Impact of soil moisture stress during the silk emergence and grain-filling in maize.

Suboptimal soil moisture during the growing season often limits maize growth and yield. However, the growth stage-specific responses of maize to soil moisture regimes have not been thoroughly investigated. This study investigated the response of maize to five different soil moisture regimes, that are, 0.25, 0.20, 0.15, 0.10, and 0.05 m3 m-3 volumetric water content (VWC), during flowering and grain-filling stages. Sub-optimal soil moisture at the flowering and grain-filling stages reduced ear leaf stomatal conductance by 73 and 64%, respectively. An increase in stress severity caused significant reductions in ear leaf chlorophyll content and greenness-associated vegetation indices across growth stages. Fourteen days of soil moisture stress during flowering delayed silk emergence, reduced silk length (19%), and silk fresh weight (34%). Furthermore, sub-optimal soil moisture caused a significant reduction in both kernel number (53%) and weight (54%). Soil moisture stress at the flowering had a direct impact on kernel number and an indirect effect on kernel weight. During grain-filling, disruption of ear leaf physiology resulted in a 34% decrease in kernel weight and a 43% decrease in kernel number. Unlike grain-filling, treatments at the flowering significantly reduced kernel starch (3%) and increased protein by 29%. These findings suggest that developing reproductive stage stress-tolerant hybrids with improved resilience to soil moisture stress could help reduce the yield gap between irrigated and rainfed maize.

Comprehensive analysis of physiological and metabolomic responses to drought reveals specific modulation of acquired tolerance mechanisms in rice.

Mild stresses induce "acquired tolerance traits" (ATTs) that provide tolerance when stress becomes severe. Here, we identified the genetic variability in ATTs among a panel of rice germplasm accessions and demonstrated their relevance in protecting growth and productivity under water-limited conditions. Diverse approaches, including physiological screens, association mapping and metabolomics, were adopted and revealed 43 significant marker-trait associations. Nontargeted metabolomic profiling of contrasting genotypes revealed 26 "tolerance-related-induced" primary and secondary metabolites in the tolerant genotypes (AC-39000 and AC-39020) compared to the susceptible one (BPT-5204) under water-limited condition. Metabolites that help maintain cellular functions, especially Calvin cycle processes, significantly accumulated more in tolerant genotypes, which resulted in superior photosynthetic capacity and hence water use efficiency. Upregulation of the glutathione cycle intermediates explains the ROS homeostasis among the tolerant genotypes, maintaining spikelet fertility, and grain yield under stress. Bioinformatic dissection of a major effect quantitative trait locus on chromosome 8 revealed genes controlling metabolic pathways leading to the production of osmolites and antioxidants, such as GABA and raffinose. The study also led to the identification of specific trait donor genotypes that can be effectively used in translational crop improvement activities.

Genetic control of source-sink relationships in grain sorghum.

MAIN CONCLUSION: QTL hotspots identified for selected source-sink-related traits provide the opportunity for pyramiding favorable alleles for improving sorghum productivity under diverse environments. A sorghum bi-parental mapping population was evaluated under six different environments at Hays and Manhattan, Kansas, USA, in 2016 and 2017, to identify genomic regions controlling source-sink relationships. The population consisted of 210 recombinant inbred lines developed from US elite post-flowering drought susceptible (RTx430) and a known post-flowering drought tolerant cultivar (SC35). Selected physiological traits related to source (effective quantum yield of photosystem II and chlorophyll index), sink (grain yield per panicle) and panicle neck diameter were recorded during grain filling. The results showed strong phenotypic and genotypic association between panicle neck diameter and grain yield per panicle during mid-grain filling and at maturity. Multiple QTL model revealed 5-12 including 2-5 major QTL for each trait. Among them 3, 7 and 8 QTL for quantum yield, panicle neck diameter and chlorophyll index, respectively, have not been identified previously in sorghum. Phenotypic variation explained by QTL identified across target traits ranged between 5.5 and 25.4%. Panicle neck diameter and grain yield per panicle were positively associated, indicating the possibility of targeting common co-localized QTL to improve both traits simultaneously through marker-assisted selection. Three major QTL hotspots, controlling multiple traits were identified on chromosome 1 (52.23-61.18 Mb), 2 (2.52-11.43 Mb) and 3 (1.32-3.95 Mb). The identified genomic regions and underlying candidate genes can be utilized in pyramiding favorable alleles for improving source-sink relationships in sorghum under diverse environments.

Classical phenotyping and deep learning concur on genetic control of stomatal density and area in sorghum.

Stomatal density (SD) and stomatal complex area (SCA) are important traits that regulate gas exchange and abiotic stress response in plants. Despite sorghum (Sorghum bicolor) adaptation to arid conditions, the genetic potential of stomata-related traits remains unexplored due to challenges in available phenotyping methods. Hence, identifying loci that control stomatal traits is fundamental to designing strategies to breed sorghum with optimized stomatal regulation. We implemented both classical and deep learning methods to characterize genetic diversity in 311 grain sorghum accessions for stomatal traits at two different field environments. Nearly 12,000 images collected from abaxial (Ab) and adaxial (Ad) leaf surfaces revealed substantial variation in stomatal traits. Our study demonstrated significant accuracy between manual and deep learning methods in predicting SD and SCA. In sorghum, SD was 32%-39% greater on the Ab versus the Ad surface, while SCA on the Ab surface was 2%-5% smaller than on the Ad surface. Genome-Wide Association Study identified 71 genetic loci (38 were environment-specific) with significant genotype to phenotype associations for stomatal traits. Putative causal genes underlying the phenotypic variation were identified. Accessions with similar SCA but carrying contrasting haplotypes for SD were tested for stomatal conductance and carbon assimilation under field conditions. Our findings provide a foundation for further studies on the genetic and molecular mechanisms controlling stomata patterning and regulation in sorghum. An integrated physiological, deep learning, and genomic approach allowed us to unravel the genetic control of natural variation in stomata traits in sorghum, which can be applied to other plants.

Deterioration of ovary plays a key role in heat stress-induced spikelet sterility in sorghum.

In sorghum (Sorghum bicolor [L.] Moench), the impact of heat stress during flowering on seed set is known, but mechanisms that lead to tolerance are not known. A diverse set of sorghum genotypes was tested under controlled environment and field conditions to ascertain the impact of heat stress on time-of-day of flowering, pollen viability, and ovarian tissue. A highly conserved early morning flowering was observed, wherein >90% of spikelets completed flowering within 30 min after dawn, both in inbreds and hybrids. A strong quantitative impact of heat stress was recorded before pollination (reduced pollen viability) and post pollination (reduced pollen tube growth and linear decline in fertility). Although viable pollen tube did reach the micropylar region, 100% spikelet sterility was recorded under 40/22°C (day/night temperatures), even in the tolerant genotype Macia. Heat stress induced significant damage to the ovarian tissue near the micropylar region, leading to highly condensed cytoplasmic contents and disintegrated nucleolus and nucleus in the susceptible genotype RTx430. Whereas, relatively less damages to ovarian cell organelles were observed in the tolerant genotype Macia under heat stress. Integrating higher tolerance in female reproductive organ will help in effective utilization of the early morning flowering mechanism to enhance sorghum productivity under current and future hotter climate.

High night temperature induced changes in grain starch metabolism alters starch, protein, and lipid accumulation in winter wheat.

Unlike sporadic daytime heat spikes, a consistent increase in night-time temperatures can potentially derail the genetic gains being achieved. Ten winter wheat genotypes were exposed to six different night-time temperatures (15-27°C) during flowering and grain-filling stages in controlled environment chambers. We identified the night-time temperature of 23o C as the critical threshold beyond which a consistent decline in yields and quality was observed. Confocal laser scanning micrographs of central endosperm, bran, and germ tissue displayed differential accumulation of protein, lipid, and starch with increasing night-time temperatures. KS07077M-1 recorded a decrease in starch and an increase in protein and lipid in central endosperm with increasing night-time temperatures, whereas the same was significantly lower in the tolerant SY Monument. Expression analysis of genes encoding 21 enzymes (including isoforms) involved in grain-starch metabolism in developing grains revealed a high night-time temperature (HNT)-induced reduction in transcript levels of adenosine diphosphate glucose pyrophosphorylase small subunit involved in starch synthesis and a ≥2-fold increase in starch degrading enzymes isoamylase III, alpha-, and beta-amylase. The identified critical threshold, grain compositional changes, and the key enzymes in grain starch metabolism that lead to poor starch accumulation in grains establish the foundational knowledge for enhancing HNT tolerance in wheat.

Enhanced N-metabolites, ABA and IAA-conjugate in anthers instigate heat sensitivity in spring wheat.

Unraveling the metabolic and phytohormonal changes in anthers exposed to heat stress would help identify mechanisms regulating heat stress tolerance during the sensitive reproductive stage. Two spring wheat genotypes contrasting for heat tolerance were exposed to heat stress during heading in controlled environment chambers. Anthers were collected from main and primary spikes for metabolic and phytohormonal profiling. A significant reduction in seed set (38%), grain number (54%) and grain weight (52%) per plant was recorded in the sensitive (KSG1177) but not in the tolerant (KSG1214) genotype under heat stress compared to control. Anther metabolite accumulation did not vary quantitatively between main and primary spikes. Hierarchical clustering of the genotypes and treatments using metabolites and phytohormones revealed a distinct cluster for KSG1177 under heat stress from that of control and KSG1214. A significant increase in N-based amino acids, ABA, IAA-conjugate and a decrease in polyamines and organic acids were observed in wheat anthers exposed to heat stress. Unlike KSG1214, a significantly higher accumulation of amino acids, ABA and IAA-conjugate in anthers of the sensitive KSG1177 was recorded under heat stress. These findings provide the rationale and direction towards developing molecular markers for enhancing heat stress tolerance in wheat.

Carbon balance and source-sink metabolic changes in winter wheat exposed to high night-time temperature.

Carbon loss under high night-time temperature (HNT) leads to significant reduction in wheat yield. Growth chamber studies were carried out using six winter wheat genotypes, to unravel postheading HNT (23°C)-induced alterations in carbon balance, source-sink metabolic changes, yield, and yield-related traits compared with control (15°C) conditions. Four of the six tested genotypes recorded a significant increase in night respiration after 4 days of HNT exposure, with all the cultivars regulating carbon loss and demonstrating different degree of acclimation to extended HNT exposure. Metabolite profiling indicated carbohydrate metabolism in spikes and activation of the TriCarboxylic Acid (TCA) cycle in leaves as important pathways operating under HNT exposure. A significant increase in sugars, sugar-alcohols, and phosphate in spikes of the tolerant genotype (Tascosa) indicated osmolytes and membrane protective mechanisms acting against HNT damage. Enhanced night respiration under HNT resulted in higher accumulation of TCA cycle intermediates like isocitrate and fumarate in leaves of the susceptible genotype (TX86A5606). Lower grain number due to lesser productive spikes and reduced grain weight due to shorter grain-filling duration determined HNT-induced yield loss in winter wheat. Traits and mechanisms identified will help catalyze the development of physiological and metabolic markers for breeding HNT-tolerant wheat.

New candidate loci and marker genes on chromosome 7 for improved chilling tolerance in sorghum.

Sorghum is often exposed to suboptimal low temperature stress under field conditions, particularly at the seedling establishment stage. Enhancing chilling tolerance will facilitate earlier planting and so minimize the negative impacts of other stresses experienced at later growth stages. Genome-wide association mapping was performed on a sorghum association panel grown under control (30/20 °C; day/night) and chilling (20/10 °C) conditions. Genomic regions on chromosome 7, controlling the emergence index and seedling (root and shoot) vigor, were associated with increased chilling tolerance but they did not co-localize with undesirable tannin content quantitative trait loci (QTLs). Shoot and root samples from highly contrasting haplotype pairs expressing differential responses to chilling stress were used to identify candidate genes. Three candidate genes (an alpha/beta hydrolase domain protein, a DnaJ/Hsp40 motif-containing protein, and a YTH domain-containing RNA-binding protein) were expressed at significantly higher levels under chilling stress in the tolerant haplotype compared with the sensitive haplotype and BTx623. Moreover, two CBF/DREB1A transcription factors on chromosome 2 showed a divergent response to chilling in the contrasting haplotypes. These studies identify haplotype differences on chromosome 7 that modulate chilling tolerance by either regulating CBF or feeding back into this signaling pathway. We have identified new candidate genes that will be useful markers in ongoing efforts to develop tannin-free chilling-tolerant sorghum hybrids.

Genome-wide association mapping for phenotypic plasticity in rice.

Phenotypic plasticity of plants in response to environmental changes is important for adapting to changing climate. Less attention has been paid to exploring the advantages of phenotypic plasticity in resource-rich environments to enhance the productivity of agricultural crops. Here, we examined genetic variation for phenotypic plasticity in indica rice (Oryza sativa L.) across two diverse panels: (1) a Phenomics of Rice Adaptation and Yield (PRAY) population comprising 301 accessions; and (2) a Multi-parent Advanced Generation Inter-Cross (MAGIC) indica population comprising 151 accessions. Altered planting density was used as a proxy for elevated atmospheric CO2 response. Low planting density significantly increased panicle weight per plant compared with normal density, and the magnitude of the increase ranged from 1.10 to 2.78 times among accessions for the PRAY population and from 1.05 to 2.45 times for the MAGIC population. Genome-wide-association studies validate three Environmental Responsiveness (ER) candidate alleles (qER1-3) that were associated with relative response of panicle weight to low density. Two of these alleles were tested in 13 genotypes to clarify their biomass responses during vegetative growth under elevated CO2 in Japan. Our study provides evidence for polymorphisms that control rice phenotypic plasticity in environments that are rich in resources such as light and CO2 .

Is early morning flowering an effective trait to minimize heat stress damage during flowering in rice?

Higher spikelet sterility due to heat stress exposure during flowering in rice is becoming a major threat for sustaining productivity in tropical and sub-tropical regions. Therefore, exploiting and incorporating early morning flowering (EMF) trait into ongoing breeding pipelines could be an effective strategy to minimize the damage. In this study, we have focused on quantifying the time of day of flowering traits such as first spikelet opening time (FSOT) and peak spikelet opening time (PSOT) in a diverse set of cultivars (n = 289) representing major rice growing regions (13 tropical and 20 subtropical countries) over three years (wet season; WS-2012, dry season; DS-2013 and 2014), under field conditions. EMF traits (FSOT and PSOT) and spikelet sterility displayed significant (p < 0.001) variations among cultivars, both within and between seasons (WS and DS). Averaged across two dry seasons, the FSOT ranged between 2.35 h and 5.08 h after dawn compared to 3.05 h and 5.50 h during the WS, while, PSOT varied from 3.32 to 6.27 h in DS and from 3.50 to 7.05 h in WS. On average, PSOT was strongly associated with FSOT both in WS (R2 = 0.78) and DS (R2 = 0.77). A near-isogenic line (IR64 + qEMF3) effectively minimized the spikelet sterility by 71% during dry seasons under field conditions compared to 289 tropical and subtropical cultivars. None of the tropical and subtropical originated cultivars possess EMF trait including the popular IR64, thus indicating the usefulness of incorporating this trait to reduce heat stress damage under hotter climate. Our findings provide evidence for the effectiveness of the EMF trait in overcoming heat stress induced sterility under field conditions. Hence, it sounds logical to introgress EMF trait into currently growing popular rice cultivars for improving their resilience to heat stress episodes coinciding with flowering.

Impact of ultraviolet-B radiation on early-season morpho-physiological traits of indica and japonica rice genotypes.

Ultraviolet (UV)-B radiation is considered one of the major detrimental rays coming from the Sun. UV-B radiation has a harmful impact on plant growth and development. The effect of UV-B radiation was studied on 64 rice (Oryza sativa L.) genotypes during the vegetative season. An equal number of genotypes from the japonica (50%) and indica (50%) subspecies were phenotyped using the Soil-Plant-Atmosphere-Research (SPAR) units. The 10 kJ UV-B was imposed 12 days after planting (DAP) and continued for three weeks (21 d). Based on the combined ultraviolet-B radiation response index (CUVBRI) for each genotype, the 64 rice genotypes were classified into sensitive, moderately sensitive, moderately tolerant, and tolerant. Various shoot traits, such as plant height, tiller, and leaf numbers, were measured. We also studied critical root phenological traits like root volume, diameter, tips, and forks. Out of all the studied shoot traits, leaf area showed maximum reduction for both indica (54%) and japonica (48%). Among the root traits, root length decreased by negligible (1%) for indica as compared to japonica (5%), while root crossing and forks showed a maximum decline for japonica (37 and 42%), respectively. This study is timely, meaningful, and required because it will help breeders select a tolerant or sensitive rice line for better yield and production under abiotic stresses.

Effects of fine grinding on mid-infrared spectroscopic analysis of plant leaf nutrient content.

Fourier transform mid infrared (FT-MIR) spectroscopy combined with modeling techniques has been studied as a useful tool for multivariate chemical analysis in agricultural research. A drawback of this method is the sample preparation requirement, in which samples must be dried and fine ground for accurate model calibrations. For research involving large sample sets, this may dramatically increase the time and cost of analysis. This study investigates the effect of fine grinding on model performance using leaf tissue from a variety of crop species. Dried leaf samples (N = 300) from various environmental conditions were obtained with data on 11 nutrients measured using chemical methods. The samples were scanned with attenuated total reflectance (ATR) and diffuse reflectance (DRIFT) FT-MIR techniques. Scanning was repeated after fine grinding for 2, 5, and 10 min. The spectra were analyzed for the 11 nutrients using partial least squares regression with a 75%/25% split for calibration and validation and repeated for 50 iterations. All analytes except for boron, iron, and zinc were well-modeled (average R2 > 0.7), with higher R2 values on ATR spectra. The 5 min level of fine grinding was found to be most optimal considering overall model performance and sample preparation time.

Developing Functional Relationships between Soil Moisture Content and Corn Early-Season Physiology, Growth, and Development.

Drought is a severe threat to agriculture production that affects all growth stages of plants, including corn (Zea mays L.). Any factor affecting early seedling growth and development will significantly impact yield. Despite the recurrence of low rainfall during the growing seasons, corn responses to different early-season soil moisture content levels have not been investigated. In this study, we investigated how corn morpho-physiological and biomass traits responded to varied soil moisture content during the early vegetative stage. Two corn hybrids were grown in a pot-culture facility under five different soil moisture treatments (0.15, 0.12, 0.09, 0.06, and 0.03 m3 m-3 volumetric water content, VWC) to assess the growth and developmental responses to varied soil moisture content during early-season growth (V2 to V7) stage. Sub-optimal soil moisture content limited plant growth and development by reducing physiological and phenotypic expression. Stomatal conductance and transpiration were decreased by an average of 65% and 59% across stress treatments relative to optimum conditions. On average, soil moisture deficit reduced the total leaf area by 71% and 72% compared to the control in 'A6659VT2RIB' and 'P1316YHR', respectively. Shoot and root dry weights were reduced by 74% and 43% under 0.03 m3 m-3 VWC. An increase in the root-to-shoot ratio was noticed under low VWC conditions compared to the control. Based on the stress tolerance index, the physiology and leaf growth parameters were more sensitive to soil moisture deficit. Our results highlight the impact of sub-optimal soil moisture on physiology and morphological traits during early-season growth. 'P1316YHR' demonstrated better physiological performance under stress conditions, while 'A6659VT2RIB' produced relatively better root growth. The findings suggest that biomass partitioning between shoot and root components is dynamic and depends on stress intensity. The current findings can help to prioritize traits associated with the early-season drought tolerance in corn. The functional relationships developed between soil moisture content and growth and developmental responses can be integrated into corn crop modeling to allow better irrigation management decisions.

Developing functional relationships between waterlogging and cotton growth and physiology-towards waterlogging modeling.

Cotton crop is known to be poorly adapted to waterlogging, especially during the early growth stages. Developing functional relationships between crop growth and development parameters and the duration of waterlogging is essential to develop or improve existing cotton crop models for simulating the impact of waterlogging. However, there are only limited experimental studies conducted on cotton specifically aimed at developing the necessary functional relationships required for waterlogging modeling. Further research is needed to understand the effects of waterlogging on cotton crops and improve modeling capabilities in this area. The current study aimed to conduct waterlogging experiments and develop functional relationships between waterlogging and cotton growth and physiology. The experiments were conducted in pots, and the waterlogging was initiated by plugging the drain hole at the bottom of the pot using a wooden peg. In the experiments, eight waterlogging treatments, including the control treatment, were imposed at the vegetative growth stage (15 days after sowing). Control treatment had zero days of water-logged condition; other treatments had 2, 4, 6, 8, 10, 12, and 14 days of waterlogging. It took five days to reach zero oxygen levels and one to two days to return to control after the treatment. After a total treatment duration of 14 days (30 days after sowing), the growth, physiological, reproductive, and nutrient analysis was conducted. All physiological parameters decreased with the number of days of waterlogging. Flavonoid and anthocyanin index increased with increased duration of waterlogging. Photosynthesis and whole plant dry weight in continuously waterlogged conditions were 75% and 78% less compared to 0, and 2-day water-logged plants. Plant height, stem diameter, number of main stem leaves, leaf area, and leaf length also decreased with waterlogging duration. When waterlogging duration increased, leaf, stem, and root macronutrients decreased, while micronutrients showed mixed trends. Based on the experimental study, functional relationships (linear, quadratic, and exponential decay) and waterlogging stress response indices are developed between growth and development parameters and the duration of waterlogging. This can serve as a base for developing or improving process-based cotton models to simulate the impact of waterlogging.

Phenological stage and vegetation index for predicting corn yield under rainfed environments.

Uncrewed aerial systems (UASs) provide high temporal and spatial resolution information for crop health monitoring and informed management decisions to improve yields. However, traditional in-season yield prediction methodologies are often inconsistent and inaccurate due to variations in soil types and environmental factors. This study aimed to identify the best phenological stage and vegetation index (VI) for estimating corn yield under rainfed conditions. Multispectral images were collected over three years (2020-2022) during the corn growing season and over fifty VIs were analyzed. In the three-year period, thirty-one VIs exhibited significant correlations (r ≥ 0.7) with yield. Sixteen VIs were significantly correlated with the yield at least for two years, and five VIs had a significant correlation with the yield for all three years. A strong correlation with yield was achieved by combining red, red edge, and near infrared-based indices. Further, combined correlation and random forest an alyses between yield and VIs led to the identification of consistent and highest predictive power VIs for corn yield prediction. Among them, leaf chlorophyll index, Medium Resolution Imaging Spectrometer (MERIS) terrestrial chlorophyll index and modified normalized difference at 705 were the most consistent predictors of corn yield when recorded around the reproductive stage (R1). This study demonstrated the dynamic nature of canopy reflectance and the importance of considering growth stages, and environmental conditions for accurate corn yield prediction.

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.

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

Drought stress during the reproductive stage and declining soybean yield potential raise concerns about yield loss and economic return. In this study, ten cultivars were characterized for 20 traits to identify reproductive stage (R1-R6) drought-tolerant soybean. Drought stress resulted in a marked reduction (17%) in pollen germination. The reduced stomatal conductance coupled with high canopy temperature resulted in reduced seed number (45%) and seed weight (35%). Drought stress followed by rehydration increased the hundred seed weight at the compensation of seed number. Further, soybean oil decreased, protein increased, and cultivars responded differently under drought compared to control. In general, cultivars with high tolerance scores for yield displayed lower tolerance scores for quality content and vice versa. Among ten cultivars, LS5009XS and G4620RX showed maximum stress tolerance scores for seed number and seed weight. The observed variability in leaf reflectance properties and their relationship with physiological or yield components suggested that leaf-level sensing information can be used for differentiating drought-sensitive soybean cultivars from tolerant ones. The study led to the identification of drought-resilient cultivars/promising traits which can be exploited in breeding to develop multi-stress tolerant cultivars.

Climate trends and maize production nexus in Mississippi: empirical evidence from ARDL modelling.

Climate change poses a significant threat to agriculture. However, climatic trends and their impact on Mississippi (MS) maize (Zea mays L.) are unknown. The objectives were to: (i) analyze trends in climatic variables (1970 to 2020) using Mann-Kendall and Sen slope method, (ii) quantify the impact of climate change on maize yield in short and long run using the auto-regressive distributive lag (ARDL) model, and (iii) categorize the critical months for maize-climate link using Pearson's correlation matrix. The climatic variables considered were maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), precipitation (PT), relative humidity (RH), and carbon emissions (CO2). The pre-analysis, post-analysis, and model robustness statistical tests were verified, and all conditions were met. A significant upward trend in Tmax (0.13 °C/decade), Tmin (0.27 °C/decade), and CO2 (5.1 units/decade), and a downward trend in DTR ( - 0.15 °C/decade) were noted. The PT and RH insignificantly increased by 4.32 mm and 0.11% per decade, respectively. The ARDL model explained 76.6% of the total variations in maize yield. Notably, the maize yield had a negative correlation with Tmax for June, and July, with PT in August, and with DTR for June, July, and August, whereas a positive correlation was noted with Tmin in June, July, and August. Overall, a unit change in Tmax reduced the maize yield by 7.39% and 26.33%, and a unit change in PT reduced it by 0.65% and 2.69% in the short and long run, respectively. However, a unit change in Tmin, and CO2 emissions increased maize yield by 20.68% and 0.63% in the long run with no short run effect. Overall, it is imperative to reassess the agronomic management strategies, developing and testing cultivars adaptable to the revealed climatic trend, with ability to withstand severe weather conditions in ensuring sustainable maize production.

Low- and High-Temperature Phenotypic Diversity of Brassica carinata Genotypes for Early-Season Growth and Development.

Temperature is a major abiotic stress factor limiting plant growth and development during the early developmental stage. Information on carinata (Brassica carinata A. Braun) traits response to low and high temperatures is necessary for breeding or selecting genotypes suited for specific ecoregions, which is limited. In the present study, 12 carinata genotypes were evaluated under low (17/09°C), optimum (22/14°C), and high (27/19°C) day/night temperatures at the early developmental stage. This study quantified temperature effects on several physiological and morphological characteristics of 12-advanced carinata lines. High-temperature plants decreased (15%) the accumulation of flavonoids and increased the nitrogen balance index by 25%. Low-temperature treatment significantly inhibited the aboveground (plant height, leaf area, number, and shoot weight) and root (length, surface area, and weight) traits. Across all genotypes, the shoot weight decreased by 55% and the root weight by 49% under low temperature. On the other hand, the maximum proportion of biomass was partitioned to roots under low temperature than at the high temperature. A poor relationship (r 2 = 0.09) was found between low- and high-temperature indices, indicating differences in trait responses and tolerance mechanisms. AX17004 and AX17009 with higher root to shoot ratios might be suitable for late planting windows or regions with low-temperature spells. The two genotypes (AX17015 and AX17005) accumulated higher biomass under low- and high-temperature treatments can be used for planting in later summer or early winter. The identified low- and high-temperature stress-tolerant carinata genotypes could be a valuable resource for increasing stress tolerance during the early developmental stage.