Low productivity of pilosae type lentils grown in South Asia is attributed to narrow genetic base of the released cultivars which results in susceptibility to biotic and abiotic stresses. For enhancement of productivity and production, broadening of genetic base is essentially required. The genetic base of released cultivars can be broadened by using diverse types including bold seeded and early maturing lentils from Mediterranean region and related wild species. Genetic diversity in eighty six accessions of three species of genus Lens was assessed based on twelve genomic and thirty one EST-SSR markers. The evaluated set of genotypes included diverse lentil varieties and advanced breeding lines from Indian programme, two early maturing ICARDA lines and five related wild subspecies/species endemic to the Mediterranean region. Genomic SSRs exhibited higher polymorphism in comparison to EST SSRs. GLLC 598 produced 5 alleles with highest gene diversity value of 0.80. Among the studied subspecies/species 43 SSRs detected maximum number of alleles in L. orientalis. Based on Nei’s genetic distance cultivated lentil L. culinaris subsp. culinaris was found to be close to its wild progenitor L. culinaris subsp. orientalis. The Prichard’s structure of 86 genotypes distinguished different subspecies/species. Higher variability was recorded among individuals within population than among populations.

Mungbean (Vigna radiataL.) is an important food grain legume, but its production capacity is threatened by global warming, which can intensify plant stress and limit future production. Identifying new variation of key root traits in mungbean will provide the basis for breeding lines with effective root characteristics for improved water uptake to mitigate heat and drought stress. The AVRDC mungbean mini core collection consisting of 296 genotypes was screened under modified semi-hydroponic screening conditions to determine the variation for fourteen root-related traits. The AVRDC mungbean mini core collection displayed wide variations for the primary root length, total surface area, and total root length, and based on agglomerative hierarchical clustering eight homogeneous groups displaying different root traits could be identified. Germplasm with potentially favorable root traits has been identified for further studies to identify the donor genotypes for breeding cultivars with enhanced adaptation to water-deficit stress and other stress conditions.

Chickpea (Cicer arietinum L.) is known to be sensitive to many herbicides and, therefore, choices for using post-emergence herbicides for weed control are limited. The present study was aimed at identifying sources of tolerance to two herbicides with different modes of action (imazethapyr—amino acid synthesis inhibitor; and metribuzin—photosynthesis inhibitor) for use in breeding herbicide tolerant cultivars. Screening of 300 diverse chickpea genotypes (278 accessions from the reference set and 22 breeding lines) revealed large genetic variations for tolerance to herbicides imazethapyr and metribuzin. In general, the sensitivity of the genotypes to metribuzin was higher compared to that for imazethapyr. Several genotypes tolerant to metribuzin (ICC 1205, ICC 1164, ICC 1161, ICC 8195, ICC 11498, ICC 9586, ICC 14402 ICC 283) and imazethapyr (ICC 3239, ICC 7867, ICC 1710, ICC 13441, ICC 13461, ICC 13357, ICC 7668, ICC 13187) were identified, based on average herbicide tolerance scores from two experimental locations each. The herbicide tolerant lines identified in this study will be useful resources for development of herbicide tolerant cultivars and for undertaking genetic and physiological studies on herbicide tolerance in chickpea.

Legumes are a better source of proteins and are richer in diverse micronutrients over the nutritional profile of widely consumed cereals. However, when exposed to a diverse range of abiotic stresses, their overall productivity and quality are hugely impacted. Our limited understanding of genetic determinants and novel variants associated with the abiotic stress response in food legume crops restricts its amelioration. Therefore, it is imperative to understand different molecular approaches in food legume crops that can be utilized in crop improvement programs to minimize the economic loss. ‘Omics’-based molecular breeding provides better opportunities over conventional breeding for diversifying the natural germplasm together with improving yield and quality parameters. Due to molecular advancements, the technique is now equipped with novel ‘omics’ approaches such as ionomics, epigenomics, fluxomics, RNomics, glycomics, glycoproteomics, phosphoproteomics, lipidomics, regulomics, and secretomics. Pan-omics—which utilizes the molecular bases of the stress response to identify genes (genomics), mRNAs (transcriptomics), proteins (proteomics), and biomolecules (metabolomics) associated with stress regulation—has been widely used for abiotic stress amelioration in food legume crops. Integration of pan-omics with novel omics approaches will fast-track legume breeding programs. Moreover, artificial intelligence (AI)-based algorithms can be utilized for simulating crop yield under changing environments, which can help in predicting the genetic gain beforehand. Application of machine learning (ML) in quantitative trait loci (QTL) mining will further help in determining the genetic determinants of abiotic stress tolerance in pulses.

Mungbean is an important food grain legume for human nutrition and nutritional food due to its nutrient-dense seed, liked palatability, and high digestibility. However, anti-nutritional factors pose a significant risk to improving nutritional quality for bio-fortification. In the present study, genetic architecture of grain micronutrients (grain iron and zinc concentration) and anti-nutritional factors (grain phytic acid and tannin content) in association mapping panel of 145 diverse mungbean were evaluated. Based on all four parameters genotypes PUSA 1333 and IPM 02-19 were observed as desired genotypes as they had high grain iron and zinc concentration but low grain phytic acid and tannin content. The next generation sequencing (NGS)-based genotyping by sequencing (GBS) identified 14,447 genome-wide SNPs in a diverse selected panel of 127 mungbean genotypes. Population admixture analysis revealed the presence of four different ancestries among the genotypes and LD decay of ∼57.6 kb kb physical distance was noted in mungbean chromosomes. Association mapping analysis revealed that a total of 20 significant SNPs were shared by both GLM and Blink models associated with grain micronutrient and anti-nutritional factor traits, with Blink model identifying 35 putative SNPs. Further, this study identified the 185 putative candidate genes. Including potential candidate genes Vradi07g30190, Vradi01g09630, and Vradi09g05450 were found to be associated with grain iron concentration, Vradi10g04830 with grain zinc concentration, Vradi08g09870 and Vradi01g11110 with grain phytic acid content and Vradi04g11580 and Vradi06g15090 with grain tannin content. Moreover, two genes Vradi07g15310 and Vradi09g05480 showed significant variation in protein structure between native and mutated versions. The identified SNPs and candidate genes are potential powerful tools to provide the essential information for genetic studies and marker-assisted breeding program for nutritional improvement in mungbean.

Lentil is a major cool-season grain legume grown in South Asia, West Asia, and North Africa. Populations in developing countries of these regions have micronutrient deficiencies; therefore, breeding programs should focus more on improving the micronutrient content of food. In the present study, a set of 96 diverse germplasm lines were evaluated at three different locations in India to examine the variation in iron (Fe) and zinc (Zn) concentration and identify simple sequence repeat (SSR) markers that associate with the genetic variation. The genetic variation among genotypes of the association mapping (AM) panel was characterized using a genetic distance-based and a general model-based clustering method. The model-based analysis identified six subpopulations, which satisfactorily explained the genetic structure of the AM panel. AM analysis identified three SSRs (PBALC 13, PBALC 206, and GLLC 563) associated with grain Fe concentration explaining 9% to 11% of phenotypic variation and four SSRs (PBALC 353, SSR 317–1, PLC 62, and PBALC 217) were associated with grain Zn concentration explaining 14%, to 21% of phenotypic variation. These identified SSRs exhibited consistent performance across locations. These candidate SSRs can be used in marker-assisted genetic improvement for developing Fe and Zn fortified lentil varieties. Favorable alleles and promising genotypes identified in this study can be utilized for lentil biofortification.