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The Air Pollution Tolerance Index (APTI) and Anticipated Performance Index (API) of Azadirachta indica, Ficus benghalensis, and Ficus religiosa were compared to assess their tolerance to air pollution in different environmental setups. The study was conducted at six different locations with different environmental setups, including Urban, Industrial, Institutional and Agricultural. The parameters used for APTI were pH, relative water content, total chlorophyll content, and ascorbic acid content in the leaves, while API was calculated using APTI along with the socio-economic characteristics of the targeted species. Three species were selected, with nine replicates of each species from each setup (i.e., 6×9×3, which means a total of 162 samples) were analyzed for APTI during the winter season, when there is a lower mixing height that prevents the dispersion of pollutants and makes the environment highly polluted, and trees show high tolerance in a polluted environment. The APTI values of all the targeted species were higher in industrial setups than in the other environmental setups, i.e., 20.42 ± 1.65 for A. indica, 14.75 ± 0.53 for F. benghalensis, and 13.39 ± 1.11 for F. religiosa. The sample t-test showed a significant difference in the APTI of the industrial setup and other setups (p=0.0000). A. indica was found to be a tolerant species, and F. benghalensis and F. religiosa were intermediate-tolerant species based on APTI. F. benghalensis and F. religiosa fall under the excellent and A. indica falls under the very good category based on API. Based on these two indices, the best tree species were identified for plantation and the abatement of air pollution in industrial areas.

Increasing soil salinity due to global warming severely restricts crop growth and yield. To select and recommend salt-tolerant cultivars, extensive genotypic screening and examination of plants’ morpho-physiological responses to salt stress are required. In this study, 18 prescreened maize hybrid cultivars were examined at the early growth stage under a hydroponic system using multivariate analysis to demonstrate the genotypic and phenotypic variations of the selected cultivars under salt stress. The seedlings of all maize cultivars were evaluated with two salt levels: control (without NaCl) and salt stress (12 dS m−1 simulated with NaCl) for 28 d. A total of 18 morpho-physiological and ion accumulation traits were dissected using multivariate analysis, and salt tolerance index (STI) values of the examined traits were evaluated for grouping of cultivars into salt-tolerant and -sensitive groups. Salt stress significantly declined all measured traits except root–shoot ratio (RSR), while the cultivars responded differently. The cultivars were grouped into three clusters and the cultivars in Cluster-1 such as Prabhat, UniGreen NK41, Bisco 51, UniGreen UB100, Bharati 981 and Star Beej 7Star exhibited salt tolerance to a greater extent, accounting for higher STI in comparison to other cultivars grouped in Cluster-2 and Cluster-3. The high heritability (h2bs, >60%) and genetic advance (GAM, >20%) were recorded in 13 measured traits, indicating considerable genetic variations present in these traits. Therefore, using multivariate analysis based on the measured traits, six hybrid maize cultivars were selected as salt-tolerant and some traits such as Total Fresh Weight (TFW), Total Dry Weight (TDW), Total Na+, Total K+ contents and K+–Na+ Ratio could be effectively used for the selection criteria evaluating salt-tolerant maize genotypes at the early seedling stage.

Lentil (Lens culinaris Medikus) is one of the most important cool season food legume crops grown in many countries. Seeds are typically rich in protein, fiber, prebiotic carbohydrates and minerals, such as iron and zinc. With changing climate and variability, the lentil crop faces frequent droughts and heat stress of varying intensity in its major production zones. In the present study, a set of 162 lentil accessions selected through the Focused Identification of Germplasm Strategy (FIGS) were screened for tolerance to heat stress and combined heat-drought stresses under field conditions at two contrasting locations, namely Marchouch and Tessaout in Morocco. The results showed a significant genotypic variation for heat tolerance and combined heat-drought tolerance among the accessions at both locations. Based on the heat tolerance index (HTI), accessions, namely ILL 7833, ILL 6338 and ILL 6104, were selected as potential sources of heat tolerance at Marchouch, and ILL 7814 and ILL 8029 at Tessaout. Using the stress tolerance index (STI), ILL 7835, ILL 6075 and ILL 6362 were identified as the most tolerant lines (STI > 1) at Marchouch, and ILL 7814, ILL 7835 and ILL 7804 (STI > 1) at Tessaout, under the combined heat-drought stress conditions. Accession ILL 7835 was identified as a good source of stable tolerance to heat stress and combined heat-drought stress at both locations.

Maize (Zea mays subsp. mays) is a staple food crop in the world. Drought is one of the most common abiotic challenges that maize faces when it comes to growth, development, and production. Further knowledge of drought tolerance could aid with maize production. However, there has been less study focused on investigating in depth the drought tolerance of inbred maize lines using artificial intelligence techniques. In this study, multi-layer perceptron (MLP), support vector machine (SVM), genetic algorithm-based multi-layer perceptron (MLP-GA), and genetic algorithm-based support vector machine (SVM-GA) hybrid artificial intelligence algorithms were used for the prediction of drought tolerance and stress tolerance indices in teosinte maize lines. Correspondingly, the gamma test technique was applied to determine efficient input and output vectors. The potential of the developed models was evaluated based on statistical indices and graphical representations. The results of the gamma test based on the least value of gamma and standard error indices show that days of anthesis (DOA), days of silking (DOS), yield index (YI), and gross yield per plant (GYP) information vector arrangements were determined to be an efficient information vector combination for the drought-tolerance index (DTI) as well as the stress-tolerance index (STI). The MLP, SVM, MLP-GA, and SVM-GA algorithms’ results were compared based on statistical indices and visual interpretations that have satisfactorily predict the drought-tolerance index and stress-tolerance index in maize crops. The genetic algorithm-based hybrid models (MLP-GA and SVM-GA) were found to better predict the drought-tolerance index and stress-tolerance index in maize crops. Similarly, the SVM-GA model was found to have the highest potential to forecast the DTI and STI in maize crops, compared to the MLP, SVM, and MLP-GA models.

Globally, chickpea production is severely affected by salinity stress. Understanding the genetic basis for salinity tolerance is important to develop salinity tolerant chickpeas. A recombinant inbred line (RIL) population developed using parental lines ICCV 10 (salt-tolerant) and DCP 92-3 (salt-sensitive) was screened under field conditions to collect information on agronomy, yield components, and stress tolerance indices. Genotyping data generated using Axiom®CicerSNP array was used to construct a linkage map comprising 1856 SNP markers spanning a distance of 1106.3 cM across eight chickpea chromosomes. Extensive analysis of the phenotyping and genotyping data identified 28 quantitative trait loci (QTLs) explaining up to 28.40% of the phenotypic variance in the population. We identified QTL clusters on CaLG03 and CaLG06, each harboring major QTLs for yield and yield component traits under salinity stress. The main-effect QTLs identified in these two clusters were associated with key genes such as calcium-dependent protein kinases, histidine kinases, cation proton antiporter, and WRKY and MYB transcription factors, which are known to impart salinity stress tolerance in crop plants. Molecular markers/genes associated with these major QTLs, after validation, will be useful to undertake marker-assisted breeding for developing better varieties with salinity tolerance.

BACKGROUND AND OBJECTIVES: The cultivation of soybeans in Indonesia frequently encounters challenges related to water saturation and drought, which ultimately leads to reduced productivity. The objective of this study was to determine how various soybean varieties react to waterlogging and drought in order to identify soybean cultivars that exhibit tolerance to both types of stressors. The study was conducted at the greenhouse of the Indonesian Legumes and Tuber Crops Research Institute, spanning from June to August 2022. A factorial randomized block design was employed, utilizing pots as the experimental units, with three replicates. The first factor is the availability of groundwater, namely optimal water available (field capacity), 40 percent of field capacity (drought stress), and water-saturated soil (waterlogging stress). The soybean variety is the second factor to consider, which includes Dering 1 (known for its drought tolerance), Dering 2 (also drought tolerant), Deja 1 (tolerant to water saturation), Deja 2 (also tolerant to water saturation), Devon 1 (noted for its high isoflavone content), and Dega 1 (specifically adapted for irrigated lowland conditions). The results showed that Dering 2 and Deja 2 varieties grown in soil moisture levels at 40 percent field capacity were capable of achieving similar growth outcomes in terms of plant height, shoot/root ratio, number of pods per plant, seed yield, and 100 seed weight compared to those grown in optimal soil moisture conditions. The stress tolerance index of the two varieties in the soil moisture at 40 percent of field capacity reached 1.03 and 0.83, respectively. The yields of Dering 2 and Deja 2 varieties at the optimal soil moisture reached 4.53 gram per plant and 6.28 gram per plant, and in soil moisture of 40 percent field capacity were 4.68 gram per plant and 5.69 gram per plant respectively. In flooded soil, the Dering 2 and Deja 1 varieties can develop the weight of 100 seeds, number of branches, and plant height as same as in optimal soil moisture, with relatively lower yield reduction compared to other varieties, with stress tolerance index values of 0.66 and 0.54. The Dering 2 and Deja 2 cultivars exhibit tolerance to drought stress levels of up to 40 percent of field capacity, whereas the Dering 2 and Deja 1 cultivars demonstrate tolerance to water-saturated soil. A noteworthy finding is the identification of soybean cultivars capable of thriving in both drought and waterlogged environments, exemplified by the Dering 2 variety. Originally bred to combat drought-related challenges, the Dering 2 cultivar has shown promising results in waterlogged soil conditions as well. Similarly, the Deja 2 variety, which was designed and released for water-saturated environments, was found in this study to be tolerant of drought conditions.

Drought is one of the major abiotic stress factors limiting crops production in Oltenia area, Romania. In order to study the response of six maize hybrids to drought stress, the trials were conducted in research field of ARDS Simnic – Craiova, during 2017-2018 (non-stressed conditions) and 2018-2019 (drought stress). Six tolerance indices including: abiotic tolerance index (ATI), stress susceptibility percentage index (SSPI), Stress tolerance index (STI), mean productivity (MP), relative drought index (RDI) and golden mean (GM), were utilized on the basis of grain yield. Results from analysis of variance showed that there is a significant difference in 1% of probability level among hybrids in terms of grain yield and tolerance indices. The yield in non-stress conditions (Yp) showed significant positive correlations with ATI, SSPI, STI and MP, and negative correlation with RDI and GM. The yield  in drought conditions (Ys) showed significant positive correlation with RDI and GM, and negative correlation with ATI and SSPI. None of the tolerance indices used could identify the high yielding hybrids under drought and non-stress conditions. Based on the ranking method, the hybrids ‘Felix’ and ‘P 9903’ were the most droughts tolerant. Therefore, they hybrids are recommended to be grown under drought prone areas and to be used as parents for breeding of drought tolerance in other cultivars.

Because soil salinity is a major abiotic constraint affecting crop yield, much research has been conducted to develop plants with improved salinity tolerance. Salinity stress impacts many aspects of a plant's physiology, making it difficult to study in toto Instead, it is more tractable to dissect the plant's response into traits that are hypothesized to be involved in the overall tolerance of the plant to salinity. We discuss how to quantify the impact of salinity on different traits, such as relative growth rate, water relations, transpiration, transpiration use efficiency, ionic relations, photosynthesis, senescence, yield and yield components. We also suggest some guidelines to assist with the selection of appropriate experimental systems, imposition of salinity stress, and obtaining and analysing relevant physiological data using appropriate indices. We illustrate how these indices can be used to identify relationships amongst the proposed traits to identify which traits are the most important contributors to salinity tolerance. Salinity tolerance is complex and involves many genes, but progress has been made in studying the mechanisms underlying a plant's response to salinity. Nevertheless, several previous studies on salinity tolerance could have benefited from improved experimental design. We hope that this paper will provide pertinent information to researchers on performing proficient assays and interpreting results from salinity tolerance experiments.

The present study explored the eco-friendly approach of utilizing plant-growth-promoting rhizobacteria (PGPR) inoculation and foliar application of silicon (Si) to improve the physiology, growth, and yield of mung bean under saline conditions. We isolated 18 promising PGPR from natural saline soil in Saudi Arabia, and screened them for plant-growth-promoting activities. Two effective strains were selected from the screening trial, and were identified as Enterobacter cloacae and Bacillus drentensis using matrix-assisted laser desorption ionization-time-of-flight mass spectrometry and 16S rRNA gene sequencing techniques, respectively. Subsequently, in a 2-year mung bean field trial, using a randomized complete block design with a split-split plot arrangement, we evaluated the two PGPR strains and two Si levels (1 and 2 kg ha(-1)), in comparison with control treatments, under three different saline irrigation conditions (3.12, 5.46, and 7.81 dS m(-1)). The results indicated that salt stress substantially reduced stomatal conductance, transpiration rate, relative water content (RWC), total chlorophyll content, chlorophyll a, chlorophyll b, carotenoid content, plant height, leaf area, dry biomass, seed yield, and salt tolerance index. The PGPR strains and Si levels independently improved all the aforementioned parameters. Furthermore, the combined application of the B. drentensis strain with 2 kg Si ha(-1) resulted in the greatest enhancement of mung bean physiology, growth, and yield. Overall, the results of this study provide important information for the benefit of the agricultural industry.

Drought is one of the most prevailing abiotic stresses affecting the growth, development, and productivity of maize. Knowledge of drought tolerance could help in maize improvement. However, less research has been done to comprehensively evaluate the drought tolerance of maize inbred lines. We used 27 elite maize inbred lines selected from Shaan A group and Shaan B group breeding populations to estimate their drought tolerance in 3 years 2 locations under normal field conditions and low irrigation. Using principal component analysis (PCA) and GGE biplots, all inbred lines, including the controls, could be divided into four types. Ten lines could be categorized as the high-yield drought-resistant type (‘KB081’, ‘KA105’, ‘KB417’, ‘KB215’, ‘KB-7’, ‘2013KB-37’, ‘KA203’, ‘2012KA-34’, ‘KA225’, and ‘91227’) because of their stability and wide adaptability. Compared with the controls, a large proportion of the inbred lines selected from Shaan A and Shaan B breeding populations demonstrated higher drought resistance. Our results suggest that multi-year drought screening can be used as a tool to improve the drought resistance of maize inbred lines and provide a scientific basis for making better use of the Shaan A and Shaan B maize inbred lines to breed new varieties and to identify existing drought-resistant maize varieties.