Therefore, this study assessed the comparative efficacy of two 1-aminocyclopropane-1-carboxylate deaminase-producing Pseudomonas species (OFT2 and OFT5) co-inoculated with Bradyrhizobium ottawaense (SG09) on the growth, physiology, nodulation efficiency, and grain yield of three major Japanese soybean cultivars: Enrei, Fukuyutaka, and Satonohohoemi. The experiments were conducted in a warehouse under natural light conditions. The treatments included the inoculation of SG09, SG09 + OFT2, and SG09 + OFT5. Compared with Bradyrhizobium inoculation alone, co-inoculation led to significant improvements in nodulation efficiency, growth, and physiological performance in the Enrei and Fukuyutaka cultivars, but not in the Satonohohoemi cultivar. Furthermore, co-inoculation significantly boosted the total nitrogen content and ion uptake in the shoots, ultimately leading to a remarkable improvement in the grain yield in the Enrei and Fukuyutaka cultivars. These findings contribute to clarifying the interplay among Bradyrhizobium, Pseudomonas, and the plant host cultivar. Notably, Bradyrhizobium-Pseudomonas co-inoculation represents a potentially effective biofertilization strategy for soybean production, highlighting promising avenues for sustainable agricultural practices.

NMR Fingerprinting of Conventional and Genetically Modified Soybean Plants with AtAREB1 Transcription Factors.

Drought stress impacts soybean yields and physiological processes. However, the insertion of the activated form of the AtAREB1 gene in the soybean cultivar BR16, which is sensitive to water deficit, improved the drought response of the genetically modified plants. Thus, in this study, we used 1H NMR in solution and solid-state NMR to investigate the response of genetically modified soybean overexpressing AtAREB1 under water deficiency conditions. We achieved that drought-tolerant soybean yields high content of amino acids isoleucine, leucine, threonine, valine, proline, glutamate, aspartate, asparagine, tyrosine, and phenylalanine after 12 days of drought stress conditions, as compared to drought-sensitive soybean under the same conditions. Specific target compounds, including sugars, organic acids, and phenolic compounds, were identified as involved in controlling sensitive soybean during the vegetative stage. Solid-state NMR was used to study the impact of drought stress on starch and cellulose contents in different soybean genotypes. The findings provide insights into the metabolic adjustments of soybean overexpressing AREB transcription factors in adapting to dry climates. This study presents NMR techniques for investigating the metabolome of transgenic soybean plants in response to the water deficit. The approach allowed for the identification of physiological and morphological changes in drought-resistant and drought-tolerant soybean tissues. The findings indicate that drought stress significantly alters micro- and macromolecular metabolism in soybean plants. Differential responses were observed among roots and leaves as well as drought-tolerant and drought-sensitive cultivars, highlighting the complex interplay between overexpressed transcription factors and drought stress in soybean plants.

Modeling soybean growth: A mixed model approach.

The evaluation of plant and animal growth, separately for genetic and environmental effects, is necessary for genetic understanding and genetic improvement of environmental responses of plants and animals. We propose to extend an existing approach that combines nonlinear mixed-effects model (NLMEM) and the stochastic approximation of the Expectation-Maximization algorithm (SAEM) to analyze genetic and environmental effects on plant growth. These tools are widely used in many fields but very rarely in plant biology. During model formulation, a nonlinear function describes the shape of growth, and random effects describe genetic and environmental effects and their variability. Genetic relationships among the varieties were also integrated into the model using a genetic relationship matrix. The SAEM algorithm was chosen as an efficient alternative to MCMC methods, which are more commonly used in the domain. It was implemented to infer the expected growth patterns in the analyzed population and the expected curves for each variety through a maximum-likelihood and a maximum-a-posteriori approaches, respectively. The obtained estimates can be used to predict the growth curves for each variety. We illustrate the strengths of the proposed approach using simulated data and soybean plant growth data obtained from a soybean cultivation experiment conducted at the Arid Land Research Center, Tottori University. In this experiment, plant height was measured daily using drones, and the growth was monitored for approximately 200 soybean cultivars for which whole-genome sequence data were available. The NLMEM approach improved our understanding of the determinants of soybean growth and can be successfully used for the genomic prediction of growth pattern characteristics.

Divergent evolution of NLR genes in the genus Glycine: impacts of annuals and perennials' life history strategies.

Within the family Fabaceae, the genus Glycine is composed of two subgenera annuals (2n=40) and perennials. This life strategy transition may have differentially affected the evolution of various gene families. Its cultivated species G. max has high level of susceptibility to major pathogens including viruses, bacteria and fungi. Understanding nucleotide-binding domain leucine-rich repeat (NLR) genes evolution in soybean is of paramount importance due to their central role in plant immunity and their potential in improving disease resistance in soybean cultivars. In this study, we investigated the significance of this annual-perennial transition on the macroevolution of NLR genes in the genus Glycine. Our results reveal a remarkable distinction between annual species such as Glycine max and Glycine soja, which exhibit an expanded NLRome compared to perennial species (G. cyrtoloba, G. stenophita, G.dolichocarpa, G. falcata, G. syndetika, G. latifolia and G. tomentella). Our evolutionary timescale analysis pinpoints recent accelerated gene duplication events for this expansion, which occurred between 0.1 and 0.5 million years ago, driven predominantly by lineage-specific and terminal duplications. In contrast, perennials initially experienced significant contraction during the diploidisation phase following the Glycine-specific whole-genome duplication event (~10 million years ago). Despite the reduction in the NLRome, perennial lineages exhibit a unique and highly diversified repertoire of NLR genes with limited interspecies synteny. The investigation of gene gain and loss ratios revealed that this diversification resulted from the birth of novel genes following individual speciation events. Among perennials, G. latifolia, a well-known resistance resource, has the highest ratio of these novel genes in the tertiary gene pool. Our study suggests evolutionary mechanisms, including recombination and transposition, as potential drivers for the emergence of these novel genes. This study also provides evidence for the unbalanced expansion of the NLRome in the Dt subgenome compared with the At subgenome in the young allopolyploid G.dolichocarpa. To the best of our knowledge, this is the first study to investigate the effect of annuality and perenniality life transition on the evolution of NLR genes in the genus Glycine to identify its genomics resources for improving the resistance of soybean crop with global importance on the economy and food security.

Comparative Transcriptomic Analysis of Soybean Cyst Nematode Inbred Populations Non-adapted or Adapted on Soybean rhg1-a/Rhg4-Mediated Resistance.

Soybean cyst nematode (SCN, Heterodera glycines) is most effectively managed through planting resistant soybean cultivars, but the repeated use of the same resistance sources has led to a widespread emergence of virulent SCN populations that can overcome soybean resistance. Resistance to SCN HG type 0 (Race 3) in soybean cultivar Forrest is mediated by an epistatic interaction between the soybean resistance genes rhg1-a and Rhg4. We previously developed two SCN inbred populations by mass-selecting SCN HG type 0 (Race 3) on susceptible and resistant recombinant inbred lines, derived from a cross between Forrest and the SCN-susceptible cultivar Essex, which differ for Rhg4. To identify SCN genes potentially involved in overcoming rhg1-a/Rhg4-mediated resistance, we conducted RNA sequencing on early parasitic juveniles of these two SCN inbred populations infecting their respective hosts, only to discover a handful of differentially expressed genes (DEGs). However, in a comparison with early parasitic juveniles of an avirulent SCN inbred population infecting a resistant host, we discovered 59 and 171 DEGs uniquely up- or downregulated in virulent parasitic juveniles adapted on the resistant host. Interestingly, the proteins coded by these 59 DEGs included vitamin B-associated proteins (reduced folate carrier, biotin synthase, and thiamine transporter) and nematode effectors known to play roles in plant defense suppression, suggesting that virulent SCN may exert a heightened transcriptional response to cope with enhanced plant defenses and an altered nutritional status of a resistant soybean host. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Registration of high‐yielding, high‐protein soybean germplasm USDA‐N7007 derived from wild soybean PI 366122

AbstractUSDA‐N7007 is a non‐GM, maturity group (MG) VII soybean [Glycine max (L.) Merr.] (Reg. no. GP‐529, PI 705147) germplasm released by the USDA Agricultural Research Service in conjunction with the North Carolina Agricultural Research Service in December of 2023. USDA‐N7007 is a high‐yielding, high‐protein germplasm derived from wild soybean (Glycine soja Siebold &amp; Zucc; PI 366122) and small‐seeded MG VII USDA cultivar N7103. Over 47 combined testing environments of the USDA Southern Uniform and USB Protein Diversity Tests (2018–2021), USDA‐N7007 yielded 98% of the check mean and 102% of the test mean. The average protein content of USDA‐N7007 was significantly higher (432 g kg−1) than the average check means of 402 g kg−1 and 413 g kg−1 in the USDA Southern Uniform and USB Protein Diversity Tests, respectively. Across both tests (2019–2021), the release was significantly (p &lt; 0.05) higher in protein (+7 g kg−1), with 9% higher seed yield (+242 kg ha−1) than the recurrent parent N7103. USDA‐N7007 is resistant to lodging, southern root‐knot nematode, and stem canker. To the best of our knowledge, this is the first US release clearly demonstrating that the wild soybean genome can be incorporated into an elite cultivar to increase seed protein without a negative effect on seed yield. This release is a truly novel and valuable resource for development of future US soybean cultivars because it will be useful to improve both genetic diversity and seed protein simultaneously without a negative effect on seed yield.

Genetic diversity of 30 soybean cultivars based on microsatellite markers

Abstract Increasing soybean production presents a significant challenge within soybean breeding endeavors. The foundation for achieving success in plant breeding lies in comprehensive knowledge of genetic diversity. Thus, this study aimed to assess the genetic diversity among 30 soybean cultivars by employing microsatellite markers. DNA extraction was conducted using a modified version of the Doyle &amp; Doyle method, followed by amplification of each sample with nine pairs of microsatellite primers. Gel visualization of the amplified samples facilitated scoring, distinguishing between polymorphic and monomorphic primers. The analysis unveiled the detection of 59 alleles, varying from 2 to 15 alleles per locus, with an average of 6.6 alleles per marker. The resulting gene diversity averaged at 0.63, with a mean main allele frequency of 0.44. Moreover, the obtained PIC values ranged from 0.18 to 0.92, with an average value of 0.60. Notably, four microsatellite markers exhibited high informativity (PIC &gt; 0.7). Cluster analysis based on genetic similarity coefficients grouped the 30 soybean cultivars into three main clusters, demonstrating the genetic variability within the utilized soybean genetic material.

Поиск информативных SSR-маркеров для паспортизации сортов сои

Soybean is one of the important crop contributing to food security. The development of new soybean cultivars and their including into the State Register will be confirmed by genetic passportization. The purpose of the research was a search of informative SSR-loci too add the existing system of DNA-markers for soybean passportization. We selected 27 SSR-loci from SoyBase using an online instrument Primer-BLAST. The information capacity of microsatellite loci was estimated in 20 soybean cultivars. PCR-products were divided in PAAG in denaturing conditions. We allocated 13 highly informative (PIC 0.50–0.72) and five informative (PIC 0.44–0.49) microsatellite loci from 27 ones selected in silico. Selected in the research loci can be used for genotyping and jointly with tested earlier DNA-markers for soybean passportization.

Seed Longevity of Soybean (Glycine max L.) Cultivars Under Lightless Storage

Soybean seeds in tropical countries are prone to rapid deterioration due to environmental condition during storage, leading to a decrease in seed quality and ultimately resulting in low potential yield. Longevity of seed during storage is influenced by genetic and environmental factors such as light. Therefore, this study aimed to determine the effect of light on the vigour of two soybean seeds cultivars (Demas 1 &amp; Devon 1 cvs) stored for three months. The investigation was conducted from February to May 2022 at Seed Technology Laboratory, Faculty of Agriculture, Universitas Padjadjaran. A correlational method was employed to assess the relationship between seed quality of Demas 1 and Devon 1 in light and lightless storage. Furthermore, data were analyzed using correlation regression and t-test to compare the two populations. The results showed that there was a high correlation between the physical and physiological quality of seeds. There were also differences in seed response to light, and this was observed from the moisture content, weight of 100 seeds, germination rate, and simultaneous growth percentage traits. Considering the seed quality traits, Demas 1 had the best vigour value after storage in dark conditions. It is worth noting that both cultivars exhibited signs of deterioration during storage. However, the rate of deterioration was slowed down due to lightless condition.

Attracting Scelionidae egg parasitoids to enhance stink bug egg parasitisation in soybean crops using methyl salicylate and (E,E)-α-farnesene.

Plant volatile organic compounds (VOCs) play a crucial role in mediating interactions between plants, herbivores and natural enemies. Among these VOCs, methyl salicylate and (E,E)-α-farnesene are emitted as herbivore-induced plant volatiles (HIPVs) by soybean plants in response to feeding by the brown stink bug Eushistus heros. These HIPVs function as synomones, influencing the foraging behaviour of the egg parasitoid, Telenomus podisi, the main natural enemy of E. heros, one of the major soybean pests in Brazil. Laboratory experiments showed that two soybean cultivars, BRS 7580 and BRS 7880, produced similar qualitative blends of HIPVs, with methyl salicylate, (E,E)-α-farnesene and (Z)-3-hexenyl acetate being produced by both cultivars. Soybean cultivar BRS 7580 produced a significant lower amount of HIPVs compared to BRS 7880 but this difference did not affect the attractiveness of the egg parasitoid Telenomus podisi. Field experiments using these two cultivars and synthetic applications of methyl salicylate and (E,E)-α-farnesene showed a substantial increase in egg parasitism in all treated areas. Parasitism rates ranged from 50% to 80% in areas where these HIPVs were deployed, compared to only 10% in untreated control areas. The egg parasitoid Telenomus podisi demonstrated an adept ability in recognising between HIPVs in soybean blends, even in the presence of significant quantitative differences. The results from the field experiment showed the potential of HIPVs in attracting natural enemies to specific target areas within fields. (E,E)-α-Farnesene showed an improved action during the later stages of soybean growth, notably at R6. In addition, this volatile attracted other families of natural enemies. © 2024 Society of Chemical Industry.