Water scarcity throughout wheat-growing periods is a major issue in India, therefore breeding methods, as well as the efficient selection approaches for moisture stress conditions are required to retain the level of crop production. In the current study recombinant inbred lines were developed through a donor, WH 730 crossed with recipient MACS 2496. Further segregating generations were advanced through the single seed descent method at Karnal. The F 7 and F 8 generations of 231 recombinant inbred lines along with five checks were planted in Alpha Lattice design for screening under normal and restricted irrigated conditions. A significant yield reduction was observed under restricted irrigated conditions than the normal irrigated condition during cropping season 2019-20 & 2020-21. Under stress condition significant association was found among yield and selection indices viz., stress susceptibility index (SSI), tolerance index (TOL), mean productivity (MP), stress tolerance index (STI), yield index (YI), drought resistance index (DI), sensitivity drought index (SDI), relative drought index (RDI), yield stability index (YSI) and percentage of yield reduction (PR). Based on selection indices, 22 superior recombinant lines were identified. These selected recombinant inbred lines may be subjected to further evaluation and also incorporated as donor parents in future hybridization programs.

The current experiments were carried out in alpha lattice design at the Seed Breeding Farm, Department of Plant Breeding and Genetics, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, Madhya Pradesh state, India, during 2019−20 and 2020−21 crop seasons, using 236 RILs population. The aim of current experiment is to assessment of genetic diversity and identification of promising recombinant inbred lines for irrigated and restricted irrigated conditions through PCA and cluster analysis. The drought selection indices viz. Relative drought index, yield stability index, drought resistance index, mean productivity, stress tolerance index and yield index were performed from two year grain yield pooled data. The principal component analysis and cluster analysis were performed through drought selection indices. Drought selection indices viz. relative drought index, yield stability index, yield index were confirm strong positively associated with grain yield under restricted irrigated conditions while mean productivity, stress tolerance index and yield index were strong positively associated with grain yield under irrigated conditions. Moreover, high cluster mean, for grain yield under restricted irrigated condition with associated selection indices was confirmed by 77 inbred lines from cluster I. similarly 128 superior inbred lines were found for irrigated condition. The highest inter cluster distance was observed between cluster I and cluster III therefore the inbred line occupy by cluster I and cluster III were considered as most diverse lines and could be used in farther breeding program to achieve more recombination for drought tolerance.

The purpose of this study was to ascertain the genotype by environment interaction (GEI) of heat tolerance wheat genotypes. The objective was to inspect the stable wheat genotype for timely and late sown planting condition in central zone of India. For that total of 20 wheat genotypes, including two parents and three commercial checks, were tested across 6 (timely sown) + 4 (late sown) environments at Jabalpur, Narmadapuram, and Sagar district of Madhya Pradesh state of India in 2019-20 and 2021-21. The per plant yield and grain filling rate data were considered to perform univariate and multivariate stability analysis. Our result revealed that environment, genotype, and GEI effects were significant (P < 0.001) across all the environments and individual environmental conditions. The greater performing along with high stability for grain yield JW3288, L8 and L13 while for grain filling rate L11, L13 and L11 genotypes were identified in timely sown, late sown and across all the environments, respectively. In order to find stable and high-performing genotypes, the GEI accompanied by several models but AMMI and GGE models were further effective and accurate than the linear regression model. In conclusion according to univariate and multivariate stability analysis L13 was the utmost genotype across all the environments therefore, it might be used in future breeding programs although, Jabalpur was recognized as the most discriminating and representative environments across all the environments.

Beachpea (Vigna marina) is a halophytic wild leguminous plant which occurs throughout tropical and subtropical beaches of world. As quantitative trait loci (QTLs) for salt tolerance in V. marina and its crossability with other Vigna species are known, the current study was undertaken to know the presence of these QTLs in the V. marina accessions along with check varieties of pulses. Accordingly, 20 Vigna genotypes (15 accessions of V. marina collected from sea-shore areas of Andaman and Nicobar Islands along with five check varieties of green gram and black gram) were subjected to molecular characterization using seven simple sequence repeat (SSR) markers associated with salt tolerance. Of the markers used, only four SSR markers amplified in the studied germplasm. Number of alleles detected per primer and size of alleles ranged from 1 to 3 and 100 to 325 bp, respectively. Polymorphism information content and heterozygosity values ranged from 0.305 to 0.537 and 0.375 to 0.612, respectively. Three major clusters, cluster I, II and III were obtained at Jaccard's similarity coefficient value of 0.48 through the un-weighted paired group method with arithmetic means method of cluster analysis. It grouped green gram and black gram genotypes in clusters I (04) and II (01), whereas all V. marina genotypes were grouped in cluster III (15). Principal co-ordinate analysis explained 85.9% of genetic variation among genotypes which was further confirmed by cluster analysis. This study indicated the effectiveness of SSR markers in separating cultivated Vigna species from wild V. marina. The findings will be useful for transferring trait of robust salt tolerance of V. marina in cultivated Vigna species using marker-assisted breeding.

Due to the advancement of electronics engineering technology, many types of sensors have been developed. But sensors are still battery-powered devices. Once the battery is dead, the sensors are of no use. So, energy optimization in wireless sensor networks is still a hot topic among researchers. This paper proposed a novel clustering method that uses the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm to select the Cluster Heads (CHs). TOPSIS is a Multi-Attribute Decision Making (MADM) based model which uses several conflicting attributes to select the best alternative. We have compared our proposed model with two other comparable models to evaluate the performance of our proposed model. The result shows that our proposed model performs better than other models.