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Aim: In the present study, we performed an in silico study on the triterpenoid compounds from the mangrove plant as potential COVID-19 main protease (Mpro) inhibitors, which can be used as a potential medicine target. Methods: In this study we performed molecular docking using AutoDock software. Results: The binding energies obtained through the docking of 6LU7 with beta-amyrin, betulin, germanicol, taraxerol, lupeol, lupane, simiarenol, tirucallol, ursolic acid, oleanolic acid, and alpha-amyrin were -8.37, −8.73, −8.06, −7.71, −8.32, −8.49, −8.16, −8.99, −9.24, −8.87, and −8.89 kcal/mol, respectively. Further, these results were also confirmed with drug-likeness properties by using Swiss ADME software. Conclusion: This study showed that triterpenoid compounds seemed to have the best potential to act as COVID-19 Mpro inhibitors, and that they contain a potential lead compound for the development of drugs, which can be used against SARS-CoV-2.

Cotton is a pivotal global commodity underscored by its economic value and widespread use. In the face of climate change, breeding resilient cultivars for variable environmental conditions becomes increasingly essential. However, the process of phenotyping, crucial to breeding programs, is often viewed as a bottleneck due to the inefficiency of traditional, low-throughput methods. To address this limitation, this study utilizes hyperspectral remote sensing, a promising tool for assessing crucial crop traits across forty cotton varieties. The results from this study demonstrated the effectiveness of four vegetation indices (VIs) in evaluating these varieties for water-use efficiency (WUE). The prediction accuracy for WUE through VIs such as the simple ratio water index (SRWI) and normalized difference water index (NDWI) was higher (up to R2 = 0.66), enabling better detection of phenotypic variations (p < 0.05) among the varieties compared to physiological-related traits (from R2 = 0.21 to R2 = 0.42), with high repeatability and a low RMSE. These VIs also showed high Pearson correlations with WUE (up to r = 0.81) and yield-related traits (up to r = 0.63). We also selected high-performing varieties based on the VIs, WUE, and fiber quality traits. This study demonstrated that the hyperspectral-based proximal sensing approach helps rapidly assess the in-season performance of varieties for imperative traits and aids in precise breeding decisions. [ABSTRACT FROM AUTHOR]

The increasing severity of drought has become a significant threat to global crop production. Early season drought in corn produces poor plant stand and grain yield. Thus, identifying corn hybrids for drought tolerance during the early season is important. Nineteen corn hybrids commonly grown in the Midsouthern US were assessed for drought tolerance using mini-hoop structures. Plants grown under non-stress conditions were exposed to three moisture levels at 100% (0.17 m3 m−3 soil; control), 66% (mild drought; DS1), and 33% (moderate drought; DS2) of the control from one to five leaf stages (V1 to V5). The physiological and morphological traits of corn hybrids were measured to assess variability in drought tolerance. When averaged across the hybrids, shoot parameters declined by 51% and 59% under DS1 and DS2 conditions, respectively, compared to the control. A decline in root traits was noticed under drought stress (38% under DS1 and 48% under DS2) compared to the control, revealing the shoot system sensitivity under drought conditions. In the principal component analysis, the first two principal components accounted for 66% of the phenotypic variation among the corn hybrids under drought stress. Total, shoot, leaf dry weights, root surface area, and root volume captured most of the phenotypic variation among the corn hybrids under drought. The results of the principal component analysis and drought stress response indices complimented the identification of 'A6659' and 'D57VP51' as drought-tolerant hybrids during the early seedling stage. These hybrids can be used as source material in developing drought-tolerant cultivars. Also, the tolerant hybrids will perform best under rainfed environments prone to early-season drought. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Chickpea is the second-most-cultivated legume globally, with India and Australia being the two largest producers. In both of these locations, the crop is sown on residual summer soil moisture and left to grow on progressively depleting water content, finally maturing under terminal drought conditions. The metabolic profile of plants is commonly, correlatively associated with performance or stress responses, e.g., the accumulation of osmoprotective metabolites during cold stress. In animals and humans, metabolites are also prognostically used to predict the likelihood of an event (usually a disease) before it occurs, e.g., blood cholesterol and heart disease. We sought to discover metabolic biomarkers in chickpea that could be used to predict grain yield traits under terminal drought, from the leaf tissue of young, watered, healthy plants. The metabolic profile (GC-MS and enzyme assays) of field-grown chickpea leaves was analysed over two growing seasons, and then predictive modelling was applied to associate the most strongly correlated metabolites with the final seed number plant−1. Pinitol (negatively), sucrose (negatively) and GABA (positively) were significantly correlated with seed number in both years of study. The feature selection algorithm of the model selected a larger range of metabolites including carbohydrates, sugar alcohols and GABA. The correlation between the predicted seed number and actual seed number was R2 adj = 0.62, demonstrating that the metabolic profile could be used to predict a complex trait with a high degree of accuracy. A previously unknown association between D-pinitol and hundred-kernel weight was also discovered and may provide a single metabolic marker with which to predict large seeded chickpea varieties from new crosses. The use of metabolic biomarkers could be used by breeders to identify superior-performing genotypes before maturity is reached. [ABSTRACT FROM AUTHOR]

Legumes are mostly grown rainfed and are exposed to various types of drought ranging from terminal drought to intermittent drought. The objective of this study was to compare the root anatomy of six major legume crops in relation to their drought adaptation strategies. Plants of chickpea (Cicer arietinum L.), groundnut (Arachis hypogaea L.), pigeonpea (Cajanus cajan [L.] Millsp.), cowpea (Vigna unguiculata L. walp.), soybean (Glycine max [L.] Merr.) and common bean (Phaseolus vulgaris L.) were grown along with pearl millet (Pennisetum glaucum [L.] R. Br.) in a Vertisol field during the rainy season of 2010. Four root segments from 35-day-old plants of each crop species were collected, 10 cm from the root tip and used for making transverse sections. These root segments were thinner in both groundnut and pigeonpea than in other legumes but similar to those of pearl millet. Soybean and pigeonpea had a relatively thinner cortex than the other legumes. Xylem vessel size and the numbers were apparently the most discriminating traits of legumes. Pigeonpea is equipped to conduct small quantities of water per unit time with a few narrow xylem vessels and that explains the conservative early growth of pigeonpea. Chickpea and cowpea showed moderate xylem passage per root indicating that they are capable of absorbing water moderately and are well equipped for regular drought episodes. The development of cortical and stele tissue and their proportion is markedly influenced by moisture availability to the root system.

Upland cotton encounters biotic and abiotic stresses during the growing season, which significantly affects the genetic potential of stress tolerance and productivity. The root-knot nematode (RKN) (Meloidogyne incognita) is a soilborne roundworm affecting cotton production. The occurrence of abiotic stress (drought stress, DS) can alter the plant–disease (RKN) interactions by enhancing host plant sensitivity. Experiments were conducted for two years under greenhouse conditions to investigate the effect of RKN and DS and their combination using nematode-resistant (Rk-Rn-1) and nematode susceptible (M8) cotton genotypes. These genotypes were subjected to four treatments: control (100% irrigation with no nematodes), RKN (100% irrigation with nematodes), DS (50% irrigation with no nematodes), and DS + RKN (50% irrigation with nematodes). We measured treatments-induced changes in cotton (i) leaf reflectance between 350 and 2500 nm; and (ii) physiology and biomass-related traits for diagnosing plant health under combined biotic and abiotic stresses. We used a maximum likelihood classification model of hyperspectral data with different dimensionality reduction techniques to learn RKN and DS stressors on two cotton genotypes. The results indicate (i) the RKN stress can be detected at an early stage of 10 days after infestation; (ii) RKN, DS, and DS + RKN can be detected with an accuracy of over 98% using bands from 350–1000 nm and 350–2500 nm. The genotypes 'Rk-Rn-1'and 'M8' showed differential responses to DS, RKN, and DS + RKN. With a few exceptions, all three stressors reduced the pigments, physiology, and biomass traits and the magnitude of reduction was higher in 'M8' than 'Rk-Rn-1'. Observed impact of stressors on plant growth followed DS + RKN > DS > RKN. Similarly, leaf reflectance properties exhibited a significant difference between individual stress treatments indicating that the hyperspectral sensor data can be used to discriminate RKN-infected plants from drought-stressed plants. Thus, our study reveals that hyperspectral and physiological changes in response to RKN and DS could help diagnose plant health before visual symptoms. [ABSTRACT FROM AUTHOR]

Drought and heat stresses are the major abiotic stress factors detrimental to maize (Zea mays L.) production. Much attention has been directed toward plant responses to heat or drought stress. However, maize reproductive stage responses to combined heat and drought remain less explored. Therefore, this study aimed to quantify the impact of optimum daytime (30°C, control) and warmer daytime temperatures (35°C, heat stress) on pollen germination, morpho‐physiology, and yield potential using two maize genotypes ("Mo17" and "B73") under contrasting soil moisture content, that is, 100% and 40% irrigation during flowering. Pollen germination of both genotypes decreased under combined stresses (42%), followed by heat stress (30%) and drought stress (19%). Stomatal conductance and transpiration were comparable between control and heat stress but significantly decreased under combined stresses (83% and 72%) and drought stress (52% and 47%) compared with the control. Genotype "Mo17" reduced its green leaf area to minimize the water loss, which appears to be one of the adaptive strategies of "Mo17" under stress conditions. The leaf reflectance of both genotypes varied across treatments. Vegetation indices associated with pigments (chlorophyll index of green, chlorophyll index of red edge, and carotenoid index) and plant health (normalized difference red‐edge index) were found to be highly sensitive to drought and combined stressors than heat stress. Combined drought and heat stresses caused a significant reduction in yield and yield components in both Mo17 (49%) and B73 (86%) genotypes. The harvest index of genotype "B73" was extremely low, indicating poor partitioning efficiency. At least when it comes to "B73," the cause of yield reduction appears to be the result of reduced sink number rather than the pollen and source size. To the best of our awareness, this is the first study that showed how the leaf‐level spectra, yield, and quality parameters respond to the short duration of independent and combined stresses during flowering in inbred maize. Further studies are required to validate the responses of potential traits involving diverse maize genotypes under field conditions. This study suggests the need to develop maize with improved tolerance to combined stresses to sustain production under increasing temperatures and low rainfall conditions. [ABSTRACT FROM AUTHOR]

Chickpea, the second most important legume crop, suffers major yield losses by terminal drought stress (DS). Stronger root system is known to enhance drought yields but this understanding remains controversial. To understand precisely the root traits contribution towards yield, 12 chickpea genotypes with well-known drought response were field evaluated under drought and optimal irrigation. Root traits, such as root length density (RLD), total root dry weight (RDW), deep root dry weight (deep RDW) and root:shoot ratio (RSR), were measured periodically by soil coring up to 1.2 m soil depth across drought treatments. Large variations were observed for RLD, RDW, deep RDW and RSR in both the drought treatments. DS increased RLD below 30 cm soil depth, deep RDW, RSR but decreased the root diameter. DS increased the genetic variation in RDW more at the penultimate soil depths. Genetic variation under drought was the widest for RLD ∼50 DAS, for deep RDW ∼50–75 DAS and for RSR at 35 DAS. Genotypes ICC 4958, ICC 8261, Annigeri, ICC 14799, ICC 283 and ICC 867 at vegetative stage and genotypes ICC 14778, ICCV 10, ICC 3325, ICC 14799 and ICC 1882 at the reproductive phase produced greater RLD. Path- and correlation coefficients revealed strong positive contributions of RLD after 45 DAS, deep RDW at vicinity of maturity and RSR at early podfill stages to yield under drought. Breeding for the best combination of profuse RLD at surface soil depths, and RDW at deeper soil layers, was proposed to be the best selection strategy, for an efficient water use and an enhanced terminal drought tolerance in chickpea. [ABSTRACT FROM AUTHOR]

Chickpea is the second most important legume crop largely grown under semi-arid tropics where terminal drought is one of the major constraints for its productivity. A trait-based selection had been considered more beneficial in drought tolerance breeding to overcome the environmental influence on drought yields. Large number of traits had been suggested in literature, with less indication on their importance and priority, for use in such breeding programs resulting in poor utilization of critical traits in drought tolerance breeding. To identify the most critical traits that contribute to grain yield under drought, 12 chickpea genotypes, with well-defined drought response, were field evaluated by sampling at regular intervals during the cropping period. Large range of variation was observed for shoot biomass productivity, specific leaf area (SLA) and leaf area index (LAI) at different days after sowings (DAS), canopy temperature depression (CTD) at mid-reproductive stages, growth duration and both morphological and analytical yield components. Grain yield under drought was closely associated with the rate of partitioning (p), crop growth rate (C), CTD, phenology, LAI at mid-pod fill stage, pod number m −2 at maturity, shoot biomass at reproductive growth stages and SLA at physiological maturity. The shoot trait(s) were prioritized based on their significance and contribution to drought tolerance. The trait(s) that conferred tolerance varied across genotypes. The order of traits/plant functions identified as important and critical for the drought tolerance were p, C, CTD, growth duration and other related traits. Relatively less important traits were LAI, SLA at the mid reproductive stage and pod number per unit area at maturity. The traits Dr, seeds pod −1 and 100-seed weight were found to be least important. Breeding for the best combination of p and C with the right phenology was proposed to be the best selection strategy to enhance terminal drought tolerance in chickpea. [ABSTRACT FROM AUTHOR]

Drought, ultraviolet-B (UV-B), and nitrogen stress are significant constraints for sweetpotato productivity. Their impact on plant growth and development can be acute, resulting in low productivity. Identifying phenotypes that govern stress tolerance in sweetpotatoes is highly desirable to develop elite cultivars with better yield. Ten sweetpotato cultivars were grown under nonstress (100% replacement of evapotranspiration (ET)), drought-stress (50% replacement of ET), UV-B (10 kJ), and low-nitrogen (20% LN) conditions. Various shoot and root morphological, physiological, and gas-exchange traits were measured at the early stage of the crop growth to assess its performance and association with the storage root number. All three stress factors caused significant changes in the physiological and root- and shoot-related traits. Drought stress reduced most shoot developmental traits (29%) to maintain root growth. UV-B stress increased the accumulation of plant pigments and decreased the photosynthetic rate. Low-nitrogen treatment decreased shoot growth (11%) and increased the root traits (18%). The highly stable and productive cultivars under all four treatments were identified using multitrait stability index analysis and weighted average of absolute scores (WAASB) analyses. Further, based on the total stress response indices, 'Evangeline', 'O'Henry', and 'Beauregard B-14' were identified as vigorous under drought; 'Evangeline', 'Orleans', and 'Covington' under UV-B; and 'Bonita', 'Orleans', and 'Beauregard B-14' cultivars showed greater tolerance to low nitrogen. The cultivars 'Vardaman' and 'NC05-198' recorded a low tolerance index across stress treatments. This information could help determine which plant phenotypes are desirable under stress treatment for better productivity. The cultivars identified as tolerant, sensitive, and well-adapted within and across stress treatments can be used as source materials for abiotic stress tolerance breeding programs. [ABSTRACT FROM AUTHOR]