An experiment was conducted with a set twenty-five genotypes of desi and Kabuli chickpeas to estimate stability parameters in Randomized Block Design with two replications under four environments (1st November 2018 (normal), 21st November 2018 (optimum), 15th December 2018 (late) and 15th January 2019 (extremely late) conditions during Rabi-2018-19. The analysis of variance showed a significant connection among genotypes, environment (linear), and genotype environment (linear) in all the traits in investigation. The JG-11, JAKI-9218, RVG-201 and RVSSG-54 these genotypes suitable for high seed yield with late and very-late sown conditions.

Twenty eight diverse genotypes sown in three different dates were screened using thirty three SSR primers. Twelve morphological characters recorded. The current study was conducted at all India Coordinated Research Project on Chickpea at R.A.K., College of Agriculture, Sehore (M.P.) during Rabi 2020-21, and 2021-22. The molecular work was carried out at Plant Molecular Biology Laboratory, Department of Plant Molecular Biology and Biotechnology, College of Agriculture, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior (M.P.). The component G×E interaction were found significant for flower initiation, days to 50% flowering, days to pod initiation, plant height, days to maturity, number of pods per plant, number of empty pods per plant, number of seeds per plant, biological yield per plant, harvest index, 100 seed weight and seed yield per plant. The highest gene diversity was found in TA-135 (0.7474) followed by GAA-44 (0.7219), GAA-40 (0.7015), STMS-2 (0.6939), TA-71 (0.6709), NCPGR-1 (0.6403) and TA-18 (0.3648). Based on a dendrogram all the 28 genotypes were grouped into three major clusters, in which cluster I contained 2 genotypes, cluster II contained 5 genotypes and cluster III encompassed remaining 21 genotypes. Genotypes RVG 204, JG-14, and RVSSG-61 were found stable for favourable and unfavourable sowing conditions, while ICC-4958, JG-11, JG-12, RVG-203, RVG-204, RVSSG-52, JG-74, RVSSG-71 showed consistent performance during unfavourable sowing conditions for seed yield per plant. The important traits and marker based diversity and stability has been discussed in this research paper.

A field experiment was conducted during Rabi, 2019-20 at Sehore, Madhya Pradesh to investigate the association of yield and its related components of physiological traits in Chickpea under three sown environments. Seed yield per plant was showed significant positive association with LA & LAI at 60 days after sowing in E-I, CGR in E-III. This suggested that attributes might be utilized primarily for selection of high yielding genotypes, with yield contributing characters potentially playing a key role as selection parameters for isolating a high yield in eligible genotypes.

The primary goal of every plant breeder is to identify gene alleles and then use them in crop improvement programmes. If there is no population variation, there cannot be a breeding programme. Breeders need a lot of labour and money to screen germplasm for a desired gene. Additionally, these screenings are compliant with environmental effects. The method of "allele mining" is employed to identify suitable alleles of a candidate gene affecting important agronomic properties or naturally occurring allelic variations. TILLING and Eco-TILLING are the ideal solutions to this issue for allele mining. A technique known as "tilling" uses mutagens to introduce new diversity in a specific allele. Then, different sequencers are used to screen the diversity in a gene to identify different mutations. The best mutant among them can then be directly used in breeding programmes. In a modified version, alleles of a gene that are present in the population are identified by screening natural populations. Eco-TILLING is the name of this fresh iteration of the technology. The generation of novel haplotypes, the use of molecular markers to characterize genetic diversity and the syntenic links across crop genotypes, as well as marker-assisted selection are just a few of the many applications of allele mining in agriculture and crop improvement. Many genes may be found and used in the breeding of many crop species using these reverse genetics techniques.Allele mining