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Failure of the rice crop, or low rice yield has dire consequences for rice-dependent households, including food insecurity and malnutrition, for India’s poorest farmers in the East Indian Plateau region. Crop diversification could reduce the risks of rice production from the vagaries of rainfall and provide cash income which is not generated from subsistence rice. Being the primary household laborers women bear the brunt of these difficult conditions in patriarchal societies. For this reason we engaged with the women farmers in Bokaro and West Singhbhum in the State of Jharkhand, and Purulia in West Bengal who participated in experiments conducted with vegetable crops and legumes in the upland and medium uplands where the traditional crop is broadcasted paddy rice. We explored four different vegetable systems, (i) cucurbits (rainy/kharif) (season—June to September), (ii) growing tomatoes in the “off season” (rainy season—July to October), (iii) growing legume crops in rotation with direct sown rice (dry/rabi season—November to January), and (iv) intercropping beans with maize (rainy season—June to September). The results showed that all the above crops proved much better in terms of income to the farmers, return per person day, although the input cost varied it was higher with the new systems explored. The research with the small-holding women farmers enabled them to try new options and make informed decisions about these opportunities. This study showed that farmers can increase crop diversity and expand the area sown to non-paddy crops. The farmers are now looking for new crops where the demand exceeds the supply. Importantly this study has demonstrated that the direct involvement of communities’ in research enables the farmers to sustainability explore solutions to the future problems with limited support from the external agencies.

Due to evolutionary divergence, sorghum race populations exhibit significant genetic and morphological variation. A k-mer-based sorghum race sequence comparison identified the conserved k-mers of all 272 accessions from sorghum and the race-specific genetic signatures identified the gene variability in 10,321 genes (PAVs). To understand sorghum race structure, diversity and domestication, a deep learning-based variant calling approach was employed in a set of genotypic data derived from a diverse panel of 272 sorghum accessions. The data resulted in 1.7 million high-quality genome-wide SNPs and identified selective signature (both positive and negative) regions through a genome-wide scan with different (iHS and XP-EHH) statistical methods. We discovered 2,370 genes associated with selection signatures including 179 selective sweep regions distributed over 10 chromosomes. Co-localization of these regions undergoing selective pressure with previously reported QTLs and genes revealed that the signatures of selection could be related to the domestication of important agronomic traits such as biomass and plant height. The developed k-mer signatures will be useful in the future to identify the sorghum race and for trait and SNP markers for assisting in plant breeding programs.

Pearl millet is a crucial nutrient-rich staple food in Asia and Africa and adapted to the climate of semi-arid topics. Since the genomic resources in pearl millet are very limited, we have developed a brand-new mid-density 4K SNP panel and demonstrated its utility in genetic studies. A set of 4K SNPs were mined from 925 whole-genome sequences through a comprehensive in-silico pipeline. Three hundred and seventy-three genetically diverse pearl millet inbreds were genotyped using the newly-developed 4K SNPs through the AgriSeq Targeted Genotyping by Sequencing technology. The 4K SNPs were uniformly distributed across the pearl millet genome and showed considerable polymorphism information content (0.23), genetic diversity (0.29), expected heterozygosity (0.29), and observed heterozygosity (0.03). The SNP panel successfully differentiated the accessions into two major groups, namely B and R lines, through genetic diversity, PCA, and structure models as per their pedigree. The linkage disequilibrium (LD) analysis showed Chr3 had higher LD regions while Chr1 and Chr2 had more low LD regions. The genetic divergence between the B- and R-line populations was 13%, and within the sub-population variability was 87%. In this experiment, we have mined 4K SNPs and optimized the genotyping protocol through AgriSeq technology for routine use, which is cost-effective, fast, and highly reproducible. The newly developed 4K mid-density SNP panel will be useful in genomics and molecular breeding experiments such as assessing the genetic diversity, trait mapping, backcross breeding, and genomic selection in pearl millet.

Pearl millet (Pennisetum glaucum L.), an important source of iron (Fe) and zinc (Zn) for millions of families in dryland tropics, helps in eradicating micronutrient malnutrition. The crop is rich in Fe and Zn, therefore, identification of the key genes operating the mineral pathways is an important step to accelerate the development of biofortified cultivars. In a first-of-its-kind experiment, leaf and root samples of a pearl millet inbred ICMB 1505 were exposed to combinations of Fe and Zn stress conditions using the hydroponics method, and a whole-genome transcriptome assay was carried out to characterize the differentially expressed genes (DEGs) and pathways. A total of 37,093 DEGs under different combinations of stress conditions were identified, of which, 7,023 and 9,996 DEGs were reported in the leaf and root stress treatments, respectively. Among the 10,194 unique DEGs, 8,605 were annotated to cellular, biological, and molecular functions and 458 DEGs were assigned to 39 pathways. The results revealed the expression of major genes related to the mugineic acid pathway, phytohormones, chlorophyll biosynthesis, photosynthesis, and carbohydrate metabolism during Fe and Zn stress. The cross-talks between the Fe and Zn provided information on their dual and opposite regulation of key uptake and transporter genes under Fe and Zn deficiency. SNP haplotypes in rice, maize, sorghum, and foxtail millet as well as in Arabidopsis using pearl millet Fe and Zn responsive genes could be used for designing the markers in staple crops. Our results will assist in developing Fe and Zn-efficient pearl millet varieties in biofortification breeding programs and precision delivery mechanisms to ameliorate malnutrition in South Asia and Sub-Saharan Africa.

Extensive use of chromium (Cr) in anthropogenic activities leads to Cr toxicity in plants causing serious threat to the environment. Cr toxicity impairs plant growth, development, and metabolism. In the present study, we explored the effect of NaHS [a hydrogen sulfide; (H2S), donor] and silicon (Si), alone or in combination, on two chickpea (Cicer arietinum) varieties (Pusa 2085 and Pusa Green 112), in pot conditions under Cr stress. Cr stress increased accumulation of Cr reduction of the plasma membrane (PM) H+-ATPase activity and decreased in photosynthetic pigments, essential minerals, relative water contents (RWC), and enzymatic and non-enzymatic antioxidants in both the varieties. Exogenous application of NaHS and Si on plants exposed to Cr stress mitigated the effect of Cr and enhanced the physiological and biochemical parameters by reducing Cr accumulation and oxidative stress in roots and leaves. The interactive effects of NaHS and Si showed a highly significant and positive correlation with PM H+-ATPase activity, photosynthetic pigments, essential minerals, RWC, proline content, and enzymatic antioxidant activities (catalase, peroxidase, ascorbate peroxidase, dehydroascorbate reductase, superoxide dismutase, and monodehydroascorbate reductase). A similar trend was observed for non-enzymatic antioxidant activities (ascorbic acid, glutathione, oxidized glutathione, and dehydroascorbic acid level) in leaves while oxidative damage in roots and leaves showed a negative correlation. Exogenous application of NaHS + Si could enhance Cr stress tolerance in chickpea and field studies are warranted for assessing crop yield under Cr-affected area.

Livestock provides an additional source of income for marginal cropping farmers, but crop residues that are used as a main source of animal feed are characteristically low in digestibility and protein content. This reduces the potential livestock product yield and quality. The key trait, which influences the quality and the cost of animal feed, is digestibility. In this study, we demonstrate that sorghum breeding can be directed to achieve genetic gains for both fodder biomass and digestibility without any trade-offs. The genotypic variance has shown significant differences for biomass across years (13,035 in 2016 and 3,395 in 2017) while in vitro organic matter digestibility (IVOMD) showed significant genotypic variation in 2016 (0.253) under drought. A range of agronomic and fodder quality traits was found to vary significantly in the population within both the control and drought conditions and across both years of the study. There was significant genotypic variance (σg2) and genotypic × treatment variance (σgxt2) in dry matter production in a recombinant inbred line (RIL) population in both study years, while there was only significant σg2 and σgxt2 in IVOMD under the control conditions. There was no significant correlation identified between biomass and digestibility traits under the control conditions, but there was a positive correlation under drought. However, a negative relation was observed between digestibility and grain yield under the control conditions, while there was no significant correlation under drought population, which was genotyped using the genotyping-by-sequencing (GBS) technique, and 1,141 informative single nucleotide polymorphism (SNP) markers were identified. A linkage map was constructed, and a total of 294 quantitative trait loci (QTLs) were detected, with 534 epistatic interactions, across all of the traits under study. QTL for the agronomic traits fresh and dry weight, together with plant height, mapped on to the linkage group (LG) 7, while QTL for IVOMD mapped on to LG1, 2, and 8. A number of genes previously reported to play a role in nitrogen metabolism and cell wall-related functions were found to be associated with these QTL.

Pearl millet is an important food and fodder crop cultivated in the arid and semi-arid regions of Africa and Asia, and is now expanding to other regions for forage purpose. This study was conducted to better understand the forage quantity and quality traits to enhance the feed value of this crop. Two sets of pearl millet hybrids (80 single cross hybrids in Set-I and 50 top cross hybrids in Set-II) along with their parents evaluated multi-locationally for the forage-linked traits under multi-cut (two cuts) system revealed significant variability for the forage traits in the hybrids and parents. The mean better parent heterosis (BPH) for total dry forage yield (TDFY) was 136% across all the single cross hybrids and 57% across all the top cross hybrids. The mean BPH for in vitro organic matter digestibility (IVOMD) varied from −11 to 7% in the single cross hybrids and −13 to 11% in the top cross hybrids across cuts. The findings of TDFY and IVOMD heterosis in these sets indicated the potential of improvement of the hybrid cultivars for forage quantity and quality in forage pearl millet. The parental lines single cross parent (SCP)-L02, SCP-L06, and top cross parent (TCP)-T08 found superior in the forage quantity and quality traits can be utilized in the future breeding programs. Most of the forage traits were found to be controlled by using the non-additive gene action. A diverse panel of 105 forage-type hybrid parents (Set-III) genotyped following genotyping by sequencing (GBS) and phenotyped for crude protein (CP) and IVOMD under multi-cuts for 2 years identified one stable significant single nucleotide polymorphism (SNP) on LG4 for CP, and nine SNPs for IVOMD distributed across all the linkage groups except on LG2. The identified loci, once validated, then could be used for the forage quality traits improvement in pearl millet through marker-assisted selection.

Sorghum (Sorghum bicolor L.) is a staple food crops in the arid and rainfed production ecologies. Sorghum plays a critical role in resilient farming and is projected as a smart crop to overcome the food and nutritional insecurity in the developing world. The development and characterisation of the sorghum pan-genome will provide insight into genome diversity and functionality, supporting sorghum improvement. We built a sorghum pan-genome using reference genomes as well as 354 genetically diverse sorghum accessions belonging to different races. We explored the structural and functional characteristics of the pan-genome and explain its utility in supporting genetic gain. The newly-developed pan-genome has a total of 35,719 genes, a core genome of 16,821 genes and an average of 32,795 genes in each cultivar. The variable genes are enriched with environment responsive genes and classify the sorghum accessions according to their race. We show that 53% of genes display presence-absence variation, and some of these variable genes are predicted to be functionally associated with drought adaptation traits. Using more than two million SNPs from the pan-genome, association analysis identified 398 SNPs significantly associated with important agronomic traits, of which, 92 were in genes. Drought gene expression analysis identified 1,788 genes that are functionally linked to different conditions, of which 79 were absent from the reference genome assembly. This study provides comprehensive genomic diversity resources in sorghum which can be used in genome assisted crop improvement.

Exploring the natural genetic variability and its exploitation for improved Nitrogen Use Efficiency (NUE) in sorghum is one of the primary goals in the modern crop improvement programs. The integrated strategies include high-throughput phenotyping, next generation sequencing (NGS)-based genotyping technologies, and a priori selected candidate gene studies that help understand the detailed physiological and molecular mechanisms underpinning this complex trait. A set of sixty diverse sorghum genotypes was evaluated for different vegetative, reproductive, and yield traits related to NUE in the field (under three N regimes) for two seasons. Significant variations for different yield and related traits under 0 and 50% N confirmed the availability of native genetic variability in sorghum under low N regimes. Sorghum genotypes with distinct genetic background had interestingly similar NUE associated traits. The Genotyping-By-Sequencing based SNPs (>89 K) were used to study the population structure, and phylogenetic groupings identified three distinct groups. The information of grain N and stalk N content of the individuals covered on the phylogenetic groups indicated randomness in the distribution for adaptation under variable N regimes. This study identified promising sorghum genotypes with consistent performance under varying environments, with buffer capacity for yield under low N conditions. We also report better performing genotypes for varied production use—grain, stover, and dual-purpose sorghum having differential adaptation response to NUE traits. Expression profiling of NUE associated genes in shoot and root tissues of contrasting lines (PVK801 and HDW703) grown in varying N conditions revealed interesting outcomes. Root tissues of contrasting lines exhibited differential expression profiles for transporter genes [ammonium transporter (SbAMT), nitrate transporters (SbNRT)]; primary assimilatory (glutamine synthetase (SbGS), glutamate synthase (SbGOGAT[NADH], SbGOGAT[Fd]), assimilatory genes [nitrite reductase (SbNiR[NADH]3)]; and amino acid biosynthesis associated gene [glutamate dehydrogenase (SbGDH)]. Identification and expression profiling of contrasting sorghum genotypes in varying N dosages will provide new information to understand the response of NUE genes toward adaptation to the differential N regimes in sorghum. High NUE genotypes identified from this study could be potential candidates for in-depth molecular analysis and contribute toward the development of N efficient sorghum cultivars.

Nitrogen (N) is one of the primary macronutrients required for crop growth and yield. This nutrient is especially limiting in the dry and low fertility soils where pearl millet [Pennisetum glaucum (L.) R. Br] is typically grown. Globally, pearl millet is the sixth most important cereal grown by subsistence farmers in the arid and semi-arid regions of sub-Saharan Africa and the Indian subcontinent. Most of these agro-ecologies have low N in the root zone soil strata. Therefore, there is an immense need to identify lines that use nitrogen efficiently. A set of 380 diverse pearl millet lines consisting of a global diversity panel (345), parents of mapping populations (20), and standard checks (15) were evaluated in an alpha-lattice design with two replications, 25 blocks, a three-row plot for 11 nitrogen use efficiency (NUE) related traits across three growing seasons (Summer 2017, Rainy 2017, and Summer 2018) in an N-depleted precision field under three different N levels (0%-N0, 50%-N50, 100%-N100 of recommended N, i.e., 100 kg ha–1). Analysis of variance revealed significant genetic variation for NUE-related traits across treatments and seasons. Nitrogen in limited condition (N0) resulted in a 27.6 and 17.6% reduction in grain yield (GY) and dry stover yield (DSY) compared to N50. Higher reduction in GY and DSY traits by 24.6 and 23.6% were observed under N0 compared to N100. Among the assessed traits, GY exhibited significant positive correlations with nitrogen utilization efficiency (NUtE) and nitrogen harvest index (NHI). This indicated the pivotal role of N remobilization to the grain in enhancing yield levels. Top 25 N-insensitive (NIS-top grain yielders) and N-sensitive (NS-poor grain yielders) genotypes were identified under low N conditions. Out of 25 NIS lines, nine genotypes (IP 10820, IP 17720, ICMB 01222-P1, IP 10379, ICMB 89111-P2, IP 8069, ICMB 90111-P2, ICMV IS89305, and ICMV 221) were common with the top 25 lines for N100 level showing the genotype plasticity toward varying N levels. Low N tolerant genotypes identified from the current investigation may help in the identification of genomic regions responsible for NUE and its deployment in pearl millet breeding programs through marker-assisted selection (MAS).

Millets are the strategic food crops in arid and drought-prone ecologies. Millets, by virtue of nature, are very well-adapted to drought conditions and able to produce sustainable yield. Millets have important nutrients that can help prevent micro-nutrient malnutrition. As a result of the adverse effect of climate change and widespread malnutrition, millets have attained a strategic position to sustain food and nutritional security. Although millets can adapt well to the drought ecologies where other cereals fail completely, the yield level is very low under stress. There is a tremendous opportunity to increase the genetic potential of millet crops in dry lands when the genetics of the drought-tolerance mechanism is fully explained. MicroRNAs (miRNAs) are the class of small RNAs that control trait expression. They are part of the gene regulation but little studied in millets. In the present study, novel miRNAs and gene targets were identified from the genomic resources of pearl millet, sorghum, foxtail millet, finger millet, and proso millet through in silico approaches. A total of 1,002 miRNAs from 280 families regulating 23,158 targets were identified using different filtration criteria in five millet species. The unique as well as conserved structural features and functional characteristics of miRNA across millets were explained. About 84 miRNAs were conserved across millets in different species combinations, which explained the evolutionary relationship of the millets. Further, 215 miRNAs controlling 155 unique major drought-responsive genes, transcription factors, and protein families revealed the genetics of drought tolerance that are accumulated in the millet genomes. The miRNAs regulating the drought stress through specific targets or multiple targets showed through a network analysis. The identified genes regulated by miRNA genes could be useful in developing functional markers and used for yield improvement under drought in millets as well as in other crops.

Germplasm should be conserved in such a way that the genetic integrity of a given accession is maintained. In most genebanks, landraces constitute a major portion of collections, wherein the extent of genetic diversity within and among landraces of crops vary depending on the extent of outcrossing and selection intensity infused by farmers. In this study, we assessed the level of diversity within and among 108 diverse landraces and wild accessions using both phenotypic and genotypic characterization. This included 36 accessions in each of sorghum, pearl millet, and pigeonpea, conserved at ICRISAT genebank. We genotyped about 15 to 25 individuals within each accession, totaling 1,980 individuals using the DArTSeq approach. This resulted in 45,249, 19,052, and 8,211 high-quality single nucleotide polymorphisms (SNPs) in pearl millet, sorghum, and pigeonpea, respectively. Sorghum had the lowest average phenotypic (0.090) and genotypic (0.135) within accession distances, while pearl millet had the highest average phenotypic (0.227) and genotypic (0.245) distances. Pigeonpea had an average of 0.203 phenotypic and 0.168 genotypic within accession distances. Analysis of molecular variance also confirms the lowest variability within accessions of sorghum (26.3%) and the highest of 80.2% in pearl millet, while an intermediate in pigeonpea (57.0%). The effective sample size required to capture maximum variability and to retain rare alleles while regeneration ranged from 47 to 101 for sorghum, 155 to 203 for pearl millet, and 77 to 89 for pigeonpea accessions. This study will support genebank curators, in understanding the dynamics of population within and among accessions, in devising appropriate germplasm conservation strategies, and aid in their utilization for crop improvement.

Biofortification through plant breeding is a cost-effective and sustainable approach towards addressing micronutrient malnutrition prevailing across the globe. Screening cultivars for micronutrient content and identification of quantitative trait loci (QTLs)/genes and markers help in the development of biofortified varieties in chickpea (Cicer arietinum L.). With the aim of identifying the genomic regions controlling seed Fe and Zn concentrations, the F2:3 population derived from a cross between MNK-1 and Annigeri 1 was genotyped using genotyping by sequencing approach and evaluated for Fe and Zn concentration. An intraspecific genetic linkage map comprising 839 single nucleotide polymorphisms (SNPs) spanning a total distance of 1,088.04 cM with an average marker density of 1.30 cM was constructed. By integrating the linkage map data with the phenotypic data of the F2:3 population, a total of 11 QTLs were detected for seed Fe concentration on CaLG03, CaLG04, and CaLG05, with phenotypic variation explained ranging from 7.2% (CaqFe3.4) to 13.4% (CaqFe4.2). For seed Zn concentration, eight QTLs were identified on CaLG04, CaLG05, and CaLG08. The QTLs individually explained phenotypic variations ranging between 5.7% (CaqZn8.1) and 13.7% (CaqZn4.3). Three QTLs for seed Fe and Zn concentrations (CaqFe4.4, CaqFe4.5, and CaqZn4.1) were colocated in the “QTL-hotspot” region on CaLG04 that harbors several drought tolerance-related QTLs. We identified genes in the QTL regions that encode iron–sulfur metabolism and zinc-dependent alcohol dehydrogenase activity on CaLG03, iron ion binding oxidoreductase on CaLG04, and zinc-induced facilitator-like protein and ZIP zinc/iron transport family protein on CaLG05. These genomic regions and the associated markers can be used in marker-assisted selection to increase seed Fe and Zn concentrations in agronomically superior chickpea varieties.

Much of the world’s population growth will occur in regions where food insecurity is prevalent, with large increases in food demand projected in regions of Africa and South Asia. While improving food security in these regions will require a multi-faceted approach, improved performance of crop varieties in these regions will play a critical role. Current rates of genetic gain in breeding programs serving Africa and South Asia fall below rates achieved in other regions of the world. Given resource constraints, increased genetic gain in these regions cannot be achieved by simply expanding the size of breeding programs. New approaches to breeding are required. The Genomic Open-source Breeding informatics initiative (GOBii) and Excellence in Breeding Platform (EiB) are working with public sector breeding programs to build capacity, develop breeding strategies, and build breeding informatics capabilities to enable routine use of new technologies that can improve the efficiency of breeding programs and increase genetic gains. Simulations evaluating breeding strategies indicate cost-effective implementations of genomic selection (GS) are feasible using relatively small training sets, and proof-of-concept implementations have been validated in the International Maize and Wheat Improvement Center (CIMMYT) maize breeding program. Progress on GOBii, EiB, and implementation of GS in CIMMYT and International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) breeding programs are discussed, as well as strategies for routine implementation of GS in breeding programs serving Africa and South Asia.

Fusarium wilt (Fusarium oxysporum f. sp. ciceris) of chickpea is the major limitation to chickpea production worldwide. As the nature of the pathogen is soil borne, exploitation of host plant resistance is the most suitable and economical way to manage this disease. Present study was therefore conducted with an aim to find new, stable and durable sources of resistance of chickpea against Fusarium wilt through multi-environment and multi-year screening. During 2007/2008 crop season, 130 promising genotypes having

Pearl millet is a climate resilient crop and one of the most widely grown millets worldwide. Heterotic hybrid development is one of the principal breeding objectives in pearl millet. In a maiden attempt to identify heterotic groups for grain yield, a total of 343 hybrid parental [maintainer (B-) and restorer (R-)] lines were genotyped with 88 polymorphic SSR markers. The SSRs generated a total of 532 alleles with a mean value of 6.05 alleles per locus, mean gene diversity of 0.55, and an average PIC of 0.50. Out of 532 alleles, 443 (83.27%) alleles were contributed by B-lines with a mean of 5.03 alleles per locus. R-lines contributed 476 alleles (89.47%) with a mean of 5.41, while 441 (82.89%) alleles were shared commonly between B- and R-lines. The gene diversity was higher among R-lines (0.55) compared to B-lines (0.49). The unweighted neighbor-joining tree based on simple matching dissimilarity matrix obtained from SSR data clearly differentiated B- lines into 10 sub-clusters (B1 through B10), and R- lines into 11 sub-clusters (R1 through R11). A total of 99 hybrids (generated by crossing representative 9 B- and 11 R- lines) along with checks were evaluated in the hybrid trial. The 20 parents were evaluated in the line trial. Both the trials were evaluated in three environments. Based on per se performance, high sca effects and standard heterosis, F1s generated from crosses between representatives of groups B10R5, B3R5, B3R6, B4UD, B5R11, B2R4, and B9R9 had high specific combining ability for grain yield compared to rest of the crosses. These groups may represent putative heterotic gene pools in pearl millet.

The low grain iron and zinc densities are well documented problems in food crops, affecting crop nutritional quality especially in cereals. Sorghum is a major source of energy and micronutrients for majority of population in Africa and central India. Understanding genetic variation, genotype × environment interaction and association between these traits is critical for development of improved cultivars with high iron and zinc. A total of 336 sorghum RILs (Recombinant Inbred Lines) were evaluated for grain iron and zinc concentration along with other agronomic traits for 2 years at three locations. The results showed that large variability exists in RIL population for both micronutrients (Iron = 10.8 to 76.4 mg kg−1 and Zinc = 10.2 to 58.7 mg kg−1, across environments) and agronomic traits. Genotype × environment interaction for both micronutrients (iron and zinc) was highly significant. GGE biplots comparison for grain iron and zinc showed greater variation across environments. The results also showed that G × E was substantial for grain iron and zinc, hence wider testing needed for taking care of G × E interaction to breed micronutrient rich sorghum lines. Iron and zinc concentration showed high significant positive correlation (across environment = 0.79; p < 0.01) indicating possibility of simultaneous effective selection for both the traits. The RIL population showed good variability and high heritabilities (>0.60, in individual environments) for Fe and Zn and other traits studied indicating its suitability to map QTL for iron and zinc.

Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped extensively for yield and yield related traits at two different locations (Delhi and Patancheru, India) during the crop seasons 2011-12 and 2012-13 under rainfed and irrigated conditions. In parallel, these lines were also genotyped using DArTseq platform to generate data on 3,000 polymorphic markers. Phenotypic and genotypic data were used with six statistical GS models to estimate the prediction accuracies. GS models were tested for four yield related traits viz. seed yield, 100 seed weight, days to 50% flowering and days to maturity. Prediction accuracy for the models tested varied from 0.138 (seed yield) to 0.912 (100 seed weight), whereas performance of models did not show any significant difference for estimating prediction accuracy within traits. Kinship matrix calculated using genotyping data reaffirmed existence of two different groups within selected lines. There was not much effect of population structure on prediction accuracy. In brief, present study establishes the necessary resources for deployment of GS in chickpea breeding.