Search Results (53)

Seed vitality is a key factor for successful germination of seeds and successful root establishment of crops. However, a cold environment can severely hinder the germination of soybean seeds, resulting in a significant decrease in yield. In this study, the cold tolerance of 205 chromosome segment substitution lines (CSSL) during the germination process was evaluated. CSSL_R22 exhibited higher seed vitality under low-temperature conditions. Five quantitative trait loci (QTL) related to cold tolerance during the germination stage were detected. By combining the QTL analysis results with transcriptome data, we determined that GmKAN1 (Glyma.20G108600) is an important regulatory factor for cold tolerance during seed germination. Preliminary studies have shown that GmKAN1, as a transcriptional repressor of GmARF2 and GmARF8, can regulate auxin synthesis to enhance the tolerance of seeds to cold stress. These results provide valuable insights into the regulatory network related to cold tolerance during soybean seed germination. Full article

Soybeans are widely used in agro-industrial sectors, and global demand for this crop continues to rise. After harvest, however, soybean seeds often lack the appropriate moisture content for storage, making drying a common practice under changing climate conditions. Because temperature is a critical factor during drying, this study aimed to evaluate the effect of air-drying temperature on physiological responses and cytogenetic conformation of soybean seeds. The experiment was conducted under a completely randomized design with four replications for each temperature. Seeds with 23 percent moisture content were dried in a convective dryer equipped with airflow and temperature control at 40 °C, 50 °C, 60 °C, and 70 °C until reaching 13 percent. Samples for physiological and cytological analyses were collected before and after drying. The results indicated that drying temperature influenced seed performance and vigor. Moreover, nuclear alterations were identified as an important component of the genotoxicity caused by high drying temperatures. Overall, air temperatures above 50 °C induced physiological and cytogenotoxic effects, underscoring the need for careful monitoring during seed drying. Full article

High-quality soybean seeds possess genetic, physical, and physiological characteristics that directly influence crop yield. The use of hyperspectral sensors combined with machine learning (ML) can streamline and accelerate seed germination testing. Therefore, the objectives of this study were: (i) to evaluate whether leaf and seed reflectance can effectively predict the physiological quality of soybean seeds using ML algorithms, and (ii) to identify which algorithm provides the highest prediction accuracy. Thirty-two soybean genotypes were evaluated in a controlled experiment. Leaves and seeds were analyzed using a hyperspectral sensor capable of measuring reflectance across the 350 to 2500 nm range. The resulting data were subjected to ML analysis with two types of input: spectral variables from leaves and seeds. The output variables predicted included germination test (GERM), electrical conductivity (EC), first germination count (FGC), vigorous tetrazolium test (VIG-TZ), and viable tetrazolium test (VIAB). Predictions were performed using stratified 10-fold cross-validation with ten repetitions (100 runs per model). All model parameters were set to the default configuration in Weka version 3.8.5. The ML models used for prediction included artificial neural networks (ANN), REPTree and M5P decision trees, random forest (RF), support vector machine (SVM), and ZeroR, with the latter serving as a control algorithm. The models showed consistent performance in predicting physiological variations in seeds, with better results when seed reflectance was used as input. For germination (GERM), the M5P, RF, and SVM algorithms obtained the highest correlations (r = 0.565–0.575). In predicting electrical conductivity (EC), M5P showed greater accuracy with leaf data (r = 0.506), while SVM performed best with seed data (r = 0.658). For first germination count (CPG), M5P was the most accurate with leaf data (r = 0.720), while M5P, RF, and SVM showed r between approximately 0.735 and 0.777 with seed data. In tetrazolium vigor (TZVG), RF showed the best performance (MAE 0.25), again highlighting seed reflection, which resulted in the lowest errors and highest correlations. Overall, the M5P, RF, and SVM algorithms achieved the most robust results, especially when used with seed spectral data. The highest germination prediction accuracy was achieved by the M5P, SVM, and RF algorithms for both input types. Seed reflectance yielded the best accuracy and the lowest MAE and RMSE values. Leaf reflectance also enabled accurate predictions, indicating that this input can serve as an early, in-field strategy for predicting soybean seed physiological quality. Full article

Soybean seed production in low-altitude subtropical environments in Paraguay is constrained by the antagonism between achieving high grain yields and high physiological seed quality, a relationship governed by the Genotype x Environment x Management (GxExM) interaction. This study aimed to elucidate this trade-off by evaluating three sowing dates (early, normal, late) across genotypes from three relative maturity groups over four growing seasons. Our results demonstrate that sowing date is the primary factor modulating this antagonism. Early and normal sowings maximized yield (up to 62.8% higher than late sowing) by synchronizing the reproductive period with maximum solar radiation but exposed the maturation phase to severe thermal and water stress. This consistently resulted in a high incidence of green seeds (>95% higher than late sowing) and a drastic reduction in seed vigor, with longevity potential reduced by up to 63.6%. In contrast, late sowing functioned as a stress-escape strategy, shifting maturation to milder autumn conditions and consistently producing seeds of high vigor, viability, and greater longevity. Critically, during a season of extreme drought and heat, the late sowing not only preserved quality but also produced the highest grain yield, highlighting its decisive role in risk mitigation. Thus, sowing date is a key management tool for targeted production in these environments. Full article

Production of a healthy crop of protein- and oil-rich soybean seeds requires a significant amount of nitrogen. Under ideal conditions, most of this nitrogen comes from the root nodules, where a symbiotic relationship with Bradyrhizobium japonicum fixes nitrogen from the atmosphere. Thus, growers generally think of soybeans as not needing nitrogen fertilization. However, a lack of B. japonicum or other unfavorable field conditions can produce inefficient nodulation, which leads to reduced vigor and yield under conditions of low soil nitrogen availability. Thus, additional resources for identifying nitrogen deficiency in soybean and strategies for the rescue application of nitrogen are needed. To generate a gradient of nitrogen deficiency, we applied different amounts of nitrogen (in the form of urea) to nodulation-deficient soybeans grown in sandy fields in South Carolina. Comparison of the ground truth data and aerial imagery suggest that leaf nitrogen deficiency can be effectively identified in the field based on plant height and color. Side dressing nitrogen fertilizer in the form of urea to nitrogen-deficient plots at the R1 stage was shown to rescue plant growth and increase crop yield. We conclude that identification and fertilization of patches of soybeans with low nitrogen content is a feasible strategy to increase soybean productivity. Although additional studies are needed to expand these results to other soil conditions, we recommend that nitrogen-deficient soybeans be treated with 40–50 pounds per acre (45–56 kg per hectare) of nitrogen at or before flowering to restore yield potential. Full article

The seed lots were evaluated based on their viability and vigor, which vary according to their origin and the locations where the seeds were produced. However, differences in vigor can be observed within a single seed lot, resulting from the deposition of photoassimilates. In this context, the hypothesis of this study is that distinct locations on the plant may produce seeds with different physiological quality. Therefore, the objective of this work was to evaluate how pod position influences the vigor of seeds from different soybean genotypes. Field experiments were conducted during the 2021/22 and 2022/23 crop seasons in Brazil. The experimental design was a randomized complete block with four replications and 32 soybean populations from the UFMS/CPCS Breeding Program. During the R4, R5, R6, and R7 reproductive stages of soybean, at the time of pod formation, the plants in each block were tagged with string to delimit the uppermost point at which pods had formed. Tagging was carried out as each stage change was verified, at approximately eight-day intervals. When analyzing how the pod position of the plant influences seed physiological variables, we found that position P1 was responsible for the best results for the variables evaluated, with the exception of genotypes G18 and G28. This result indicates that pods from the first position produce seeds with greater germination capacity and a higher ability to generate normal seedlings. However, the genotypes are still under development and, therefore, do not yet exhibit stability. Nevertheless, the results obtained highlight the relationship between the pod position of the plant and seed physiological variables. The position of the pods on the soybean plant influences the physiological quality of the seeds. In general, the P1 position, when the plants are in the R4 reproductive stage, with fully developed pods measuring 2 cm on one of the four upper nodes of the stem, is responsible for the best results in seed physiological quality tests for most of the soybean genotypes evaluated. These results indicate that pod position should be considered in breeding and seed production programs, since genotypes with greater physiological stability in the upper positions may be preferential in selection strategies. In the future, studies in different environments and evaluation of biochemical traits may confirm these patterns and contribute to the development of cultivars with higher seed quality and physiological uniformity. Full article

Cobalt, molybdenum, and nickel are elements directly involved in biological nitrogen fixation in legume plants. However, there is a lack of information about the effects of the interaction among these elements on seed vigor and plant development. This study aimed to evaluate the effects of different doses of these elements on soybean seeds with higher and lower vigor, focusing on nitrogen metabolism and plant development under controlled conditions. The two lots of soybean seeds (higher and lower vigor) were treated with doses of 0, 2, 4, 6, and 8 mL kg⁻¹ of seeds of a liquid commercial product composed of cobalt, molybdenum, and nickel. At the full flowering stage, urease and nitrogenase activities, dry biomass of shoots, roots, and nodules, nitrogen concentration in shoots, plant height, number of nodules, and the efficiency of biological nitrogen fixation (measured by nitrogen-15 isotopic ratio) were assessed. Urease activity increased by 191% in high-vigor seed plants and 65% in low-vigor seed plants. Nitrogenase activity was higher in higher-vigor plants. Nodule dry biomass increased by 42% in lower-vigor plants compared to the control treatment, while in higher-vigor plants, it decreased with increasing doses. Shoot biomass was 30% higher than the control at the 2 mL kg⁻¹ dose. In general, the best responses to the application of the elements in the evaluated variables were observed with the doses of 2 and 4 mL kg⁻¹. It is concluded that the appropriate application of cobalt, molybdenum, and nickel on seeds enhances growth and symbiotic efficiency. However, excessive doses may cause phytotoxic effects. Full article

Biostimulants based on Bradyrhizobium japonicum are commonly used in soybean production. However, the effect of nitrogen-fixing bacteria in consortia with other plant growth-promoting rhizobacteria (PGPR) and their integration with mineral nutrients on soybean seed quality has not been explored. The study aimed to examine the effects of five treatments on seed germination and initial seedling growth of two soybean cultivars (‘NS Apolo’, ‘NS Rubin’): control (untreated seeds); Br. japonicum (BJ), BJ and nutrient complex (NC), BJ, Azotobacter chroococcum (AC), Bacillus subtilis (BS), and NC; BJ, AC, Bacillus megaterium (BM), and NC. Seed treatments significantly enhanced germination energy, seedling vigor index, root length, fresh shoot weight, fresh root weight, dry shoot weight, and dry root weight of both cultivars, as well as final germination, shoot length, and shoot elongation rate of ‘NS Rubin’, as compared to the control. The highest effect on the investigated parameters was achieved by integrated use of PGPR and nutrients (BJ + BM + AC + NC), indicating that integration of PGPR with a targeted NC represents an innovative approach with practical implications for improving early soybean establishment and field performance. Full article

Precision agriculture facilitates improved management by studying the spatial and temporal variability of soil attributes. Soybean (Glycine max (L.) Merrill) seeds may exhibit distinct quality when produced in different management zones. This study aimed to validate management zones during seed production and identify the variability and spatial distribution of soybean seed physiological quality using geostatistical tools. Management zones were defined based on interpolated maps of soil and vegetation attributes using the Smart Map Plugin (SMP) within the QGIS environment. Post-harvest, the variability of physiological seed quality across different management zones was assessed. Germination, accelerated aging, dry weight, emergence, electrical conductivity, and tetrazolium tests were conducted in a completely randomized design. Soil attributes, initial plant stand, and soybean seed productivity validated the management zones. Physiological seed quality varies across the production field, particularly in terms of vigor, thereby enhancing diagnostics through map interpolation. Geostatistics enable determination of the spatial distribution of soybean seed physiological quality in seed production areas, facilitating decision-making regarding harvest zones. Full article

Soybean is one of the main agricultural commodities, and its productivity is limited by several diseases, such as anthracnose, which is caused by a complex of fungal species, with Colletotrichum truncatum being the most prevalent. Management is mainly carried out through chemical seed treatment. However, a reduction in the sensitivity of C. truncatum to fungicides was observed. Therefore, it is extremely important to search for products that are effective in controlling the disease. The objectives of this study were to evaluate the efficacy of commercial formulations of copper, potassium, manganese, and zinc phosphites in the treatment of soybean seeds infected by C. truncatum, as well as their direct fungitoxicity and ability to induce soybean defense mechanisms. For this purpose, seeds inoculated with C. truncatum were subjected to phosphites and a fungicide (carbendazim + thiram). The seeds were exposed to germination, health, and vigor tests. Fungal toxicity and the ability of phosphites to induce defense through the activities of catalase, peroxidase, and superoxide dismutase enzymes, as well as the levels of lignin and total soluble phenols, were also evaluated. Mn and Zn phosphites showed direct toxicity to C. truncatum and were as effective as the fungicide (carbendazim + thiram) in treating soybean seeds infected by the fungus. Mn phosphite induced the production of catalase (CAT), peroxidase (POX) and lignin, while Zn phosphite increased the production of CAT and POX. These results demonstrate the efficacy of Mn and Zn phosphites in controlling C. truncatum in infected soybean seeds, their direct toxic action, and their ability to induce resistance. Full article

Salt stress impedes normal development, compromises plant quality, and reduces crop yield. The germination phase in soybean marks the initial stage of its growth cycle. Characterizing salt tolerance during this period can help stimulate soybean growth in natural environments and aid the rapid screening of salt-tolerant soybean varieties. Our study characterized the salt tolerance of 36 soybean germplasms in culture dishes during the germination period. Soybeans were subjected to varying concentrations (0, 60, 120, and 180 mmol/L) of NaCl solution to simulate diverse levels of salt stress, and parameters such as germination energy, germination rate, and root length were measured. Statistical techniques such as analysis of variance, membership function, cluster analysis, and quadratic regression equations were used, and the salt tolerance of these 36 soybean germplasms was determined. The critical indicators and the most effective screening concentration for assessing the germination salt tolerance of soybean were identified. Soybeans tolerated low salt concentrations; however, salt concentrations greater than 120 mmol/L significantly inhibited germination indicators. The germination rate, germination vigor, vitality index, seed germination index, total fresh weight, and total dry weight could be used to identify salt tolerance. The semi-lethal concentration of soybean was 155.4 mmol/L, and the coefficient of variation was 20.00%, indicating that it could be used as a screening concentration for evaluating salt tolerance during soybean germination. A total of 36 soybean varieties were classified into four salt tolerance levels through cluster analysis. QN-27, QN-35, and QN-36 were highly salt-resistant materials, and QN-2, QN-17, and QN-19 were salt-sensitive materials. Characterizing salt tolerance during soybean germination can facilitate the selection and breeding of salt-tolerant soybean varieties. Future research utilizing this approach can aid in the selection of soybean varieties with salinity tolerance. Full article

Soybean seeds with similar germination rates may exhibit subtle differences in physiological quality, influencing field performance and storage longevity. This study used a shotgun proteomics approach to characterize the proteomic profile of two commercial soybean seed lots (higher- and lower-quality) during germination, aiming to identify biomarkers associated with vigor and deterioration. Proteins were analyzed across three germination phases: imbibition (Phase I, 0.5 h), metabolic activation (Phase II, 20 h), and radicle protrusion (Phase III, 51 h). A total of 777 proteins were identified, and of these differentially abundant proteins (DAPs), the following totals were detected: 12 in Phase I, 17 in Phase II, and 28 in Phase III. In Phase I, ribosomal proteins were more abundant in high-quality seeds, indicating efficient translation and preparation for germination. Conversely, in Phase III, low-quality seeds showed increased levels of storage proteins and stress-response proteins, including alcohol dehydrogenase (ADH), heat shock proteins, and annexins, reflecting delayed germination and more deterioration. These findings highlight the dynamic nature of protein expression during germination and demonstrate the potential of proteomics to detect subtle differences in physiological quality. The identified biomarkers provide insights for seed quality assessment and offer practical applications for improving classification and management of commercial soybean seed lots. Full article

Understanding the ability of hybrids of genetically modified (GM) soybean and wild soybean to survive and reproduce under unfavorable conditions is critical for answering questions regarding risk assessment and the existence of transgenes in the environment. To investigate the effects of high-temperature stress on soybean growth and competitive ability, the GM soybean DBN8002, which expresses the VIP3Aa and PAT proteins, and F₂ generations derived from a cross between GM soybean and NJW (wild soybean) were placed in a greenhouse with an elevated temperature (38/32 °C) for 14 days, and the plant agronomic performance and foreign protein levels of hybrid soybean were evaluated to observe their responses to high temperature. The results revealed that the VIP3Aa and PAT protein levels in F₂ and GM were not influenced by high-temperature stress. In contrast, the pollen germination, pod number, hundred-seed weight, and seed vigor of the F₂ hybrid and parent soybean plants decreased after high-temperature stress. However, except for the number of fully filled seeds per plant, the above parameters of the F₂ hybrid were similar to or slightly lower than those of wild soybean, and no significant difference in fitness was observed between the F₂ hybrid and wild soybean, indicating that the growth and competitive ability of the hybrid were similar to those of its female parent under heat stress conditions, resulting in the transgenes persisting and spreading within agricultural ecosystems. Our results enhance the understanding of the GM soybean plant’s response to heat stress, lay the foundation for breeding heat-resistant soybean varieties, and provide new insights and advanced information on the ecological risks arising from the escape of transgenes. Full article

The use of summarized spectral data in bands obtained by hyperspectral sensors can make it possible to obtain biochemical information about seeds and, thus, relate the results to seed viability and vigor. Thus, the hypothesis of this work is based on the possibility of obtaining information about the physiological quality of seeds through hyperspectral bands and distinguishing seed lots regarding their quality through wavelengths. The objective was then to evaluate the possibility of differentiating soybean genotypes regarding the physiological quality of seeds using spectral data. The experiment was conducted during the 2021/2022 harvest at the Federal University of Mato Grosso do Sul in a randomized block design with four replicates and 10 F3 soybean populations (G1, G8, G12, G15, G19, G21, G24, G27, G31, and G36). After the maturation of each genotype, seeds were harvested from the central rows of each plot, which consisted of five one-meter rows. Seed samples from each experimental unit were placed in a Petri dish to collect spectral data. Readings were performed in the laboratory at a temperature of 26 °C and using two 60 W halogen lamps as the light source, positioned 15 cm between the sensor and the sample. The sensor used was the Ocean Optics (Florida, USA) model STS-VIS-L-50-400-SMA, which captured the reflectance of the seed sample at wavelengths between 450 and 824 nm. After readings from the hyperspectral sensor, the seeds were subjected to tests for water content, germination, first germination count, electrical conductivity, and tetrazolium. The data obtained were subjected to an analysis of variance and the means were compared by the Scott–Knott test at 5% probability, analyzed using R software version 4.2.3 (Auckland, New Zealand). The data on the physiological quality of the seeds of the soybean genotypes were subjected to principal component analysis (PCA) and associated with the K-means algorithm to form groups according to the similarity and distinction between the genetic materials. After the formation of these groups, spectral curve graphs were constructed for each soybean genotype and for the groups that were formed. The physiological quality of the soybean genotypes can be differentiated using hyperspectral bands. The spectral bands, therefore, provide important information about the physiological quality of soybean seeds. Through the use of hyperspectral sensors and the observation of specific bands, it is possible to differentiate genotypes in terms of seed quality, complementing and/or replacing traditional tests in a fast, accurate, and non-destructive way, reducing the time and investment spent on obtaining information on seed viability and vigor. The results found in this study are promising, and further research is needed in future studies with other species and genotypes. The interval between 450 and 649 nm was the main spectrum band that contributed to the differentiation between soybean genotypes of superior and inferior physiological quality. Full article

Soybean (Glycine max (L.) Merr.) is an important crop for both food and feed, playing a significant role in agricultural production and the human diet. During long-term storage, soybean seeds often exhibit reduced quality, decreased germination, and lower seedling vigor, ultimately leading to significant yield reductions in soybean crops. Seed storage tolerance is a complex quantitative trait controlled by multiple genes and is also influenced by environmental factors during seed formation, harvest, and storage. This study aimed to evaluate soybean germplasms for their storage tolerance, identify quantitative trait nucleotides (QTNs) associated with seed storage tolerance traits, and screen for candidate genes. The storage tolerance of 168 soybean germplasms was evaluated, and 23,156 high-quality single nucleotide polymorphism (SNP) markers were screened and analyzed through a genome-wide association study (GWAS). Ultimately, 14 QTNs were identified as being associated with seed storage tolerance and were distributed across the eight chromosomes of soybean, with five QTNs (rs25887810, rs27941858, rs33981296, rs44713950, and rs18610980) being newly reported loci in this study. In the linkage disequilibrium regions of these SNPs, 256 genes were identified. By combining GWAS and weighted gene co-expression network analysis (WGCNA), eight hub genes (Glyma.03G058300, Glyma.04G1921100, Glyma.04G192600, Glyma.04G192900, Glyma.07G002000, Glyma.08G329400, Glyma.16G074600, Glyma.16G091400) were jointly identified. Through the analysis of expression patterns, two candidate genes (Glyma.03G058300, Glyma.16G074600) potentially involved in seed storage tolerance were ultimately identified. Additionally, haplotype analysis revealed that natural variations in Glyma.03G058300 could affect seed storage tolerance. The findings of this research provide a theoretical foundation for understanding the regulatory mechanism underlying soybean storage. Full article