Identification of drought tolerant Chickpea genotypes through multi trait stability index

Unraveling the genetics of heat tolerance in chickpea landraces (Cicer arietinum L.) using genome-wide association studies

Chickpea, being an important grain legume crop, is often confronted with the adverse effects of high temperatures at the reproductive stage of crop growth, drastically affecting yield and overall productivity. The current study deals with an extensive evaluation of chickpea genotypes, focusing on the traits associated with yield and their response to heat stress. Notably, we observed significant variations for these traits under both normal and high-temperature conditions, forming a robust basis for genetic research and breeding initiatives. Furthermore, the study revealed that yield-related traits exhibited high heritability, suggesting their potential suitability for marker-assisted selection. We carried out single-nucleotide polymorphism (SNP) genotyping using the genotyping-by-sequencing (GBS) method for a genome-wide association study (GWAS). Overall, 27 marker-trait associations (MTAs) linked to yield-related traits, among which we identified five common MTAs displaying pleiotropic effects after applying a stringent Bonferroni-corrected p-value threshold of <0.05 [-log10(p) > 4.95] using the BLINK (Bayesian-information and linkage-disequilibrium iteratively nested keyway) model. Through an in-depth in silico analysis of these markers against the CDC Frontier v1 reference genome, we discovered that the majority of the SNPs were located at or in proximity to gene-coding regions. We further explored candidate genes situated near these MTAs, shedding light on the molecular mechanisms governing heat stress tolerance and yield enhancement in chickpeas such as indole-3-acetic acid-amido synthetase GH3.1 with GH3 auxin-responsive promoter and pentatricopeptide repeat-containing protein, etc. The harvest index (HI) trait was associated with marker Ca3:37444451 encoding aspartic proteinase ortholog sequence of Oryza sativa subsp. japonica and Medicago truncatula, which is known for contributing to heat stress tolerance. These identified MTAs and associated candidate genes may serve as valuable assets for breeding programs dedicated to tailoring chickpea varieties resilient to heat stress and climate change.

Exploring Genetics by Environment Interactions in Some Rice Genotypes across Varied Environmental Conditions

Rice production faces challenges related to diverse climate change processes. Heat stress combined with low humidity, water scarcity, and salinity are the foremost threats in its cultivation. The present investigation aimed at identifying the most resilient rice genotypes with yield stability to cope with the current waves of climate change. A total of 34 rice genotypes were exposed to multilocation trials. These locations had different environmental conditions, mainly normal, heat stress with low humidity, and salinity-affected soils. The genotypes were assessed for their yield stability under these conditions. The newly developed metan package of R-studio was employed to perform additive main effects and multiplicative interactions modelling and genotype-by-environment modelling. The results indicated that there were highly significant differences among the tested genotypes and environments. The main effects of the environments accounted for the largest portion of the total yield sum of squared deviations, while different sets of genotypes showed good performance in different environments. AMMI1 and GGE biplots confirmed that Giza179 was the highest-yielding genotype, whereas Giza178 was considered the most-adopted and highest-yielding genotype across environments. These findings were further confirmed by the which-won-where analysis, which explained that Giza178 has the greatest adaptability to the different climatic conditions under study. While Giza179 was the best under normal environments, N22 recorded the uppermost values under heat stress coupled with low humidity, and GZ1968-S-5-4 manifested superior performance regarding salinity-affected soils. Giza 177 was implicated regarding harsh environments. The mean vs. stability-based rankings indicated that the highest-ranked genotypes were Giza179 > Giza178 > IET1444 > IR65600-77 > GZ1968-S-5-4 > N22 > IR11L236 > IR12G3213. Among them, Giza178, IR65600-77, and IR12G3213 were the most stable genotypes. Furthermore, these results were confirmed by cluster-analysis-based stability indices. A significant and positive correlation was detected between the overall yield under all the environments with panicle length, number of panicles per plant, and thousand grain weight. Our study sheds light on the notion that the Indica/Japonica and Indica types have greater stability potential over the Japonica ones, as well as the potential utilization of genotypes with wide adaptability, stability, and high yield, such as Giza178, in the breeding programs for climate change resilience in rice.

Identification of High-Yielding Genotypes of Barley in the Warm Regions of Iran

One of the most important effects of climatic changes is increasing temperatures and expanding water deficit stress in tropical and subtropical regions. As the fourth most important cereal crop, barley (Hordeum vulgare L.) is crucial for food and feed security, as well as for a sustainable agricultural system. The present study investigates 56 promising barley genotypes, along with four local varieties (Norooz, Oxin, Golchin, and Negin) in four locations to identify high-yielding and adapted genotypes in the warm climate of Iran. Genotypes were tested in an alpha lattice design with six blocks, which were repeated three times. Traits measured were the number of days to heading and maturity, plant height, thousand kernels weight, and grain yield. A combined analysis of variance showed the significant effects of genotypes (G), environments (E), and their interaction (GEI) on all measured traits. Application of the additive main-effect and multiplicative interaction (AMMI) model to the grain yield data showed that GEI was divided into three significant components (IPCAs), and each accounted for 50.93%, 30.60%, and 18.47%, respectively. Two selection indices [Smith-Hazel (SH) and multiple trait selection index (MTSI)] identified G18, G24, G29, and G57 as desirable genotypes at the four test locations. Using several BLUP-based indices, such as the harmonic mean of genotypic values (HMGV), the relative performance of genotypic values (RPGV), and the harmonic mean of the relative performance of genotypic values (HMRPGV), genotypes G6, G11, G22, G24, G29, G38, G52, and G57 were identified as superior genotypes. The application of GGE analysis identified G6, G24, G29, G52, and G57 as the high-yielding and most stable genotypes. Considering all statistical models, genotypes G24, G29, and G57 can be used, as they are well-adapted to the test locations in warm regions of Iran.

Genotype × environment interaction and stability analysis for seed yield and yield components in sesame (Sesamum indicum L.) in Benin Republic using AMMI, GGE biplot and MTSI

Increasing production requires the development of high yielding cultivars adapted to various environments. Multi-environment trials (MET) remains the best approach to assess the performance of accessions across environments. The objective of this study was to select the best performing and stable accessions of sesame across different environments in Benin Republic. Nineteen sesame accessions were evaluated across eight environments using a randomized complete block design with four replicates. The accessions were evaluated for three traits: days to 50% flowering (D50F), thousand-seed weight (TSW), and seed yield (SY) during 2020 growing season. The stable and top-performing accessions across environments were determined using AMMI (Additive main effects and multiplicative interaction), GGE (Genotype main effect and genotype × environment interaction), and MTSI (Multi-trait stability index). AMMI analysis of variance showed a significant difference across environments for the three traits. The accessions were affected by environmental conditions for the three traits. The broad-sense heritability estimates were high (>0.60) for all the traits, indicating the improvement is achievable through selection. AMMI1 and AMMI2 biplots identified G10 and G13 as high seed yielding accessions adapted to environments E1, E2. The GGE biplot showed two mega-environments for TSW and three mega-environments for D50F and SY. For SY, G11 and G13 were the best accessions in the first mega-environment, G10 the best accession in the second mega-environment; G3 and G8 were the best accessions in the third mega-environment. AMMI and GGE analyses identified G10, G5, G12 as high seed yielding and stable accessions across environments. GGE biplot revealed that E1 and E2 were the most suitable environments for multi-location trials based on their discriminating ability and representativeness. MTSI indicated G10, G13, G19 as promising germplasm to be recommended for breeding program.

NK, Pavani S. L, Ganesan S, Singh PK, Sah RP, V. P, Subudhi H, Mahender A, Anandan A, Ali J. Multi-environment evaluation of rice genotypes: impact of weather and culm biochemical parameters against sheath blight infection

Introduction

Sheath blight caused by Rhizoctonia solani is one of the major diseases of rice, causing widespread crop losses. The use of semi-dwarf rice varieties in the ongoing nutrient-intensive rice cultivation system has further accentuated the incidence of the disease. An ideal solution to this problem would be identifying a stable sheath blight-tolerant genotype.

Material and methods

A multi-environment evaluation of 32 rice genotypes against sheath blight infection was conducted over six seasons across two locations (Agricultural Research Farm, Institute of Agricultural Sciences, Banaras Hindu University (28.18° N, 38.03° E, and 75.5 masl), for four years during the wet seasons (kharif) from 2015 to 2018 and two seasons at the National Rice Research Institute (20°27'09" N, 85°55'57" E, 26 masl), Cuttack, Odisha, during the dry season (rabi) of 2019 and the kharif of 2019, including susceptible and resistant check. Percent disease index data were collected over 4 weeks (on the 7th, 14th, 21st, and 28th day after infection), along with data on other morphological and physiological traits.

Result and discussion

The resistant genotypes across seasons were the ones with a higher hemicellulose content (13.93-14.64) and lower nitrogen content (1.10- 1.31) compared with the susceptible check Tapaswini (G32) (hemicellulose 12.96, nitrogen 1.38), which might explain the resistant reaction. Three different stability models-additive main effect and multiplicative interaction (AMMI), genotype + genotype x environment (GGE) biplot, and multi-trait stability index (MTSI)-were then used to identify the stable resistant genotypes across six seasons. The results obtained with all three models had common genotypes highlighted as stable and having a low area under the disease progress curve (AUDPC) values. The ideal stable genotypes with low disease incidence were IC 283139 (G19), Tetep (G28), IC 260917 (G4), and IC 277274 (G10), with AUDPC values of 658.91, 607.46, 479.69, and 547.94, respectively. Weather parameters such as temperature, rainfall, sunshine hours, and relative humidity were also noted daily. Relative humidity was positively correlated with the percent disease index.

Capturing agro-morphological variability for tolerance to terminal heat and combined heat-drought stress in landraces and elite cultivar collection of wheat

Climate change has resulted in extreme temperature and drought around the globe, which poses serious threat to food security. Both heat and drought stress affects the production and productivity of wheat crop. The present study was undertaken to evaluate 34 landraces and elite cultivars of Triticum spp. for phenological and yield-related traits under optimum, heat, and combined heat-drought stress environments during 2020-2021 and 2021-2022. The pooled analysis of variance showed significant genotype × environment interaction, suggesting an influence of stress on trait expression. The trait performance of genotypes exhibited significant reduction under combined heat-drought stress as compared to optimum and heat stress environments. The maximum seed yield penalty was observed under combined heat-drought stress environment as compared to heat stress alone. Regression analysis indicated significant contribution of number of grains per spike towards stress tolerance. Based on Stress Tolerance Index (STI), genotypes Local-17, PDW 274, HI-8802, and HI-8713 were identified to be tolerant to both heat and combined heat and drought stress at Banda, whereas genotypes DBW 187, HI-8777, Raj 4120, and PDW 274 were tolerant at Jhansi location. The genotype PDW 274 showed stress tolerance under all treatments at both the locations. The genotypes PDW 233 and PDW 291 showed highest stress susceptibility index (SSI) across the environments. The number of grains per spike and test kernel weight were positively associated with seed yield across the environments and locations. The selected genotypes Local-17, HI 8802, and PDW 274 were identified to be the potential sources of heat and combined heat-drought tolerance, which may be utilized in hybridization to develop tolerant wheat genotypes and also for mapping of underlying genes/quantitative trait loci (QTLs).

Multi-trait selection for mean performance and stability of maize hybrids in mega-environments delineated using envirotyping techniques

Under global climate changes, understanding climate variables that are most associated with environmental kinships can contribute to improving the success of hybrid selection, mainly in environments with high climate variations. The main goal of this study is to integrate envirotyping techniques and multi-trait selection for mean performance and the stability of maize genotypes growing in the Huanghuaihai plain in China. A panel of 26 maize hybrids growing in 10 locations in two crop seasons was evaluated for 9 traits. Considering 20 years of climate information and 19 environmental covariables, we identified four mega-environments (ME) in the Huanghuaihai plain which grouped locations that share similar long-term weather patterns. All the studied traits were significantly affected by the genotype × mega-environment × year interaction, suggesting that evaluating maize stability using single-year, multi-environment trials may provide misleading recommendations. Counterintuitively, the highest yields were not observed in the locations with higher accumulated rainfall, leading to the hypothesis that lower vapor pressure deficit, minimum temperatures, and high relative humidity are climate variables that -under no water restriction- reduce plant transpiration and consequently the yield. Utilizing the multi-trait mean performance and stability index (MTMPS) prominent hybrids with satisfactory mean performance and stability across cultivation years were identified. G23 and G25 were selected within three out of the four mega-environments, being considered the most stable and widely adapted hybrids from the panel. The G5 showed satisfactory yield and stability across contrasting years in the drier, warmer, and with higher vapor pressure deficit mega-environment, which included locations in the Hubei province. Overall, this study opens the door to a more systematic and dynamic characterization of the environment to better understand the genotype-by-environment interaction in multi-environment trials.

Molecular Breeding and Drought Tolerance in Chickpea

Cicer arietinum L. is the third greatest widely planted imperative pulse crop worldwide, and it belongs to the Leguminosae family. Drought is the utmost common abiotic factor on plants, distressing their water status and limiting their growth and development. Chickpea genotypes have the natural ability to fight drought stress using certain strategies viz., escape, avoidance and tolerance. Assorted breeding methods, including hybridization, mutation, and marker-aided breeding, genome sequencing along with omics approaches, could be used to improve the chickpea germplasm lines(s) against drought stress. Root features, for instance depth and root biomass, have been recognized as the greatest beneficial morphological factors for managing terminal drought tolerance in the chickpea. Marker-aided selection, for example, is a genomics-assisted breeding (GAB) strategy that can considerably increase crop breeding accuracy and competence. These breeding technologies, notably marker-assisted breeding, omics, and plant physiology knowledge, underlined the importance of chickpea breeding and can be used in future crop improvement programmes to generate drought-tolerant cultivars(s).