Molecular characterization and genetic diversity among 82 soybean accessions was carried out by using 44 simple sequence repeat (SSR) markers. Of the 44 SSR markers used, 40 markers were found polymorphic among 82 soybean accessions. These 40 polymorphic markers produced a total of 119 alleles, of which five were unique alleles and four alleles were rare. The allele number for each SSR locus varied between two to four with an average of 2.97 alleles per marker. Polymorphic information content values of SSRs ranged from 0.101 to 0.742 with an average of 0.477. Jaccard's similarity coefficient was employed to study the molecular diversity of 82 soybean accessions. The pairwise genetic similarity among 82 soybean accessions varied from 0.28 to 0.90. The dendrogram constructed based on genetic similarities among 82 soybean accessions identified three major clusters. The majority of genotypes including four improved cultivars were grouped in a single subcluster IIIa of cluster III, indicating high genetic resemblance among soybean germplasm collection in India.

Soybean is a leading oilseed crop in India, which contains about 40% of protein and 20% of oil. Core collection will accelerate the management and utilization of soybean genetic resources in breeding programmes. In the present study, eight agromorphological traits of 3443 soybean germplasm were analysed for the development of core collection using the principal component score (PCS) strategy and the power core method. The PCS strategy yielded core collection (CC1) of 576 accessions, which accounted for 16.72% of the entire collection (EC). The analysis based on the power core programme resulted in CC2 of 402 accessions, which accounted for 11.67% of the EC. Statistical analysis showed similar trends for the mean and range estimated in both core collections and EC. In addition, the variance, standard deviation and coefficient of variance were in general higher in core collections than in the EC. The correlations observed in the EC in general were preserved in core collections. A total of 311 and 137 unique accessions were found in CC1 and CC2 in addition to 265 accessions that were found to be common in both core collections. These 265 common accessions were the most diverse core sets, which accounted for 7.64% of the EC. We proposed to constitute an integrated core collection (ICC) by integrating both common and unique accessions. The ICC comprised 713 accessions, which accounted for about 20.62% of the EC. Statistical analysis indicated that the ICC captured maximum variation than CC1 and CC2. Therefore, the ICC can be extensively evaluated for a large number of economically important traits for the identification of desirable genotypes and for the development of mini core collection in soybean.

Salinization of soils and freshwater resources by natural processes and/or human activities has become an increasing issue that affects environmental services and socioeconomic relations. In addition, salinization jeopardizes agroecosystems, inducing salt stress in most cultivated plants (nutrient deficiency, pH and oxidative stress, biomass reduction), and directly affects the quality and quantity of food production. Depending on the type of salt/stress (alkaline or pH-neutral), specific approaches and solutions should be applied to ameliorate the situation on-site. Various agro-hydrotechnical (soil and water conservation, reduced tillage, mulching, rainwater harvesting, irrigation and drainage, control of seawater intrusion), biological (agroforestry, multi-cropping, cultivation of salt-resistant species, bacterial inoculation, promotion of mycorrhiza, grafting with salt-resistant rootstocks), chemical (application of organic and mineral amendments, phytohormones), bio-ecological (breeding, desalination, application of nano-based products, seed biopriming), and/or institutional solutions (salinity monitoring, integrated national and regional strategies) are very effective against salinity/salt stress and numerous other constraints. Advances in computer science (artificial intelligence, machine learning) provide rapid predictions of salinization processes from the field to the global scale, under numerous scenarios, including climate change. Thus, these results represent a comprehensive outcome and tool for a multidisciplinary approach to protect and control salinization, minimizing damages caused by salt stress.

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The bread wheat line WR95 showed seed-