Resilience of soybean cultivars to drought stress during flowering and early-seed setting stages

The Impact of Soybean Genotypes on Rhizosphere Microbial Dynamics and Nodulation Efficiency

Rhizosphere microbiome exerts a significant role in plant health, influencing nutrient availability, disease resistance, and overall plant growth. Establishing a robust and efficient nodulation process is essential for optimal nitrogen fixation in legumes like soybeans. Different soybean genotypes exhibit variations in their rhizosphere microbiome, potentially impacting nitrogen fixation through nodulation. However, a detailed understanding of how specific soybean genotypes influence rhizosphere microbial communities and nodulation patterns remains limited. Our study aims to investigate the relationship between rhizosphere microbial abundance and plant growth in four soybean genotypes. We evaluated plant growth parameters, including biomass, leaf area, and stomatal conductance, and identified significant genotypic differences in nodulation. Specifically, genotypes PI 458505 and PI 603490 exhibited high levels of nodulation, while PI 605839A and PI 548400 displayed low nodulation. 16S rRNA gene amplicon sequencing revealed diverse bacterial communities in the rhizosphere, with Proteobacteria as the dominant phylum. High-nodulation genotypes harbored more diverse microbial communities enriched with Actinobacteria and Acidobacteriota, while low-nodulation genotypes showed higher abundances of Firmicutes and Planctomycetota. Alpha and beta diversity analyses confirmed distinct microbial community structures between high- and low-nodulation groups. Our findings suggest that the rhizosphere microbiome significantly influences soybean growth and nodulation, highlighting the potential for genotype-driven strategies to enhance plant-microbe interactions and improve soybean productivity.

Integrative Approaches to Soybean Resilience, Productivity, and Utility: A Review of Genomics, Computational Modeling, and Economic Viability

Soybean is a vital crop globally and a key source of food, feed, and biofuel. With advancements in high-throughput technologies, soybeans have become a key target for genetic improvement. This comprehensive review explores advances in multi-omics, artificial intelligence, and economic sustainability to enhance soybean resilience and productivity. Genomics revolution, including marker-assisted selection (MAS), genomic selection (GS), genome-wide association studies (GWAS), QTL mapping, GBS, and CRISPR-Cas9, metagenomics, and metabolomics have boosted the growth and development by creating stress-resilient soybean varieties. The artificial intelligence (AI) and machine learning approaches are improving genetic trait discovery associated with nutritional quality, stresses, and adaptation of soybeans. Additionally, AI-driven technologies like IoT-based disease detection and deep learning are revolutionizing soybean monitoring, early disease identification, yield prediction, disease prevention, and precision farming. Additionally, the economic viability and environmental sustainability of soybean-derived biofuels are critically evaluated, focusing on trade-offs and policy implications. Finally, the potential impact of climate change on soybean growth and productivity is explored through predictive modeling and adaptive strategies. Thus, this study highlights the transformative potential of multidisciplinary approaches in advancing soybean resilience and global utility.

Microbiome Structures and Beneficial Bacteria in Soybean Roots Under Field Conditions of Prolonged High Temperatures and Drought Stress

Drought stress has a significant impact on agricultural productivity, affecting key crops such as soybeans, the second most widely cultivated crop in the United States. Endophytic and rhizospheric microbial diversity analyses were conducted with soybean plants cultivated during the 2023 growing season amid extreme weather conditions of prolonged high temperatures and drought in Louisiana. Specifically, surviving and non-surviving soybean plants were collected from two plots of a Louisiana soybean field severely damaged by extreme heat and drought conditions in 2023. Although no significant difference was observed between surviving and non-surviving plants in microbial diversity of the rhizosphere, obvious differences were found in the structure of the endophytic microbial community in root tissues between the two plant conditions. In particular, the bacterial genera belonging to Proteobacteria, Pseudomonas and Pantoea, were predominant in the surviving root tissues, while the bacterial genus Streptomyces was conspicuously dominant in the non-surviving (dead) root tissues. Co-occurrence patterns and network centrality analyses enabled us to discern the intricate characteristics of operational taxonomic units (OTUs) within endophytic and rhizospheric networks. Additionally, we isolated and identified bacterial strains that enhanced soybean tolerance to drought stresses, which were sourced from soybean plants under a drought field condition. The 16S rDNA sequence analysis revealed that the beneficial bacterial strains belong to the genera Acinetobacter, Pseudomonas, Enterobacter, and Stenotrophomonas. Specific bacterial strains, particularly those identified as Acinetobacter pittii and Pseudomonas sp., significantly enhanced plant growth metrics and reduced drought stress indices in soybean plants through seed treatment. Overall, this study advances our understanding of the soybean-associated microbiome structure under drought stress, paving the way for future research to develop innovative strategies and biological tools for enhancing soybean resilience to drought.

Using hyperspectral reflectance to detect changes in photosynthetic activity in Atractylodes chinensis leaves as a function of decreasing soil water content

Application of hyperspectral reflectance technology to track changes in photosynthetic activity in Atractylodes chinensis (A. chinensis) remains underexplored. This study aimed to investigate the relationship between hyperspectral reflectance and photosynthetic activity in the leaves of A. chinensis in response to a decrease in soil water content. Results demonstrated that the reflectance in both the visible light and near-infrared bands increased in conjunction with reduced soil water content. The derived vegetable indices of photochemical reflection index (PRI) and the pigment-specific simple ratio of chlorophyll b (PSSRb) gradually decreased. In contrast, the normalized difference in water index (NWI) and water index (WI) increased. Moreover, significant correlations were observed between PRI, PSSRb, WI, and NWI and photosynthetic activity indices, namely photosynthetic rate and total performance index. Consequently, hyperspectral reflection represents a productive approach for evaluating the influence of water deficit on photosynthetic activity in A. chinensis leaves.

Association mapping for water use efficiency in soybean identifies previously reported and novel loci and permits genomic prediction

Soybean is a major legume crop cultivated globally due to the high quality and quantity of its seed protein and oil. However, drought stress is the most significant factor that decreases soybean yield, and more than 90% of US soybean acreage is dependent on rainfall. Water use efficiency (WUE) is positively correlated with the carbon isotopic ratio 13C/12C (C13 ratio) and selecting soybean varieties for high C13 ratio may enhance WUE and help improve tolerance to drought. Our study objective was to identify genetic loci associated with C13 ratio using a diverse set of 205 soybean maturity group IV accessions, and to examine the genomic prediction accuracy of C13 ratio across a range of environments. An accession panel was grown and assessed across seven distinct combinations of site, year and treatment, with five site-years under irrigation and two site-years under drought stress. Genome-wide association mapping (GWAM) analysis identified 103 significant single nucleotide polymorphisms (SNPs) representing 93 loci associated with alterations to C13 ratio. Out of these 93 loci, 62 loci coincided with previous studies, and 31 were novel. Regions tagged by 96 significant SNPs overlapped with 550 candidate genes involved in plant stress responses. These confirmed genomic loci could serve as a valuable resource for marker-assisted selection to enhance WUE and drought tolerance in soybean. This study also demonstrated that genomic prediction can accurately predict C13 ratio across different genotypes and environments and by examining only significant SNPs identified by GWAM analysis, higher prediction accuracies (P ≤ 0.05; 0.51 ≤ r ≤ 0.65) were observed. We generated genomic estimated breeding values for each genotype in the entire USDA-GRIN germplasm collection for which there was marker data. This information was used to identify the top ten extreme genotypes for each soybean maturity group, which could serve as valuable genetic and physiological resources for future breeding and physiological studies.

Explainable Artificial Intelligence to Predict the Water Status of Cotton (Gossypium hirsutum L., 1763) from Sentinel-2 Images in the Mediterranean Area

Climate change and water scarcity bring significant challenges to agricultural systems in the Mediterranean region. Novel methods are required to rapidly monitor the water stress of the crop to avoid qualitative losses of agricultural products. This study aimed to predict the stem water potential of cotton (Gossypium hirsutum L., 1763) using Sentinel-2 satellite imagery and machine learning techniques to enhance monitoring and management of cotton's water status. The research was conducted in Rutigliano, Southern Italy, during the 2023 cotton growing season. Different machine learning algorithms, including random forest, support vector regression, and extreme gradient boosting, were evaluated using Sentinel-2 spectral bands as predictors. The models' performance was assessed using R2 and root mean square error (RMSE). Feature importance was analyzed using permutation importance and SHAP methods. The random forest model using Sentinel-2 bands' reflectance as predictors showed the highest performance, with an R2 of 0.75 (±0.07) and an RMSE of 0.11 (±0.02). XGBoost (R2: 0.73 ± 0.09, RMSE: 0.12 ± 0.02) and AdaBoost (R2: 0.67 ± 0.08, RMSE: 0.13 ± 0.02) followed in performance. Visible (blue and red) and red edge bands were identified as the most influential predictors. The trained RF model was used to model the seasonal trend of cotton's stem water potential, detecting periods of acute and moderate water stress. This approach demonstrates the prospective for high-frequency, non-invasive monitoring of cotton's water status, which could support smart irrigation strategies and improve water use efficiency in Mediterranean cotton production.

Differential Drought Responses of Soybean Genotypes in Relation to Photosynthesis and Growth-Yield Attributes

Water scarcity leads to significant ecological challenges for global farming production. Sustainable agriculture depends on developing strategies to overcome the impacts of drought on important crops, including soybean. In this present study, seven promising soybean genotypes were evaluated for their drought tolerance potential by exposing them to water deficit conditions. The control group was maintained at 100% field capacity (FC), while the drought-treated group was maintained at 50% FC on a volume/weight basis. This treatment was applied at the second trifoliate leaf stage and continued until maturity. Our results demonstrated that water shortage exerted negative impacts on soybean phenotypic traits, physiological and biochemical mechanisms, and yield output in comparison with normal conditions. Our results showed that genotype G00001 exhibited the highest leaf area plant-1 (483.70 cm2), photosynthetic attributes like stomatal conductance (gs) (0.15 mol H2O m-2 s-1) and photosynthetic rate (Pn) (13.73 μmol CO2 m-2 s-1), and xylem exudation rate (0.25 g h-1) under drought conditions. The G00001 genotype showed greater leaf greenness by preserving photosynthetic pigments (total chlorophylls (Chls) and carotenoids; 4.23 and 7.34 mg g-1 FW, respectively) in response to drought conditions. Soybean plants accumulated high levels of stress indicators like proline and malondialdehyde when subjected to drought stress. However, genotype G00001 displayed lower levels of proline (4.49 μg g-1 FW) and malondialdehyde (3.70 μmol g-1 FW), indicating that this genotype suffered from less oxidative stress induced by drought stress compared to the other investigated soybean genotypes. Eventually, the G00001 genotype had a greater yield in terms of seeds pod-1 (SP) (1.90) and 100-seed weight (HSW) (14.60 g) under drought conditions. On the other hand, BD2333 exhibited the largest decrease in plant height (37.10%), pod number plant-1 (85.90%), SP (56.20%), HSW (54.20%), gs (90.50%), Pn (71.00%), transpiration rate (59.40%), relative water content (34.40%), Chl a (79.50%), total Chls (72.70%), and carotenoids (56.70%), along with the maximum increase in water saturation deficit (290.40%) and malondialdehyde content (280.30%) under drought compared to control conditions, indicating its higher sensitivity to drought stress. Our findings suggest that G00001 is a promising candidate to consider for field trials and further evaluation of its molecular signature may help breeding other elite cultivars to develop drought-tolerant, high-yielding soybean varieties.

Resilience of soybean genotypes to drought stress during the early vegetative stage

Drought stress poses a significant risk to soybean production, as it relies on optimum rainfall under rainfed conditions. Exposure to brief dry periods during early vegetative growth impacts soybean growth and development. Choosing a genotype that can withstand stress with minimal impact on physiology and growth might help sustain biomass or yields under low rainfall conditions. Therefore, this study characterized 64 soybean genotypes for traits associated with drought tolerance during the early vegetative stage under two soil moisture treatments, 100% evapotranspiration (well-watered) and 50% evapotranspiration (drought), using the Soil-Plant-Atmosphere Research (SPAR) units. Eighteen morpho-physiological traits responses were assessed, and their relationship with the early vegetative drought tolerance was investigated. Drought stress significantly increased root weight, root volume, and root-to-shoot ratio but reduced shoot weight. Drought-stressed plants increased the canopy temperature by  3.1 °C. Shoot weight positively correlated with root surface area (r = 0.52, P < 0.001) and root weight (r = 0.65, P < 0.001). There was a strong negative correlation between shoot weight and root-to-shoot ratio (P < 0.01). Further, the combined drought response index was strongly associated with the root response index and weakly with the physiological response index. These findings suggest that genotypes (S55-Q3 and R2C4775) with high above-ground biomass with a balanced root-to-shoot ratio improves drought tolerance during the early vegetative. These genotypes could serve as valuable genetic resources to dissect the molecular networks underlying drought tolerance and ultimately be used in breeding programs to improve root ability at the early vegetative stage.

Pollen thermotolerance of a widespread plant, Lotus corniculatus, in response to climate warming: possible local adaptation of populations from different elevations

One of the most vulnerable phases in the plant life cycle is sexual reproduction, which depends on effective pollen transfer, but also on the thermotolerance of pollen grains. Pollen thermotolerance is temperature-dependent and may be reduced by increasing temperature associated with global warming. A growing body of research has focused on the effect of increased temperature on pollen thermotolerance in crops to understand the possible impact of temperature extremes on yield. Yet, little is known about the effects of temperature on pollen thermotolerance of wild plant species. To fill this gap, we selected Lotus corniculatus s.l. (Fabaceae), a species common to many European habitats and conducted laboratory experiments to test its pollen thermotolerance in response to artificial increase in temperature. To test for possible local adaptation of pollen thermal tolerance, we compared data from six lowland (389-451 m a.s.l.) and six highland (841-1,030 m a.s.l.) populations. We observed pollen germination in vitro at 15 °C, 25 °C, 30 °C, and 40 °C. While lowland plants maintained a stable germination percentage across a broad temperature range (15-30 °C) and exhibited reduced germination only at extremely high temperatures (40 °C), highland plants experienced reduced germination even at 30 °C-temperatures commonly exceeded in lowlands during warm summers. This suggests that lowland populations of L. corniculatus may be locally adapted to higher temperature for pollen germination. On the other hand, pollen tube length decreased with increasing temperature in a similar way in lowland and highland plants. The overall average pollen germination percentage significantly differed between lowland and highland populations, with highland populations displaying higher germination percentage. On the other hand, the average pollen tube length was slightly smaller in highland populations. In conclusion, we found that pollen thermotolerance of L. corniculatus is reduced at high temperature and that the germination of pollen from plant populations growing at higher elevations is more sensitive to increased temperature, which suggests possible local adaptation of pollen thermotolerance.

Physiological Regulation of Photosynthetic-Related Indices, Antioxidant Defense, and Proline Anabolism on Drought Tolerance of Wild Soybean (Glycine soja L.)

Wild soybean (Glycine soja L.), drought-tolerant cultivar Tiefeng 31 (Glycine max L.), and drought-sensitive cultivar Fendou 93 (Glycine max L.) were used as materials to investigate the drought tolerance mechanism after 72 h 2.5 M PEG 8000 (osmotic potential -0.54 MPa)-simulated drought stress at the seedling stage. The results indicated that the leaves of the G. soja did not wilt under drought stress. However, both the drought-tolerant and drought-sensitive cultivated soybean cultivars experienced varying degrees of leaf wilt. Notably, the drought-sensitive cultivated soybean cultivars exhibited severe leaf wilt after the drought stress. Drought stress was determined to have a significant impact on the dry matter of the above-ground part of the drought-sensitive cultivar Fendou 93, followed by the drought-tolerant cultivar Tiefeng 31, with the lowest reduction observed in G. soja. Furthermore, the presence of drought stress resulted in the closure of leaf stomata. G. soja exhibited the highest proportion of stomatal opening per unit area, followed by the drought-tolerant cultivar Tiefeng 31, while the drought-sensitive cultivar Fendou 93 displayed the lowest percentage. Photosynthesis-related indexes, including photosynthetic rate, intercellular CO2, transpiration rate, and stomatal conductance, decreased in Fendou 93 and Tiefeng 31 after drought stress, but increased in G. soja. In terms of the antioxidant scavenging system, lower accumulation of malondialdehyde (MDA) was observed in G. soja and Tiefeng 31, along with higher activities of superoxide dismutase (SOD, EC 1.15.1.1) and catalase (CAT, EC 1.11.1.6) to counteract excess reactive oxygen species and maintain cell membrane integrity. In contrast, the drought-sensitive cultivar Fendou 93 had higher MDA content and higher activities of ascorbate peroxidase (APX, EC 1.11.1.11) and peroxidase (POD, 1.11.1.7). G. soja and Tiefeng 31 also exhibited less accumulation of osmolytes, including soluble sugar, soluble protein, and free proline content. The activities of δ-OAT, ProDH, and P5CS, key enzymes in proline anabolism, showed an initial increase under drought stress, followed by a decrease, and then an increase again at the end of drought stress in G. soja. Before drought stress, Tiefeng 31 had higher activities of ProDH and P5CS, which decreased with prolonged drought stress. Fendou 93 experienced an increase in the activities of δ-OAT, ProDH, and P5CS under drought stress. The δ-OAT gene expression levels were up-regulated in all three germplasms. The expression levels of the P5CS gene in Fendou 93 and Tiefeng 31 were down-regulated, while G. soja showed no significant change. The expression of the P5CR gene and ProDH gene was down-regulated in Fendou 93 and Tiefeng 31, but up-regulated in G. soja. This indicates that proline content is regulated at both the transcription and translation levels.

Integrated crop and livestock systems increase both climate change adaptation and mitigation capacities

Integrated crop-livestock systems (ICLS) are proposed as key solutions to the various challenges posed to present-day agriculture which must guarantee high and stable yields while minimizing its impacts on the environment. Yet the complex relationships between crops, grasslands and animals on which they rely demand careful and precise management. In this study, from a 18-year ICLS field experiment in Brazil, that consists in annual no-till soybean-pastures grazed by beef cattle, we investigated the impacts of contrasted pastures grazing intensities (defined by sward heights of 10, 20, 30 and 40 cm, plus an ungrazed treatment) on the agroecosystem productivity and soil organic carbon (SOC) under both historical and future (2040-2070, RCP8.5) climatic conditions. We used an innovative methodology to model the ICLS with the STICS soil-crop model, which was validated with field observations. Results showed that the total system production increased along with grazing intensity because of higher stocking rates and subsequent live weight gains. Moderate and light grazing intensities (30 and 40 cm sward heights) resulted in the largest increase in SOC over the 18-year period, with all ICLS treatments leading to greater SOC contents than the ungrazed treatment. When facing climate change under future conditions, all treatments increased in productivity due to the CO2 fertilization effect and the increases in organic amendments that result from the larger stocking rate allowed by the increased pasture carrying capacity. Moderate grazing resulted in the most significant enhancements in productivity and SOC levels. These improvements were accompanied by increased resistance to both moderate and extreme climatic events, benefiting herbage production and live weight gain. Globally, our results show that adding a trophic level (i.e. herbivores) into cropping systems, provided that their carrying capacities are respected, proved to increase their ability to withstand climate change and to contribute to its mitigation.

Development of KASP markers assisted with soybean drought tolerance in the germination stage based on GWAS

Soybean [Glycine max(L.)Merr.] is a leading oil-bearing crop and cultivated globally over a vast scale. The agricultural landscape in China faces a formidable challenge with drought significantly impacting soybean production. In this study, we treated a natural population of 264 Chinese soybean accessions using 15% PEG-6000 and used GR, GE, GI, RGR, RGE, RGI and ASFV as evaluation index. Using the ASFV, we screened 17 strong drought-tolerant soybean germplasm in the germination stage. Leveraging 2,597,425 high-density SNP markers, we conducted Genome-Wide Association Studies (GWAS) and identified 92 SNPs and 9 candidate genes significantly associated with drought tolerance. Furthermore, we developed two KASP markers for S14_5147797 and S18_53902767, which closely linked to drought tolerance. This research not only enriches the pool of soybean germplasm resources but also establishes a robust foundation for the molecular breeding of drought tolerance soybean varieties.

Climate trends and soybean production since 1970 in Mississippi: Empirical evidence from ARDL model

Studying historical response of crops to weather conditions at a finer scale is essential for devising agricultural strategies tailored to expected climate changes. However, determining the relationship between crop and climate in Mississippi (MS) remains elusive. Therefore, this research attempted to i) estimate climate trends between 1970 and 2020 in MS during the soybean growing season (SGS) using the Mann-Kendall and Sen slope method, ii) calculate the impact of climate change on soybean yield using an auto-regressive distributive lag (ARDL) econometric model, and iii) identify the most critical months from a crop-climate perspective by generating a correlation between the detrended yield and the monthly average for each climatic variable. Specific variables considered were maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), precipitation (PT), carbon dioxide emissions (CO2), and relative humidity (RH). All required diagnostic-tests i.e., pre-analysis, post-analysis, model-sensitivity, and assessing the models' goodness-of-fit were performed and statistical standards were met. A positive trend in Tmin (+0.25 °C/decade), and a negative trend in DTR (-0.18 °C/decade) was found. Although Tmax, PT, and RH showed non-significant trends, numerical changes were noted as +0.11 °C/decade, +3.03 mm/decade, and -0.06 %/decade, respectively. Furthermore, soybean yield was positively correlated with Tmin (in June and September), PT (in July and August), and RH (in July), but negatively correlated with Tmax (in July and August) and DTR (in June, July, and August). Soybean yield was observed to be significantly reduced by 18.11 % over the long-term and by 5.51 % over the short-term for every 1 °C increase in Tmax. With every unit increase in Tmin and CO2 emissions, the yield of soybeans increased significantly by 7.76 % and 3.04 %, respectively. Altogether, soybeans in MS exhibited variable sensitivity to short- and long-terms climatic changes. The results highlight the importance of testing climate-resilient agronomic practices and cultivars that encompass asymmetric sensitivities in response to climatic conditions of MS.

Chitosan-GSNO nanoparticles: a positive modulator of drought stress tolerance in soybean

BACKGROUND

Chitosan biopolymer is an emerging non-toxic and biodegradable plant elicitor or bio-stimulant. Chitosan nanoparticles (CSNPs) have been used for the enhancement of plant growth and development. On the other hand, NO is an important signaling molecule that regulates several aspects of plant physiology under normal and stress conditions. Here we report the synthesis, characterization, and use of chitosan-GSNO nanoparticles for improving drought stress tolerance in soybean.

RESULTS

The CSGSNONPs released NO gas for a significantly longer period and at a much lower rate as compared to free GSNO indicating that incorporation of GSNO in CSNPs can protect the NO-donor from rapid decomposition and ensure optimal NO release. CS-GSNONPs improved drought tolerance in soybean plants reflected by a significant increase in plant height, biomass, root length, root volume, root surface area, number of root tips, forks, and nodules. Further analyses indicated significantly lower electrolyte leakage, higher proline content, higher catalase, and ascorbate peroxidase activity, and reduction in MDA and H2O2 contents after treatment with 50 μM CS-GSNONPs under drought stress conditions. Quantitative real-time PCR analysis indicated that CS-GSNONPs protected against drought-induced stress by regulating the expression of drought stress-related marker genes such as GmDREB1a, GmP5CS, GmDEFENSIN, and NO-related genes GmGSNOR1 and GmNOX1.

CONCLUSIONS

This study highlights the potential of nano-technology-based delivery systems for nitric oxide donors to improve plant growth, and development and protect against stresses.

Influence of Exogenous 24-Epicasterone on the Hormonal Status of Soybean Plants

Brassinosteroids (BRs) are key phytohormones involved in the regulation of major processes of cell metabolism that guide plant growth. In the past decades, new evidence has made it clear that BRs also play a key role in the orchestration of plant responses to many abiotic and biotic stresses. In the present work, we analyzed the impact of foliar treatment with 24-epicastasterone (ECS) on the endogenous content of major phytohormones (auxins, salicylic acid, jasmonic acid, and abscisic acid) and their intermediates in soybean leaves 7 days following the treatment. Changes in the endogenous content of phytohormones have been identified and quantified by LC/MS. The obtained results point to a clear role of ECS in the upregulation of auxin content (indole-3-acetic acid, IAA) and downregulation of salicylic, jasmonic, and abscisic acid levels. These data confirm that under optimal conditions, ECS in tested concentrations of 0.25 µM and 1 µM might promote growth in soybeans by inducing auxin contents. Benzoic acid (a precursor of salicylic acid (SA)), but not SA itself, has also been highly accumulated under ECS treatment, which indicates an activation of the adaptation strategies of cell metabolism to possible environmental challenges.

Enhancement of osmotic stress tolerance in soybean seed germination by bacterial bioactive extracts

Soybean (Glycine max (L.) Merr.) is important to the global food industry; however, its productivity is affected by abiotic stresses such as osmosis, flooding, heat, and cold. Here, we evaluated the bioactive extracts of two biostimulant bacterial strains, Bacillus butanolivorans KJ40 and B. siamensis H30-3, for their ability to convey tolerance to osmotic stress in soybean seeds during germination. Soybean seeds were dip-treated in extracts of KJ40 (KJ40E) or H30-3 (H30-3E) and incubated with either 0% or 20% polyethylene glycol 6000 (PEG), simulating drought-induced osmotic stress. We measured malondialdehyde content as a marker for lipid peroxidation, as well as the activity of antioxidant enzymes, including catalase, glutathione peroxidase, and glutathione reductase, together with changes in sugars content. We also monitored the expression of genes involved in the gibberellic acid (GA)-biosynthesis pathway, and abscisic acid (ABA) signaling. Following osmotic stress in the extract-treated seeds, malondialdehyde content decreased, while antioxidant enzyme activity increased. Similarly, the expression of GA-synthesis genes, including GmGA2ox1 and GmGA3 were upregulated in KJ40E-dipped seeds at 12 or 6 h after treatment, respectively. The ABA signaling genes GmABI4 and GmDREB1 were upregulated in H30-3E- and KJ40E-treated seeds at 0 and 12 h after treatment under osmotic stress; however, GmABI5, GmABI4, and GmDREB1 levels were also elevated in the dip-treated seeds in baseline conditions. The GA/ABA ratio increased only in KJ40E-treated seeds undergoing osmotic stress, while glucose content significantly decreased in H30-3E-treated seeds at 24 h after treatment. Collectively, our findings indicated that dip-treatment of soybean seeds in KJ40E and H30-3E can enhance the seeds' resistance to osmotic stress during germination, and ameliorate cellular damage caused by secondary oxidative stress. This seed treatment can be used agriculturally to promote germination under drought stress and lead to increase crop yield and quality.

Colchicine-Induced Polyploidy in Leguminous Crops Enhances Morpho-Physiological Characteristics for Drought Stress Tolerance

Legumes play a significant role in the alleviation of food insecurity, maintaining soil fertility, and achieving sustainable crop production under adverse environmental conditions. The increased demand in legume production contemplates that attention on the genetic improvement of these crops through various means such as genetic engineering and mutation breeding should take a centre stage in global agriculture. Therefore, this paper provides a succinct analysis of the currently available literature on morphological and physiological traits in polyploidised leguminous plants to counter the adverse effects of drought stress. The effects of colchicine on various morphological and physiological traits of polyploidised legumes compared to their diploid counterparts were examined. Numerous reports revealed variations in these traits, such as improved root and shoot growth, plant biomass, chloroplastidic content, protein, RNA, and DNA. The differences observed were also associated with the strong relationship between plant ploidy induction and colchicine application. Furthermore, the analysis indicated that polyploidisation remains dose-dependent and may be achievable within a shorter space of time as this antimitotic chemical interferes with chromosome separations in somatic plant cells. The efficiency of this process also depends on the advancement of treatment conditions (in vitro, in vivo, or ex vitro) and the successful regeneration of polyploidised plants for adaptation under drought stress conditions. As such, the improvement in metabolite profile and other essential growth characteristics serves as a clear indication that induced polyploidy needs to be further explored to confer resilience to environmental stress and improve crop yield under drought stress conditions in leguminous plants.

Impact of salt stress on physiology, leaf mass, and nutrient accumulation in romaine lettuce

The impact of salt stress is becoming more prevalent each year, largely due to the effects of climate change. Limited availability of salt-free water is rising concern for hydroponics lettuce production. Despite evidence supporting salt stress-induced quality losses and physiological changes, studies on romaine lettuce salt-stress tolerance are limited. This study examined the mechanism underlying the sodium chloride (NaCl) tolerance (0, 50, 100, and 150 mM) of lettuce on its growth and nutrition at late-rosette and early head-formation stages. Results revealed 76% fresh mass reduction under increased NaCl at both stages. The study also found unchanged carbon assimilation with reduced stomatal conductance under increased NaCl. Salt-stressed lettuce accumulated more boron and iron but had reduced phosphorus and calcium. Phenolics and sugars increased linearly under salt stress, suggesting that lettuce responds to increased oxidative stress at both stages. A positive association between salt treatment and sodium to potassium ion ratio indicated lettuce sensitivity to salt stress at both stages.