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Soybean is a major crop in the world and an essential source for minerals, including iron (Fe) and zin (Zn). Deficiency of Fe and Zn in soil and soybean plants result in yield loss and poor seed nutritional qualities. Information on genomic regions and candidate genes controlling seed Fe and Zn accumulation in soybean seed is limited. Therefore, The objective of this research was to identify genetic regions, known as quantitative trait loci (QTL), and candidate genes that control the accumulation of Fe and Zn in soybean mature seeds. A ‘Forrest’ by ‘Williams 82’ (F × W82) recombinant inbred line (RIL) population (n = 306) was used and genotyped using a total of 5405 single nucleotides polymorphism (SNP) markers using Infinium SNP6K BeadChips. A two-year experiment was conducted across two environments: North Carolina in 2018 (NC) and Illinois in 2020 (IL). Only QTL with LOD scores ≥ 2.5, as identified by the composite interval mapping (CIM) method, are reported here. In total, 6 QTL were identified for seed Fe; specifically, 3 QTL (qFe-01-[NC-2018], qFe-02-[NC-2018], and qFe-03-[NC-2018]) were located on chromosomes 1, 2, and 6, respectively, in the NC environment, and 3 QTL (qFe-01-[IL-2020], qFe-02-[IL-2020], and qFe-03-[IL-2020]) were positioned on chromosomes 1, 2, and 12, respectively, in the IL environment. A total of 6 QTL associated with seed Zn were also identified; 4 QTL (qZn-01-[NC-2018]; qZn-02-[NC-2018]; qZn-03-[NC-2018]; and qZn-04-[NC-2018]), respectively on Chr 2, 3, 7, and 19 in NC; and 2 QTL (qZn-01-[IL-2020] and qZn-02-[IL-2020]), respectively, on Chr 5 and 8 in IL. Several functional genes encode Fe- and Zn-proteins, transcription factors, proteins-zinc finger motifs (involved in DNA binding and transcriptional regulation; crosstalk between the regulatory pathways of Zn and Fe transporters) were identified and located within the QTL interval. To our knowledge, and based on the literature available, the QTL identified here on Chr 2 and Chr 6 are novel and were not previously identified. This current research provides a new knowledge of the genetic basis of seed Fe and Zn and the markers associated with QTL. The QTL identified here will contribute to efficient marker assisted selection for higher Fe and Zn content in soybean seeds. The candidate genes and metal-responsive transcription factors may coordinate the expression of both Zn and Fe transporters in response to changes in metal availability, providing new knowledge on minerals uptake and transport mechanisms, allowing for possible genetic engineering application.

Understanding the genetic basis of seed Ni and Mo is essential. Since soybean is a major crop in the world and a major source for nutrients, including Ni and Mo, the objective of the current research was to map genetic regions (quantitative trait loci, QTL) linked to Ni and Mo concentrations in soybean seed. A recombinant inbred line (RIL) population was derived from a cross between ‘Forrest’ and ‘Williams 82’ (F × W82). A total of 306 lines was used for genotyping using 5405 single nucleotides polymorphism (SNP) markers using Infinium SNP6K BeadChips. A two-year experiment was conducted and included the parents and the RIL population. One experiment was conducted in 2018 in North Carolina (NC), and the second experiment was conducted in Illinois in 2020 (IL). Logarithm of the odds (LOD) of ≥2.5 was set as a threshold to report identified QTL using the composite interval mapping (CIM) method. A wide range of Ni and Mo concentrations among RILs was observed. A total of four QTL (qNi-01, qNi-02, and qNi-03 on Chr 2, 8, and 9, respectively, in 2018, and qNi-01 on Chr 20 in 2020) was identified for seed Ni. All these QTL were significantly (LOD threshold > 2.5) associated with seed Ni, with LOD scores ranging between 2.71–3.44, and with phenotypic variance ranging from 4.48–6.97%. A total of three QTL for Mo (qMo-01, qMo-02, and qMo-03 on Chr 1, 3, 17, respectively) was identified in 2018, and four QTL (qMo-01, qMo-02, qMo-03, and qMo-04, on Chr 5, 11, 14, and 16, respectively) were identified in 2020. Some of the current QTL had high LOD and significantly contributed to the phenotypic variance for the trait. For example, in 2018, Mo QTL qMo-01 on Chr 1 had LOD of 7.8, explaining a phenotypic variance of 41.17%, and qMo-03 on Chr 17 had LOD of 5.33, with phenotypic variance explained of 41.49%. In addition, one Mo QTL (qMo-03 on Chr 14) had LOD of 9.77, explaining 51.57% of phenotypic variance related to the trait, and another Mo QTL (qMo-04 on Chr 16) had LOD of 7.62 and explained 49.95% of phenotypic variance. None of the QTL identified here were identified twice across locations/years. Based on a search of the available literature and of SoyBase, the four QTL for Ni, identified on Chr 2, 8, 9, and 20, and the five QTL associated with Mo, identified on Chr 1, 17, 11, 14, and 16, are novel and not previously reported. This research contributes new insights into the genetic mapping of Ni and Mo, and provides valuable QTL and molecular markers that can potentially assist in selecting Ni and Mo levels in soybean seeds.

Soybean seed sugars are among the most abundant beneficial compounds for human and animal consumption in soybean seeds. Higher seed sugars such as sucrose are desirable as they contribute to taste and flavor in soy-based food. Therefore, the objectives of this study were to use the ‘Forrest’ by ‘Williams 82’ (F × W82) recombinant inbred line (RIL) soybean population (n = 309) to identify quantitative trait loci (QTLs) and candidate genes that control seed sugar (sucrose, stachyose, and raffinose) contents in two environments (North Carolina and Illinois) over two years (2018 and 2020). A total of 26 QTLs that control seed sugar contents were identified and mapped on 16 soybean chromosomes (chrs.). Interestingly, five QTL regions were identified in both locations, Illinois and North Carolina, in this study on chrs. 2, 5, 13, 17, and 20. Amongst 57 candidate genes identified in this study, 16 were located within 10 Megabase (MB) of the identified QTLs. Amongst them, a cluster of four genes involved in the sugars’ pathway was collocated within 6 MB of two QTLs that were detected in this study on chr. 17. Further functional validation of the identified genes could be beneficial in breeding programs to produce soybean lines with high beneficial sucrose and low raffinose family oligosaccharides.

Abstract Paraquat is used as a harvest‐aid to desiccate green tissues for increasing harvest efficiency and maintaining seed quality. However, its application can cause significant crop damage and yield loss if applied too early. Limited information is available on determining the optimum time for applying paraquat. Therefore, the objectives of this study were to investigate the effects of the timing (critical stages of seed‐fill) of paraquat application on soybean seed yield, seed quality (germination, viability, hard‐seed, and seed damage), and seed composition. Field experiments were conducted in 2019 and 2020 at Stoneville, MS. Paraquat was applied at a rate of 0.56 kg a.i. ha–1 at growth stages R6 (full seed‐fill), R6.5 (pod cavities completely filled with seeds), or R7 (yellow color/beginning maturity). Cultivars P46A57BX and P48A60X were used. The results showed that the application of paraquat at R6 or R6.5 resulted in significant yield loss for both cultivars in both years, whereas application at R7 resulted in significant yield loss for P46A57BX in both years, but in only 1 yr for P48A60X. Seed germination and viability were significantly increased over the control in 2020 for both cultivars at all three application stages, but with mixed effects in 2019. No seed damage that would result in dockage was observed in any treatment, as seed damage for all treatments was below 2%. Application of paraquat at R6 resulted in significantly higher seed protein, oleic acid, raffinose, and stachyose but lower oil and sucrose. This research demonstrated that the harvest‐aid paraquat significantly reduced seed yield, increased seed protein, oleic acid, raffinose, and stachyose when applied before growth stage R7. Therefore, producers should use caution when applying paraquat for harvest efficiency before R7, as they will also likely reduce seed yield the earlier paraquat is applied.

Charcoal rot, caused by Macrophomina phaseolina, is a major soybean disease resulting in significant yield loss and poor seed quality. Currently, no resistant soybean cultivar is available in the market and resistance mechanisms to charcoal rot are unknown, although the disease is believed to infect plants from infected soil through the roots by unknown toxin-mediated mechanisms. The objective of this research was to investigate the association between seed sugars (sucrose, raffinose, stachyose, glucose, and fructose) and their role as biomarkers in the soybean defense mechanism in the moderately resistant (MR) and susceptible (S) genotypes to charcoal rot. Seven MR and six S genotypes were grown under irrigated (IR) and non-irrigated (NIR) conditions. A two-year field experiment was conducted in 2012 and 2013 at Jackson, TN, USA. The main findings in this research were that MR genotypes generally had the ability to maintain higher seed levels of sucrose, glucose, and fructose than did S genotypes. Conversely, susceptible genotypes showed a higher level of stachyose and lower levels of sucrose, glucose, and fructose. This was observed in 6 out of 7 MR genotypes and in 4 out of 6 S genotypes in 2012; and in 5 out of 7 MR genotypes and in 5 out of 6 S genotypes in 2013. The response of S genotypes with higher levels of stachyose and lower sucrose, glucose, and fructose, compared with those of MR genotypes, may indicate the possible role of these sugars in a defense mechanism against charcoal rot. It also indicates that nutrient pathways in MR genotypes allowed for a higher influx of nutritious sugars (sucrose, glucose, and fructose) than did S genotypes, suggesting these sugars as potential biomarkers for selecting MR soybean plants after harvest. This research provides new knowledge on seed sugars and helps in understanding the impact of charcoal rot on seed sugars in moderately resistant and susceptible genotypes.