Soybean Cultivars Research Articles

A Holistic Approach to the Selection of Soybean (Glycine max) Cultivars for Shade Environments Based on Morphological, Yield and Genetic Traits

ABSTRACTThe reduction of photosynthetically active radiation impacts the growth and productivity of soybean in agroforestry and intercropping systems. Thus, this report explored the responses of 16 soybean cultivars submitted to shade levels in field conditions. Multi‐faceted and relative importance analyses revealed that the steam diameter and plant height are fundamental morphological markers for selecting shade‐resilient cultivars, both were high and positively correlated to yield components. Moreover, the responses to shade varied among soybean cultivars, with certain genotypes demonstrating distinct tolerance levels, which allowed also the estimative of genetic variance that revealed strong participation of genetic components in responses to shade. Multivariate and clustering analysis using steam diameter and plant height in combination with two yield components resulted in the identification of four soybean cultivars more tolerant to shade environments and two sensible. Therefore, this report provides insights into soybean cultivation under varying light conditions, provides a robust foundation for the integration of morphological and yield markers in breeding programmes focused on shade tolerance and guides future endeavours in crop improvement for optimal and sustainable yield and resilience in the climate change context.

The Correlation between Maturity, Plant Architecture and Yield Related Traits of Soybean Cultivars in Northern China

The Correlation between Maturity, Plant Architecture and Yield Related Traits of Soybean Cultivars in Northern China

Use of Phenomics in the Selection of UAV-Based Vegetation Indices and Prediction of Agronomic Traits in Soybean Subjected to Flooding

Flooding is a frequent environmental stress that reduces soybean growth and grain yield in many producing areas in the world, such as the United States, Southeast Asia, and Southern Brazil. In these regions, soybean is frequently cultivated in lowland areas in crop rotation with rice, which provides numerous technical, economic, and environmental benefits. In this context, the identification of the most important spectral variables for the selection of more flooding-tolerant soybean genotypes is a primary demand within plant phenomics, with faster and more reliable results enabled using multispectral sensors mounted on unmanned aerial vehicles (UAVs). Accordingly, this research aimed to identify the optimal UAV-based multispectral vegetation indices for characterizing the response of soybean genotypes subjected to flooding and to test the best linear model fit in predicting tolerance scores, relative maturity group, biomass, and grain yield based on phenomics analysis. Forty-eight soybean cultivars were sown in two environments (flooded and non-flooded). Ground evaluations and UAV-image acquisition were conducted at 13, 38, and 69 days after flooding and at grain harvest, corresponding to the phenological stages V8, R1, R3, and R8, respectively. Data were subjected to variance component analysis and genetic parameters were estimated, with stepwise regression applied for each agronomic variable of interest. Our results showed that vegetation indices behave differently in their suitability for more tolerant genotype selection. Using this approach, phenomics analysis efficiently identified indices with high heritability, accuracy, and genetic variation (>80%), as observed for MSAVI, NDVI, OSAVI, SAVI, VEG, MGRVI, EVI2, NDRE, GRVI, BNDVI, and RGB index. Additionally, variables predicted based on estimated genetic data via phenomics had determination coefficients above 0.90, enabling the reduction in the number of important variables within the linear model.

High-quality genome of a modern soybean cultivar and resequencing of 547 accessions provide insights into the role of structural variation.

Soybean provides protein, oil and multiple health-related compounds. Understanding the effects of structural variations (SVs) on economic traits in modern breeding is important for soybean improvement. Here we assembled the high-quality genome of modern cultivar Nongdadou2 (NDD2) and identified 25,814 SV-gene pairs compared to 29 reported genomes, with 13 NDD2-private SVs validated in 547 deep-resequencing (average = 18.05-fold) accessions, which advances our understanding of genomic variation biology. We found some insertions/deletions involved in seed protein and weight formation, an inversion related to adaptation to drought and a large intertranslocation implicated in a key divergence event in soybean. Of 749,714 SVs from 547 accessions, 6,013 were significantly associated with 22 yield-related and seed-quality-related traits determined in ten location × year environments. We uncovered 1,761 associated SVs that hit genes or regulatory regions, with 12 in GmMQT influencing oil and isoflavone contents. Our work provides resources and insights into SV roles in soybean improvement.

Identification of quantitative trait loci of pod dehiscence in a collection of soybean grown in the southeast of Kazakhstan.

Soybean [Glycine max (L.) Merr.] is one of the important crops that are constantly increasing their cultivation area in Kazakhstan. It is particularly significant in the southeastern regions of the country, which are currently predominant areas for cultivating this crop. One negative trait reducing yield in these dry areas is pod dehiscence (PD). Therefore, it is essential to understand the genetic control of PD to breed new cultivars with high yield potential. In this study, we evaluated 273 soybean accessions from different regions of the world for PD resistance in the conditions of southeastern regions of Kazakhstan in 2019 and 2021. The field data for PD suggested that 12 accessions were susceptible to PD in both studied years, and 32 accessions, in one of the two studied years. The genotyping of the collection using a DNA marker for the Pdh1 gene, a major gene for PD, revealed that 244 accessions had the homozygous R (resistant) allele, 14 had the homozygous S (susceptible) allele, and 15 accessions showed heterozygosity. To identify additional quantitative trait loci (QTLs), we applied an association mapping study using a 6K SNP Illumina iSelect array. The results suggested that in addition to major QTL on chromosome 16, linked to the physical location of Pdh1, two minor QTLs were identified on chromosomes 10 and 13. Both minor QTLs for PD were associated with calmodulin-binding protein, which presumably plays an important role in regulating PD in dry areas. Thus, the current study provided additional insight into PD regulation in soybean. The identified QTLs for PD can be efficiently employed in breeding for high-yield soybean cultivars.

How do drought and heat affect the response of soybean seed yield to elevated O3? An analysis of 15 seasons of free-air O3 concentration enrichment studies.

The coincidence of rising ozone concentrations ([O3]), increasing global temperatures, and drought episodes is expected to become more intense and frequent in the future. A better understanding of the responses of crop yield to elevated [O3] under different levels of drought and high temperature stress is, therefore, critical for projecting future food production potential. Using a 15-year open-air field experiment in central Illinois, we assessed the impacts of elevated [O3] coupled with variation in growing season temperature and water availability on soybean seed yield. Thirteen soybean cultivars were exposed to a wide range of season-long elevated [O3] in the field using free-air O3 concentration enrichment. Elevated [O3] treatments reduced soybean seed yield from as little as 5.3% in 2005 to 35.2% in 2010. Although cultivars differed in yield response to elevated [O3] (R), ranging from 17.5% to -76.4%, there was a significant negative correlation between R and O3 dosage. Soybean cultivars showed greater seed yield losses to elevated [O3] when grown at drier or hotter conditions compared to wetter or cooler years, because the hotter and drier conditions were associated with greater O3 treatment. However, year-to-year variation in weather conditions did not influence the sensitivity of soybean seed yield to a given increase in [O3]. Collectively, this study quantitatively demonstrates that, although drought conditions or warmer temperatures led to greater O3 treatment concentrations and O3-induced seed yield reduction, drought and temperature stress did not alter soybean's sensitivity to O3. Our results have important implications for modeling the effects of rising O3 pollution on crops and suggest that altering irrigation practices to mitigate O3 stress may not be effective in reducing crop sensitivity to O3.

The Effect of Use of Cow Manure on the Growth of Two Cultivars of Glycine Max L. Using a Verticulture Planting System

This study aims to provide data on the verticulture method planting and the use of cow manure to black soybeans (Glycine max L.). This study used a factorial Randomized Block Design (RAK) containing two factorials and four replications. K1 refers to the unit 1 soybean cultivar, while K2 stands for the pearl 2 cultivar. One of the cultivar factors is this (K). Inside the interval (P), we find three values: P1= 0 kg, P2= 0.18 kg, and P3= 0.32 kg. “Among the variables that underwent changes were plant height, leaf count, leaf area index, chlorophyll content, relative growth rate (LPR), net assimilation rate (LAB), and active root nodules. According to the results, there was no significant difference between using 0.16 kg/bed of organic fertilizer or no fertilizer at all when measuring plant height at 7, 14, 21, 28, 35, and 42 HST for Cultivar K1 (detam 1)”. The availability of organic fertilizer at 0.32 kg/bed was significantly affected by manure at 7, 14, 21, 28, 35, and 42 HST at the third dosage. The results of this study show that neither cultivar 1 nor pearl cultivar 2 had any discernible impact on the vegetative development of black soybean plants when manure was applied at dosages of 0 kg, 0.16 kg, and 0.32 kg.

Small Black Soybean Cultivar ‘Seum’ with High Yield and Lodging Tolerance

Small Black Soybean Cultivar ‘Seum’ with High Yield and Lodging Tolerance

Identification of candidate genes and genomic prediction of soybean fatty acid components in two soybean populations.

Soybean, a source of plant-derived lipids, contains an array of fatty acids essential for health. A comprehensive understanding of the fatty acid profiles in soybean is crucial for enhancing soybean cultivars and augmenting their qualitative attributes. Here, 180 F10 generation recombinant inbred lines (RILs), derived from the cross-breeding of the cultivated soybean variety 'Jidou 12' and the wild soybean 'Y9,' were used as primary experimental subjects. Using inclusive composite interval mapping (ICIM), this study undertook a quantitative trait locus (QTL) analysis on five distinct fatty acid components in the RIL population from 2019 to 2021. Concurrently, a genome-wide association study (GWAS) was conducted on 290 samples from a genetically diverse natural population to scrutinize the five fatty acid components during the same timeframe, thereby aiming to identify loci closely associated with fatty acid profiles. In addition, haplotype analysis and the Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed to predict candidate genes. The QTL analysis elucidated 23 stable QTLs intricately associated with the five fatty acid components, exhibiting phenotypic contribution rates ranging from 2.78% to 25.37%. In addition, GWAS of the natural population unveiled 102 significant loci associated with these fatty acid components. The haplotype analysis of the colocalized loci revealed that Glyma.06G221400 on chromosome 6 exhibited a significant correlation with stearic acid content, with Hap1 showing a markedly elevated stearic acid level compared with Hap2 and Hap3. Similarly, Glyma.12G075100 on chromosome 12 was significantly associated with the contents of oleic, linoleic, and linolenic acids, suggesting its involvement in fatty acid biosynthesis. In the natural population, candidate genes associated with the contents of palmitic and linolenic acids were predominantly from the fatty acid metabolic pathway, indicating their potential role as pivotal genes in the critical steps of fatty acid metabolism. Furthermore, genomic selection (GS) for fatty acid components was conducted using ridge regression best linear unbiased prediction based on both random single nucleotide polymorphisms (SNPs) and SNPs significantly associated with fatty acid components identified by GWAS. GS accuracy was contingent upon the SNP set used. Notably, GS efficiency was enhanced when using SNPs derived from QTL mapping analysis and GWAS compared with random SNPs, and reached a plateau when the number of SNP markers exceeded 3,000. This study thus indicates that Glyma.06G221400 and Glyma.12G075100 are genes integral to the synthesis and regulatory mechanisms of fatty acids. It provides insights into the complex biosynthesis and regulation of fatty acids, with significant implications for the directed improvement of soybean oil quality and the selection of superior soybean varieties. The SNP markers delineated in this study can be instrumental in establishing an efficacious pipeline for marker-assisted selection and GS aimed at improving soybean fatty acid components.

Effects of Trichoderma harzianum and Bacillus subtilis on the root and soil microbiomes of the soybean plant INTACTA RR2 PRO™.

Soybean is a significant export product for several countries, including the United States and Brazil. There are numerous varieties of soybean. Among them, a genetically modified type known as INTACTA RR2 PRO™ has been designed to demonstrate resistance to glyphosate and to produce toxins that are lethal to several species of caterpillars. Limited information is available on the use of Trichoderma harzianum and Bacillus subtilis to promote plant growth and their impact on the plant microbiome. This study aimed to evaluate the effects of these microorganisms on this soybean cultivar by analyzing parameters, such as root and shoot dry matter, nutritional status, and root and soil microbial diversity. The results indicated that treatments with B. subtilis alone or in combination with T. harzianum as seed or seed and soil applications significantly enhanced plant height and biomass compared to the other treatments and the control. No significant differences in phosphorus and nitrogen concentrations were detected across treatments, although some treatments showed close correlations with these nutrients. Microbial inoculations slightly influenced the soil and root microbiomes, with significant beta diversity differences between soil and root environments, but had a limited overall impact on community composition. The combined application of B. subtilis and T. harzianum particularly enhanced plant growth and promoted plant-associated microbial groups, such as Rhizobiaceae, optimizing plant-microbe interactions. Furthermore, the treatments resulted in a slight reduction in fungal richness and diversity.

Differential susceptibility of Spodoptera frugiperda (Lepidoptera: Noctuidae) to single versus pyramided Bt traits in Brazilian soybean: what doesn't kill you makes you stronger?

Lepidopteran pest control in agriculture has become heavily dependent on cultivars that express Bacillus thuringiensis (Bt) toxins as 'plant-incorporated protectants'. However, populations of Spodoptera frugiperda (Smith) in Brazil appear resistant to the Bt traits currently available in commercial soybean cultivars. This study evaluated S. frugiperda life history when feeding on three different Bt soybean cultivars. Cultivars expressing Cry1Ac + Cry1F and Cry1A.105 + Cry2Ab2 + Cry1Ac Bt toxins caused 100% larval mortality in S. frugiperda. Both non-Bt and Cry1Ac-expressing soybean induced transgenerational effects that increased the survival of subsequent generations. A Cry1Ac soybean diet reduced the generation time (T) of S. frugiperda relative to non-Bt soybean, resulting in shorter generation time and more rapid population growth. The implications of these results revealed how diet can alter aspects of insect life history and biology, and have important implications for sustainable management of S. frugiperda on soybean. © 2024 Society of Chemical Industry.

Responses of Leaf Expansion, Plant Transpiration and Leaf Senescence of Different Soybean (Glycine max. (L.) Merr.) Genotypes to Soil Water Deficit

ABSTRACTThe responses of eco‐physiological processes such as leaf expansion, plant transpiration and senescence to soil water deficit have been reported to be genotype‐dependent in different crops. To study such responses in soybean (Glycine max. (L.) Merr.), a 2‐year (2017 and 2021) outdoor pot experiment was carried out on the Heliaphen automated phenotyping platform at INRAE in Toulouse (France). Six soybean cultivars (Sultana‐MG 000, ES Pallador‐MG I, Isidor‐MG I, Santana‐MG I/II, Blancas‐MG II and Ecudor‐MG II) belonging to four maturity groups (MG) commonly grown in Europe were subjected to progressive soil water deficit from the reproductive stage R1 for 17 and 23 days in 2017 and 2021, respectively. The fraction of transpirable soil water (FTSW) was used as an indicator of soil water deficit. Non‐linear regression was used to calculate FTSWt, that is, the FTSW threshold for which the rate of the eco‐physiological process in stressed plants starts to diverge from a reference value. According to FTSWt, the three eco‐physiological processes showed significant differences in sensitivity to water deficit: leaf expansion exhibits the highest sensitivity and the widest range (FTSWt: 0.44–0.93), followed by plant transpiration (FTSWt: 0.17–0.56), with leaf senescence showing the narrowest range (FTSWt: 0.05–0.16). Among six cultivars, regarding leaf expansion, Cvs Santana (FTSWt = 0.48 in 2017; FTSWt = 0.44 in 2021), Blancas (FTSWt = 0.51 in 2017; FTSWt = 0.48 in 2021) and Ecudor (FTSWt = 0.46 in 2017; FTSWt = 0.52 in 2021) in late MGs (I/II to II) exhibited higher tolerance to soil drying. Conversely, the cv. Sultana in the earliest MG (000) showed the highest sensitivity (FTSWt = 0.91 in 2017; FTSWt = 0.93 in 2021) to water deficit. However, concerning the FTSWt values for plant transpiration (0.17–0.56 in 2017; 0.19–0.31 in 2021) and senescence (0.05–0.16 in 2017; 0.06–0.16 in 2021), their range did not demonstrate a correlated trend with the MG. In addition, a negative linear correlation was observed between values of FTSWt of normalised leaf expansion at the whole‐plant level (NLE) and specific leaf area (SLA) measured on irrigated plants for both years. This suggests that genotypes with high values of SLA could be associated with higher tolerance of leaf expansion to soil water deficit. Such a non‐destructive phenotyping method under outdoor conditions could bring new information to variety testing process and provide paths for integrating genotypic variability into crop growth models used for simulating soybean eco‐physiological responses to water deficit across the plant, field and even regional scales.

Identification of QTLs and candidate genes for water-soluble protein content in soybean seeds

Soybean represents a vital source of premium plant-based proteins for human nutrition. Importantly, the level of water-soluble protein (WSP) is crucial for determining the overall quality and nutritional value of such crops. Enhancing WSP levels in soybean plants is a high-priority goal in crop improvement. This study aimed to elucidate the genetic basis of WSP content in soybean seeds by identifying quantitative trait loci (QTLs) and set the foundation for subsequent gene cloning and functional analysis. Using 180 F10 recombinant inbred lines generated by crossing the high-protein soybean cultivar JiDou 12 with the wild variety Ye 9, our researcher team mapped the QTLs influencing protein levels, integrating Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene expression profiling to identify candidate genes. During the 2020 and 2022 growing seasons, a standard bell-shaped distribution of protein content trait data was observed in these soybean lines. Eight QTLs affecting protein content were found across eight chromosomes, with LOD scores ranging from 2.59 to 7.30, explaining 4.15–11.74% of the phenotypic variance. Notably, two QTLs were newly discovered, one with a elite allele at qWSPC-15 from Ye 9. The major QTL, qWSPC-19, on chromosome 19 was stable across conditions and contained genes involved in nitrogen metabolism, amino acid biosynthesis, and signaling. Two genes from this QTL, Glyma.19G185700 and Glyma.19G186000, exhibited distinct expression patterns at maturity, highlighting the influence of these genes on protein content. This research revealed eight QTLs for WSP content in soybean seeds and proposed a gene for the key QTL qWSPC-19, laying groundwork for gene isolation and enhanced soybean breeding through the use of molecular markers. These insights are instrumental for developing protein-rich soybean cultivars.

Soybean production in SEALBA: inoculation, co-inoculation, and starter nitrogen fertilization

The grain production area in the Brazilian agricultural region known as SEALBA, especially in Alagoas State, has seen significant growth in recent years. This study aims to contribute to sustainable regional development by evaluating the effects of inoculation, co-inoculation, and the application of starter mineral nitrogen (N), either individually or in combination, on soybean growth and yield. Eight field experiments were conducted from 2018 to 2021 in two municipalities within Alagoas, covering soybean cultivation areas ranging from the first to the fourth year. The experiments followed a randomized complete block design with four replications, employing a factorial arrangement of treatments. The first factor encompassed five levels related to inoculation technologies and N management: 1) Inoculation with Bradyrhizobium; 2) Inoculation with Bradyrhizobium combined with N basal fertilization; 3) Co-inoculation of Bradyrhizobium + Azospirillum; 4) Co-inoculation of Bradyrhizobium + Azospirillum + N fertilization at the base; and 5) Control treatment without microbiological inputs or nitrogen fertilizers. The second factor involved the evaluation of different soybean cultivars, with two materials assessed in 2018 and three cultivars in 2019, 2020, and 2021. Results demonstrated that seed inoculation with Bradyrhizobium led to increased soybean grain yield in first-year cultivation areas. However, N basal fertilization, commonly known as starter fertilization, did not result in yield improvements compared to the use of microbiological inputs alone. Soybean cultivars BRS 9383 IPRO and FTR 3191 IPRO exhibited greater responsiveness to seed inoculation with Bradyrhizobium.

Assessing Soybean Cultivar Resistance to Target Spot Using a Detached Leaf Assay

Target spot (TS), caused by the fungus Corynespora cassiicola, is a foliar disease of increasing importance to soybean in the US. Identifying cultivar resistance to TS is challenging. The objective of this research was to determine the reactions of a diverse collection of soybean genotypes to target spot using a detached leaf inoculation method. A detached unifoliate leaf of each soybean genotype was placed in a Petri dish on moist filter paper, wounded at three locations, inoculated with 10 μl, of a 105 conidial suspension of C. cassiicola, and incubated at room temperature (23°C). The percent leaf area with TS symptoms (TSS) was measured digitally 7, 10, 14, and 17 days after inoculation (DAI) and the area under the disease progress curve (AUDPC) calculated. Thirty-seven soybean genotypes and three soybean cultivars were evaluated in three replicated trials. At 17 DAI, target spot symptoms ranged from 2 to 84% TSS. Significant differences occurred between soybean genotypes at each rating time in each trial. Across the three trials, the reaction of most soybean genotypes ranged from resistant to susceptible. These soybean genotypes were evaluated in the field with natural inoculum at two locations in 2022. Target spot developed late but differed significantly between genotypes averaging from 0.35 to 3.35% TSS. Field results were not significantly correlated to the detached leaf results. The detached leaf assay is another tool for screening soybean genotypes for resistance to TS but needs field validation.

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.

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.