Search Results (180)

Floral ontogeny in soybean (Glycine max) is governed by multilayered regulatory hierarchies that integrate phytohormonal cues with precisely choreographed gene-expression programs. Yet, the transcriptomic architecture underpinning this continuum remains only partially resolved. Here, we generated a strand-specific, high-depth temporal transcriptome atlas of soybean inflorescences spanning four morphologically defined stadiums (Stadium 0–Stadium 3). We detected transcriptional activity for 60,889 loci; pairwise stadium contrasts revealed 4000–7000 differentially expressed genes, with the most extensive reprogramming coinciding with the onset of anthesis (Stadium 2). Unsupervised clustering delineated ~600 genes peaking at the pre-anthesis phase (Stadium 1), a cohort enriched for transcriptional regulators and floral organ-identity determinants. Stadium-resolved gene-set enrichment and KEGG mapping uncovered dynamic modulation of canonical hormone-signaling pathways—including auxin, cytokinin, gibberellin, abscisic acid, ethylene, jasmonate, and salicylate circuits—reflecting shifting developmental priorities. Forty-five MADS-box transcription factor genes were expressed; notably, JOINTLESS was strongly induced at anthesis, while the root-predominant factor GmNMH7 exhibited unexpected floral expression, implicating a hitherto unappreciated role in reproductive development. Quantitative RT-PCR of representative loci corroborated RNA-seq measurements. This high-resolution atlas refines our understanding of the hormonal and genetic circuitry of soybean floral morphogenesis, furnishing molecular targets for engineering flowering time and inflorescence architecture under fluctuating environmental conditions. Full article

The Fabaceae family, the third-largest among flowering plants, is nutritionally vital, providing rich sources of protein, dietary fiber, vitamins, and minerals. Leguminous plants, such as soybeans, peas, and chickpeas, typically contain two to three times more protein than cereals like wheat and rice, with low fat content (primarily unsaturated fats) and no cholesterol, making them essential for cardiovascular health and blood sugar management. Since the release of the soybean genome in 2010, genomic research in Fabaceae has advanced dramatically. High-quality reference genomes have been assembled for key species, including soybeans (Glycine max), common beans (Phaseolus vulgaris), chickpeas (Cicer arietinum), and model legumes like Medicago truncatula and Lotus japonicus, leveraging long-read sequencing, single-cell technologies, and improved assembly algorithms. These advancements have enabled telomere-to-telomere (T2T) assemblies, pan-genome constructions, and the identification of structural variants (SVs) and presence/absence variations (PAVs), enriching our understanding of genetic diversity and domestication history. Functional genomic tools, such as CRISPR-Cas9 gene editing, mutagenesis, and high-throughput omics (transcriptomics, metabolomics), have elucidated regulatory networks controlling critical traits like photoperiod sensitivity (e.g., E1 and Tof16 genes in soybeans), seed development (GmSWEET39 for oil/protein transport), nitrogen fixation efficiency, and stress resilience (e.g., Rpp3 for rust resistance). Genome-wide association studies (GWAS) and comparative genomics have further linked genetic variants to agronomic traits, such as pod size in peanuts (PSW1) and flowering time in common beans (COL2). This review synthesizes recent breakthroughs in legume genomics, highlighting the integration of multi-omic approaches to accelerate gene cloning and functional confirmation of the genes cloned. Full article

Soybean [Glycine max (L.) Merr.] is a globally significant crop that provides essential meal protein and vegetable oil for human consumption. The protein content in soybean seeds is a critical factor that affects nutrition regarding human dietary needs as well as livestock feed. Therefore, identifying the key genes that affect the soybean seed protein content is one of the major goals in soybean research. To identify candidate genes and related pathways involved in soybean seed storage protein during seed development, an RNA-seq analysis was conducted in two soybean varieties that differ in protein content. A series of pathways related to seed protein metabolism, including “Photosynthesis”, “TCA cycle”, and “Starch and sucrose metabolism” pathways, were identified through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Seven candidate genes exhibiting two different gene regulation patterns were identified, six of which are directly related to the seed storage protein pathway, and one of which is related to the carbon binding pathway. An integrated analysis of transcriptomic and candidate gene expression trend suggested that 40 days after flowering (DAF) might be a crucial period for seed protein accumulation in soybean. Through a Weighted Gene Co-expression Network Analysis (WGCNA), two modules and two novel hub genes were found, which may be highly correlated with seed protein development. These findings might be valuable for a complete understanding of the genetic basis of seed protein content and lay a theoretical foundation for future gene functional identification and breeding efforts in soybean. Full article

Thrips flavus (Thysanoptera: Thripidae) is a Eurasian pest that primarily attacks a variety of cash crops such as soybean. Currently, there is insufficient knowledge of thrips-resistance mechanisms in soybeans and a lack of effective thrips-resistant soybean varieties. The objective of this study was to identify the correlation between the pest thrips, T. flavus, resistance levels and morphological structures of soybean varieties. A total of 41 spring soybean varieties were planted in a field in Northeast China. Observations were made regarding the infestation intensity of T. flavus, the morphological structures (compound leaf shape, leaf length, leaf width, leaf surface humidity, trichome density, length, and color), leaf SPAD value, leaf nitrogen content, etc. Specifically, leaf trichome density (regardless of whether it was on the upper or lower surfaces of the upper, middle, or lower leaves), trichome color, and compound leaf shape all showed significant positive correlations with the amount of T. flavus. Additionally, principal component analysis (PCA) indicated that, during the peak flowering stage, leaf width, trichome length, trichome density, SPAD value, and nitrogen content were key factors for evaluating resistance; meanwhile, during the podding stage, leaf length, SPAD value, nitrogen content, and leaf surface humidity made the most significant contributions. Field resistance screening using the number of T. flavus per meter of double rows, the average number of T. flavus per plant, and hierarchical cluster analysis yielded consistent results. The soybean variety “podless-trichome” is a thrips-resistant variety (high resistance), and “Jinong 29” is a thrips-sensitive variety (high sensitivity). This study provides valuable insights into the occurrence of insect resistance to thrips in soybean varieties. Full article

Polyamine oxidase (PAO) is an important enzyme that functions in the catabolism of polyamines. While plant PAOs have been studied in several species, there is a lack of research on this gene family in soybean (Glycine max L.), one of the major food crops worldwide. Here, a genome-wide analysis identified 16 GmPAOs from the soybean genome, which were unevenly distributed in nine soybean chromosomes and were then phylogenetically classified into three groups. Collinearity analysis identified 17 duplicated gene pairs from the GmPAO family, and their Ka/Ks values were all less than one, indicating that the GmPAO family has undergone purifying selection during evolution. Analyses of the conserved motif and gene structure revealed the sequence differences among the GmPAOs of the three groups, suggestive of their functional differentiation. Additionally, the prediction of the secondary and tertiary structure of the GmPAOs provided a further basis for revealing their biological functions. A number of cis-acting elements relevant to development, phytohormone, and stress response were discovered in the promoter regions of the GmPAOs, which might be responsible for their functional diversities. Expression pattern analysis indicated that more than half of the GmPAOs showed preference in flower, two showed specificity in stem and shoot apical meristem, whereas four were barely expressed in all samples. Expression profiling of the GmPAOs also revealed that they were involved in the response to abiotic stresses, including cold, drought, and especially submergence stress. All these results lay an important foundation for further characterizing the functional roles of GmPAOs in soybean development and response to abiotic stresses. Full article

Sowing date significantly affects plant growth, development, and yield, holding a crucial role in soybean cultivation. This study was conducted in the southern coastal region of Korea under recent climate change conditions to investigate the effects of five different sowing dates on climatic characteristics, growth, and yield. Compared to historical data, the southern coastal region has experienced a consistent increase in average temperature during the soybean cultivation period, along with frequent abnormal summer climate events such as concentrated heavy rainfall and monsoons. These climate changes prolonged the vegetative growth period in earlier sowings, leading to an increased risk of lodging at maturity due to vigorous vegetative growth. Furthermore, earlier sowing delayed flowering and exposed plants to longer post-flowering photoperiods, consequently reducing the number of pods. Therefore, in the southern coastal region of Korea, it is crucial to re-evaluate conventional sowing practices and establish region-specific optimal dates, with careful consideration given to postponing the soybean sowing date to late June in order to enhance yield stability and improve the feasibility of double-cropping systems by shortening the growing period. Full article

In order to analyze the relationship between hyperspectral image and soybean canopy nitrogen content in the field, and to establish a prediction model for soybean canopy nitrogen content with few parameters and a simple structure, hyperspectral image data and corresponding nitrogen content data of soybean canopy at different growth periods under different fertilization treatments were acquired. Three spectral characteristic variables selection methods, including correlation coefficient analysis, stepwise regression, and spectral index analysis, were used to determine the spectral characteristic variables that are closely related to the soybean canopy nitrogen content. The predictive models for soybean canopy nitrogen content based on spectral characteristic variables were established using a multiple linear regression algorithm. On this basis, the established prediction models for soybean canopy nitrogen content were compared and analyzed, and the optimal prediction model for soybean canopy nitrogen content was determined. To verify the applicability of prediction models for soybean canopy nitrogen content, a spatial distribution map of soybean canopy nitrogen content at the regional scale was drawn based on unmanned aerial vehicle (UAV) hyperspectral imaging data at the flowering and seed filling stages of soybean in the experimental area, and the spatial distribution of soybean nitrogen content was statistically analyzed. The results show the following: (1) Soybean canopy spectral reflectance was highly significantly negatively correlated with soybean canopy nitrogen content in the range of 450–729 nm, and highly significantly positively correlated in the range of 756–774 nm, with the largest positive correlation coefficient of 0.2296 at 765 nm and the largest absolute value of negative correlation coefficient of −0.8908 at 630 nm. (2) The predictive model for soybean canopy nitrogen content based on three optimal spectral indices, NDSI(R₅₅₂,R₅₅₅), RSI(R₅₃₇,R₅₇₃), and DSI(R₅₄₀,R₅₅₅), was optimal, with R² of 0.9063 and 0.91566 and RMSE of 3.3229 and 3.2219 for the calibration and prediction set, respectively. (3) Based on the established optimal prediction model for soybean canopy nitrogen content combined with the UAV hyperspectral image data, spatial distribution maps of soybean nitrogen content at the flowering and seed filling stages were generated, and the R² between soybean nitrogen content in the spatial distribution map and the ground measured value was 0.93906, the RMSE was 3.6476, and the average relative error was 9.5676%, which indicates that the model had higher prediction accuracy and applicability. (4) The overall results show that the optimal prediction model for soybean canopy nitrogen content established based on hyperspectral imaging data has the characteristics of few parameters, a simple structure, and strong applicability, which provides a new method for realizing rapid, dynamic, and non-destructive monitoring of soybean nutritional status on the regional scale and provides a decision-making basis for precision fertilization management during soybean growth. Full article

Soil erosion has caused the loss of black soil and exposed the soil parent material in the cultivated layer of sloping farmland in Northeast China. Straw return (STR) and manure fertilization (MF) are critical measures to improve soil quality and crop yield. However, the effect of STR and MF on the soil properties of the parent material remains unclear. We conducted a 1-year pot experiment in the field using the soil parent material of degraded black soil to evaluate the effects of STR and MF on soil nutrients, microbial community, and soybean yield. We analyzed these effects using two treatments (STR and MF) in three soybean growth stages (seedling, flowering, and maturity) and a control group (CK). The MF treatment had higher α and β diversity of soil microbial than the CK during all soybean growth stages. Similarly, STR had higher soil microbial α diversity at the maturity stage and lower diversity at the seedling stage. Co-occurrence network analysis suggested that STR and MF increased the proportion of positively correlated edges in soil bacterial and fungal networks compared to the CK. Notably, the treatments enriched beneficial taxa, such as Schizothecium (fungi) and Massilia (bacteria), which are associated with organic matter decomposition and nitrogen cycling. STR and MF significantly improved soil organic matter, total nitrogen, and carbon-nitrogen ratio (p < 0.05). Structural equation modeling (SEM) revealed that STR and MF directly increased soybean yield. This effect was primarily mediated by the significantly higher soil organic matter, total carbon, total nitrogen, and carbon-to-nitrogen ratio in the treatments than in the CK (p < 0.05). In summary, STR and MF improved soil fertility and soil microbial community diversity of degraded black soil. This study provides scientific methods to improve the fertility of degraded black soil and increase soybean production in the short term. Full article

Many of today’s innovative materials used to carry trace elements (TEs) are derived from chelates. Most of the materials used for this purpose have been produced on the basis of EDTA, which is not considered to be environmentally friendly due to its high persistence. Research is therefore being carried out to produce materials that do not pose an environmental risk. Therefore, a study was carried out to determine the effects of newly developed innovative materials with embedded biodegradable and environmentally safe chelates (IDHA—iminodisuccinic acid—and N-butyl-D-gluconamide ligands) containing copper, molybdenum and iron on the yield, biometric characteristics and chemical composition of soybean and selected soil properties. It is difficult to find publications on their effects in soybean cultivation. The greatest increase in soybean leaf greenness index (SPAD) was found after the addition of pure Salmag^® (Sal.^®). The effect of the chelates on the SPAD index was lower, with Sal.^® + Fe chelate having the greatest effect during the vegetative development stage and Cu chelate having the greatest effect during the flowering stage. Sal.^® + Cu, especially with Fe, accelerated pod and seed ripening in the last vegetative stage of soybean. Sal.^® + Cu had the most favourable impact on plant height, pure Sal.^® on the pod number per plant, Sal.^® + Fe on the seed number per pod, Sal.^® with Mo and Fe chelates on soybean seed yield, and pure Sal.^® on fresh weight remaining above-ground part yield, while pure Sal.^® and Sal.^® + Fe had the most favourable impact on dry weight aerial yield. The fertiliser materials (especially Sal.^® + Cu) generally increased the N content of the tested soybean organs and the Cu content of the other above-ground soybean parts (especially those containing chelates) and had an antagonistic effect on the Mg content of the soybean above-ground parts. Sal.^® + Cu also had a negative effect on the Fe content of other above-ground soybean parts. Sal.^® + Fe had a positive impact on the iron content, and Sal.^® + Mo had a positive impact on the molybdenum content of soybean. The applied fertilisers had little effect on the contents of Cu, Mo and Fe in the soil. There was only a significant increase in the Cu content of the soil after the addition of Sal.^® + Cu and a significantly smaller increase under the influence of Sal.^® without chelates, as well as an increase in the Mo content of the soil with Sal.^®. The present study confirms the beneficial impact of the novel materials with chelates. It has been demonstrated that the presence of materials containing Mo and, in particular, Cu has a considerable effect on the yield and quality characteristics of soybeans. Full article

The interest in traditional meat being replaced by plant-based food has increased throughout the years. Some agricultural products, such as root crops, could be incorporated into alternative meat products due to the health benefits. However, relevant studies have discovered that some roots are considered allergen materials, necessitating further identification to maintain consumer safety. Aside from high accuracy, the limitations offered by traditional identification methods are a reason to employ nondestructive methods. This study aimed to develop a hyperspectral imaging system measuring the 400 nm to 1000 nm spectral range for the nondestructive identification of roots in soybean-based patty. Four thin-sliced traditional medicinal roots (tianma (Gastrodia elata), balloon flower root (Platycodon grandiflorum), deodeok (Codonopsis lanceolata), and ginseng (Panax ginseng)) were incorporated in a soybean-based patty with a concentration of 5% w/w. Moreover, support vector machine (SVM) learning and one-dimensional convolutional neural networks (1D-CNN) were realized for the discrimination model in tandem with spectral data extracted from the hyperspectral image. Our study demonstrated that SVM learning effectively discriminates between original patty and patty with root addition, with an F1-score, precision, and recall beyond 96.77%. This optimum model was achieved by using the standard normal variate (SNV) spectra. Full article

Frankliniella intonsa (Thysanoptera: Thripidae) is a polyphagous pest that causes significant economic agricultural losses by damaging flowers, vegetables, and fruit trees. We performed an age-stage two-sex life table analysis to evaluate the performance and adaptability of F. intonsa against nine common vegetable crops cultivated in Guangxi: cowpea (Vigna unguiculata) (Fabales: Leguminosae), green beans (Phaseolus vulgaris) (Fabales: Leguminosae), soybean (Glycine max) (Fabales: Leguminosae), catjang cowpea (Vigna cylindrica) (Fabales: Leguminosae), courgette (Cucurbita pepo) (Cucurbitales: Cucurbitaceae), wax gourd (Benincasa hispida) (Cucurbitales: Cucurbitaceae), bitter gourd (Momordica charantia) (Cucurbitales: Cucurbitaceae), cucumber (Cucumis sativus) (Cucurbitales: Cucurbitaceae), and chieh-qua (Benincasa hispida) (Cucurbitales: Cucurbitaceae). Among the tested host crops, green beans, cowpea, and courgette significantly accelerated the growth rate and favored the reproductive success of F. intonsa. Green beans, cowpea, and courgette facilitated rapid growth and reproductive success. The mean generation times (T) and net reproductive rates (R₀) were as follows: 14.90 d, 17.09 d, 21.03 d, and 104.04, 45.51, 32.61. Bitter gourd and chieh-qua significantly suppressed population growth (T: 49.49 d, 0 d; R₀: 0.73, 0). Wax gourd, catjang cowpea, cucumber, and soybean exhibited moderate effects characterized by delayed development and lower reproductive output (T: 22.30 d, 20.30 d, 19.51 d, 32.73 d; R₀: 7.17, 25.22, 13.74, and 12.54). These findings highlight the critical role of crop type in F. intonsa population dynamics. Therefore, the agricultural production of green beans, cowpea, and courgette crops necessitates improved control measures and monitoring. Similar measures are needed for cucumber, catjang cowpea, soybeans, and wax gourds because they pose risks as potential hosts. Full article

The soybean yield per unit area in Xinjiang has reached a high level, with the crop maturing quickly because of the higher temperatures and levels of mechanization. However, environmental factors cause flowers and pods to shed easily, limiting yield potential. Efficient plant growth regulators (PGRs) used to increase crop yields have gained popularity, but their effectiveness in reducing flower and pod shedding, considering factors such as environment, crop variety, and time of spraying, remains unclear. This study investigated whether spraying several PGRs could reduce soybean flower and pod shedding. Field experiments were conducted from 2022 to 2024 in Ili, Xinjiang, China, using α-naphthaleneacetic acid (NAA), prohexadione-calcium (Pro-Ca), and iron chlorine e6 (ICE6) with foliar applications of 300, 450, and 45 g ha⁻¹ at the four-node stage (V4) and full pod stage (R4). All PGR treatments reduced flower and pod shedding over the years and resulted in an increase in the average flower and pod numbers compared to normal-growth-treated (CK) soybeans. The effective slowing of flower and pod shedding during the critical pod formation stage (R4) ensured a stable yield potential. The flower-to-pod conversion rate was higher after spraying plants with PGRs than for the CK group, and pod retention was higher at the beginning of maturity (R7). Our results demonstrated that spraying PGRs (NAA, Pro-Ca, and ICE6) effectively reduced soybean flower and pod shedding, optimized pod distribution, and increased soybean yield potential. The study findings provide a useful reference for global soybean growers to optimize planting methods. Full article

Expanding soybean planting is vital for food security both in China and globally. The 50° N latitude serves as the northern boundary of major soybean regions. However, enhancing the adaptability of soybean to photothermal conditions enables the potential to extend cultivation to higher latitudes and altitudes. Understanding the genetic basis of super-early maturity of soybean is crucial to achieving this goal. In this study, 438 soybean germplasms collected from high-latitude regions were evaluated in Heihe (HH) (50°15′ N, 127°28′ E, 154 m), Beijicun (BJC) (53°28′ N, 122°21′ E, 295 m) and Labudalin (LBDL) (50°15′ N, 120°19′ E, 577 m). Using resequencing data, we analyzed natural variation and haplotypes in 35 key genes associated with flowering time and maturity. The results showed that the relative maturity groups (RMGs) for BJC, HH, and LBDL were −1.0, 0.0, and −1.2, respectively. Among the 35 genes analyzed, 23 had identical allelic variations, while 12 genes exhibited 19 SNPs and four InDels. Functional mutations were identified in E1, E2, E3, and E4. Notably, all cultivars carried the e1-as allele of E1, which is likely critical for high-latitude adaptation. Additional mutations included a single-base substitution in E2 (16142 A > T) and E3 (5203 C > T), causing premature codon termination, along with frameshift mutations in E4 (3726 and 4099) and E3 (2649). Haplotype analysis revealed significant differences in growth stages among nine gene haplotypes. The higher frequency of early-maturing haplotypes in BJC and LBDL highlights the role of gene accumulation in soybean adaptation. These findings offer valuable insights for improving soybean maturity and expanding its cultivation in high-latitude regions of China. Full article

The pseudo response regulator (PRR) gene is an important component of the core oscillator involved in plant circadian rhythms and plays an important role in regulating plant growth and development and stress responses. In this study, we investigated the function of GmPRR7b by overexpression and gene editing approaches. It was found that GmPRR7b plays a role in delaying flowering. While GmPRR7b overexpressing plants showed significantly delayed flowering compared to untransformed WT, GmPRR7b edited plants flowered earlier than the control WT. On the basis of previous research results and bioinformatics analysis, we re-identified 14 soybean PRR genes and analysed their rhythmic expression. Based on the rhythmic expression pattern, we found that GmPRR5/9a and GmPRR5/9b interacted with GmPRR7b by yeast two-hybrid and bimolecular fluorescence complementation (BiFC) experiments. Combined with the expression regulatory networks of the GmPRR7b, we inferred a possible regulatory mechanism by which GmPRR7b affects flowering through quit rhythm expression. These research elements provide valuable references for understanding growth, development, and circadian regulation in soybean. Full article

A phenotype survey on soybean flower and pod drop conducted by agricultural experts revealed issues such as poor real-time performance and strong subjectivity. Based on the YOLOv5 detection model, a microscale detection layer is added and the size of the initial anchor box is improved to enhance feature expression ability. The CBAM attention mechanism is introduced in the backbone network to capture the information of direction and position, which helps the model to locate and recognize more accurately. The test results show that the accuracy rate of the soybean flower and pod recognition model reaches 98.4%, and the recall rate reaches 97.4%. Compared with the original network model, the accuracy rate and recall rate increase by 12.8% and 4.1%, respectively. Compared with manual counting, the average accuracy rate of field flower number is 80.32%, and the average accuracy rate of pod number is 82.17%. The research results show that models can effectively replace manual labor to complete the task of field soybean flower and pod identification and counting, and this application will promote the study of the basic laws of flower and pod fall and provide phenotypic investigation techniques. Full article