Context Pearl millet (Pennisetum glaucum L.) is a key dryland staple crop suffering significant yield losses under heat and drought stress. Both marginal and productive ecologies of pearl millet cultivation require distinct ideotypes for breeding, whereas strong genotype × environment interactions and multiple correlated traits complicate simultaneous selection. Aims This study aimed to identify high-performing and stable pearl millet genotypes for marginal (A1) and favorable (AB) environments by using integrated multi-trait and stability-based selection indices. Methods A global diversity panel of 242 pearl millet inbred lines (PMiGAP) was evaluated over three kharif seasons (2022–2024) at ICAR-IARI, New Delhi. Nine agronomic traits were recorded and analyzed using mixed models. Genotypes were assessed using MGIDI, WAASB and WAASBY indices. Environment-specific ideotypes were defined and predicted genetic gains were estimated at 15% selection intensity. Key results Significant genotype, environment and genotype × environment effects were observed for all traits. Moderate to high heritability was recorded for flowering time and panicle length whereas yield traits showed low to moderate heritability. MGIDI identified 37 superior genotypes per environment. Predicted gains included −4.60% for days to flowering and +13.7% for panicles per plant for A1 and +13.4% for grain yield per panicle in AB environment. WAASB and WAASBY identified IP 12020, IP 8949, IP 18293-P152, PT-732B-P2, and IP 5207 as high-performing and stable. Conclusions The integrated MGIDI–WAASB–WAASBY framework enabled objective selection of superior genotypes combining multi-trait performance and stability across multi-environment. Implications The identified genotypes provide valuable material for breeding programs targeting both drought-prone and favorable environments and can accelerate genetic gain and yield stability in pearl millet.

Addressing micronutrient malnutrition requires targeted biofortification of staple crops such as pearl millet [Pennisetum glaucum (L.) R.Br.], which is widely consumed in arid and semi-arid regions. This study assessed 47 advanced breeding lines developed at ICAR-IARI, New Delhi, to evaluate genetic variability, heritability, and diversity for nutritional (iron, zinc, protein, starch, oil, amylose) and anti-nutritional (phytate and phenol) traits. Substantial variation was observed for grain iron (33.9–121.4 mg/kg), zinc (27.4–90.0 mg/kg), and protein (7.99–15.56

Rancidity remains a critical challenge in pearl millet, leading to quick decline in flour quality and restricting its shelf life, consumer appeal, and marketability. Simultaneous improvement for low rancidity and stable yield in pearl millet complicates selection due to the involvement of multiple, contrasting traits. Four multi-trait stability approaches, Smith-Hazel Index (SHI), Factor Analysis and Ideotype-Based BLUP Index (FAI-BLUP), Multi-Trait Stability Index (MTSI), and Multi-Trait Genotype-Ideotype Distance Index (MGIDI) were evaluated to determine their efficiency in identifying superior, stable, and ideotype-aligned genotypes for low rancidity and yield associated traits. A globally diverse panel of 220 genotypes was evaluated for four key rancidity-related traits under both fresh and stored conditions, along with five major agronomic traits assessed across multiple environments in India. The MTSI exhibited negative selection differentials for all rancidity-related parameters, reflecting effective reduction of undesirable rancidity traits. Both the Smith-Hazel (SH) and FAI-BLUP indices effectively identified elite multi-trait-superior pearl millet genotypes. Each method selected 33 genotypes combining low rancidity with desirable agronomic performance, with FAI-BLUP additionally emphasizing stability and proximity to the ideotype. The Venn diagram analysis revealed fifteen genotypes that consistently ranked as superior across all three indices MTSI, Smith-Hazel, and MGIDI namely G28 (GB8735), G37 (IP-6060), G44 (IP-12840), G95 (IP-10953), G33 (ICMV88908), G57 (IP-17554), G31 (IP-3757), G71 (ICMB90111), G220 (Damodhar Bajri), G45 (IP-19386), G3 (ICTP8203), G52 (IP-13149), G75 (IP-5695), G78 (IP-7095), and G142 (IP-21169). In pearl millet, this is the first study to concurrently employed four multi-trait stability models to unravel G & times; E interactions specifically for rancidity-related traits alongside grain yield.

Pearl millet is a vital dietary source for dry land populations and is often regarded as a “super cereal”; however, genetic improvement has lagged behind major cereals, resulting in slow progress in nutritional enhancement. In the present study, genotyping-by-sequencing-derived SNP markers were used in a 178-line PMiGAP panel evaluated across four agro-ecologically diverse environments to dissect genomic diversity, population structure, and linkage disequilibrium associated with four mineral traits (Fe, Zn, P, and Mn) and two anti-nutritional traits (PAC and TTC). A total of 76,220 high-confidence SNPs were retained for analysis. Population structure resolved five genetically coherent yet variably admixed subgroups aligned with geographic origin, while genome-wide FST scans revealed heterogeneous selection signatures across the panel. GWAS using the BLINK algorithm identified 16 significant MTAs distributed across six chromosomes, including two environmentally stable SNPs, S1_237185612 (Zn) and S4_57239923 (TTC). Functional annotation showed that S4_57239923 (Chr Pgl04; Pgl_GLEAN_10024187) functions in Ca2+-dependent signalling and vascular transport, influencing micronutrient allocation via ZIP/ZIF-mediated Zn mobilization and ferritin-driven Fe sequestration. SNP S1_237185612 (Chr Pgl01; Pgl_GLEAN_10014727, 10014726, 10014724, 10014723, 10014728) mapped to pathways related to metal sensing, protein turnover, cell-wall chelation, and nutrient signalling, consistent with established Zn transport and micronutrient buffering mechanisms. These findings represent the first multi-environment SNP-based genomic dissection of nutritional and anti-nutritional traits using the globally diverse PMiGAP panel evaluated across representative A1, A, and B agro-ecological zones of India, providing robust genomic resources, stable diagnostic markers, and functionally supported candidate genes for marker-assisted selection, genomic prediction, and precise nutritional enhancement.

Context Pearl millet, a climate-resilient, nutrient-rich cereal, faces productivity challenges from environmental variability, necessitating identification of stable, high-yielding genotypes.Aims This study aimed to identify stable, high-yielding pearl millet to achieve increased grain yield per hectare (GYPH), spike length (SL), spike girth (SG), and thousand-seed weight (TSW) from a global germplasm collection of 248 pearl millet genotypes.Methods Field trials were conducted in an alpha lattice design with three replications across three environments. Genotype stability and performance were assessed using additive main effect and multiplicative interaction (AMMI) and genotype main effect plus genotype-by-environment interaction (GGE) biplot analyses. Stability indices (AMMI-based stability parameter (ASTAB), AMMI stability index (ASI), AMMI stability value (ASV), modified AMMI stability index (MASI), and modified AMMI stability value (MASV)) were integrated to quantitatively assess the stable genotypes.Key results The first two AMMI principal components explained 55% and 45% of the total variation for GYPH, whereas GGE biplots explained 84.99%, 88.89%, 77.7%, and 83.17% for GYPH, SL, SG, and TSW respectively. AMMI identified G57, G101, and G209 as stable for GYPH, whereas GGE selected G87, G242, G246, and G131. The genotype selection index (GSI) highlighted G87, G209, G242, G143, and G172 as highly stable for GYPH. Stable genotypes were also identified for SL (G57, G246, G140), SG (G218, G157, G8), and TSW (G57, G95, G149).Conclusions The integrated assessment of stability using multiple approaches was shown to be effective in identifying stable genotypes across diverse environments. Notably, G87 emerged as the most stable genotype for GYPH.Implications Integrating stable genotypes into breeding programs could enhance yield stability, disease resistance, and grain quality, ensuring adaptability across environments.

Pearl millet production environments spans from severely moisture stressed to better endowed ecologies. ‘Minicore collection’, a global diversity capsule of 238 genotypes is a prized genetic resource for strengthening breeding programs. With the aim to evaluate genetic merit of pearl millet minicore for best trait combinations for different production environments, data on eight metric traits were recorded from field trials conducted for four years during 2021–2024. The results revealed significant effects of genotypes, environment and genotype × environment with higher mean squares due to environments indicating larger role of environment in trait expression. Fifteen early-flowering including two extra-early genotypes hold strong promise for drought‐prone and short‐season environments, where rapid flowering is a vital adaptive trait. Days to flowering and panicle length exhibited both moderate-to-high heritability whereas in contrast, grain yield, panicle and tiller number showed low heritability reflecting a greater influence of environmental variation. Genotypes IP 13387, IP 19964, IP 5869, IP 10953, IP 7422, IP 10371, IP 12374 and IP 16402 stands out based on MGIDI and MTSI indices representing key candidates with higher stability and broad adaptability. These findings highlight the potential of minicore to accelerate pearl millet improvement under changing climatic conditions and diverse production environments.

Pearl millet, known for its nutritional excellence and climatic resilience, is becoming important in addressing food and nutritional security Current work introduces Near Infrared Spectroscopy models to estimate nutrients in pearl millet grains. The model is quick, economic and non-destructive alternative to traditional methods, useful in advancing the single plant progenies for improving nutrient content in segregating generations. Spectra were acquired from 403 varied genotypes, and mathematical optimizations using derivatives were performed to enhance the models. The optimal configurations were "2,36,6,2" (order of derivatives, gap, first smoothing and second smoothing, respectively) for amylose, "2,32,6,2" for starch, "2,32,8,2" for oil and protein, and "3,36,6,2" for phytic acid. The models were refined using modified partial least squares (MPLS) regression on spectra processed to eliminate variations with standard normal variate (SNV) and detrending (DT) techniques. The adjusted MPLS models exhibited impressive coefficients of determination of 0.985, 0.984, 0.986, 0.969 and 0.993 for amylose, protein, oil, starch and phytic acid, respectively. The SEP(C) values for amylose (0.347), starch (0.732), protein (0.313), phytic acid (0.014), and oil (0.162) suggest variable levels of predictive precision. Validation with independent samples showed superior predictive performance with coefficients of determination values ranging from 0.878 for phytic acid to 0.976 for protein, minimal bias, high ratios of prediction to deviation (2.93-5.81), and no significant differences between the predicted and reference values (p > 0.05). These advanced Near-Infrared Spectroscopy models allow quick and cost-effective nutritional assessment of pearl millet germplasm and breeding lines, supporting biofortification initiatives and enhancing nutritional security.

Pearl millet is a vital nutri-cereal that serves as a staple food and a significant source of calories for millions of people in arid and semi-arid tropical regions. The present work aims to conduct various genetic interpretations using six generations of six crosses, which were evaluated during the South-west monsoon season 2021 and 2022 at IARI, New Delhi, India for different biochemical traits. Amylose content (AC) among all the genotypes varied from 21.3-26.4g/100g, starch content (SC) from 56.1-71.0g/100g, oil content from 5.37-13.2g/100g, total protein content from 5.7-14.7g/100g, phytic acid content from 0.86-1.01g/100g and total phenolic content (TPhC) from 0.06-0.19g/100g. Seed yield per spike (SYS) showed positive correlation with thousand seed weight (TSW) and SC while there was negative correlation with protein content. Significant variation was observed for almost all the traits except in a few cases. AC and SC were governed by both additive and dominant gene actions. However, phytic acid, TPhC, TSW and SYS exhibited a stronger bias towards dominant gene action, therefore selection can be delayed to later generations to achieve greater homozygosity and trait stability. In contrast, oil and protein content were primarily controlled by additive effects, indicating that early-generation selection may prove beneficial for identifying superior breeding lines.

Pearl millet is nutrient-rich, but mineral bioavailability is limited by anti-nutritional factors like tannins and phytic acid. This study assessed seed soaking (0, 12, and 24 h) in 30 genotypes. Soaking significantly reduced phytic acid and tannins, enhancing mineral bioavailability. However, it caused nutrient leaching, decreasing phosphorus (5731.38-1006.83 mg/kg), zinc (69.21-50.37 mg/kg), iron (116.42-93.12 mg/kg), and manganese (17.91-13.93 mg/kg). Association analysis suggested 12 h soaking balanced nutrient retention and anti-nutrient reduction. Principal component analysis (65.9 % variation) identified phytic acid, tannins, zinc, and phosphorus as key contributors. Multi-trait selection indices identified G19, G22, and G23 as most suitable for enhancing bioavailability. G29 had the highest tannin reduction (89.17 %), while G23 showed the greatest phytic acid decrease (87.77 %). These findings highlighted the effectiveness of seed soaking in reducing anti-nutrients and enhancing mineral bioavailability in pearl millet.

Wild relatives of pearl millet thrive under harsh arid and semi-arid ecologies due to higher resilience to both biotic and abiotic stresses. With the objective to evaluate wild germplasm for stress tolerance and their utilization for wide hybridization, two set of investigations were conducted. In the first study, forty two accessions of Pennisetum monodii were evaluated for phenotypic traits, foliar blast resistance and tolerance to dehydration stress at seedling stage while in second study quantitative trait variability were evaluated in F2 generation generated from interspecific crosses between P. glaucum × P. monodii. Wide variation for quantitative traits were observed among which high number of tillers and panicles per plant were most distinct. Seven genotypes showed resistant reaction to foliar blast both under natural epiphytotic and artificial disease conditions. Seedling dehydration stress carried out through hydroponics differentiated tolerant and susceptible genotypes in which five genotypes showed tolerant reaction manifested by high shoot length, high root length and shoot weight under stress conditions. Genotypes IP 22019 and IP 21675 showed resistant reaction to foliar blast as well as tolerance to dehydration stress. Data recorded on eight interspecific crosses showed transgressive segregants for number of panicles per plant, tillers per plant and panicle length. Wild accessions with desirable traits and transgressive segregants provide novel trait combinations for efficient use in pearl millet pre-breeding.

In drier zones pearl millet faces moderate to severe drought stress at seedling stage leading to mortality and poor plant stand. An effective and rapid drought screening protocol as well as tolerant genotypes are required to address the issue. Hydroponics provide an uniform stress environment which we utilized in the study to create dehydration stress in pearl millet seedlings through root dehydration. Stress duration for 7 days @ 6 h/day differentiated the tolerant and susceptible genotypes. Pearl millet minicore collection of 207 genotypes were divided in to four groups based on seedlings traits measured under stress. Phenotypic response of seedlings to dehydration stress measured through drought score showed moderate correlation with quantum yield and fresh shoot weight. In all, 32 genotypes showed tolerant reaction to seedling drought stress. Both tolerant and susceptible genotypes identified under hydroponics performed at par under soil-pot conditions. Genotypes IP 3642, IP 20995, IP 10665, IP 1556, IP 2322, IP 8562, IP 18579, IP 8472, IP 5711, IP 277, IP 11268 showed better seedling growth parameters under rapid dehydration through hydroponics as well in progressive soil drying under pot conditions.

To identify the best crop genotypes for recommendation to breeders, and eventually, for use in breeding, evaluation is usually done in field trials in a variety of environments, called multi-environment trials. This study aims to identify stable sources of yield and its component traits across various environments to ensure the long-term breeding progress of pearl millet. To find stable genotypes for cropping under various environmental conditions, 37 genotypes of pearl millet were examined from 2014 to 2016 growing seasons in nine diverse environments, including Delhi, Dharwad, and Jodhpur. The stability of the pearl millet was assessed for eight yield component traits and two nutritional traits using the weighted average of absolute scores biplot (WAASB) for the best linear unbiased predictions of the genotype–environment interaction and the multi-trait stability index (MTSI). Based on the WAASBY index, the genotypes G36, G25, G23, G18, G16, G15, and G1 are selected as the productive and stable genotypes for SYPP. Out of 37 pearl millet genotypes, MTSI analysis for several environments showed that the genotypes G16, G15, G26, G34, G4, and G17 were the most stable and high yielding. It is concluded that identified genotypes can be used as parents in breeding programs for the development of high-yielding breeding material across the environments. The current study's findings suggested that MTSI, which is a powerful and straightforward selection technique, may be useful to plant breeders for the selection of genotypes based on a variety of traits.

Pearl millet is renowned for its exceptional nutritional value due to its high concentration of essential nutrients. However, a substantial hurdle hindering its global adoption is the issue of rancidity, which manifests as the development of undesirable odours and flavors in millet flour. The present work aims to evaluate a set of highly diverse 255 accessions for exploring genotypic variations related to biochemical parameters influencing rancidity and their categorization using a rancidity matrix. These parameters include comprehensive acid value (CAV), comprehensive peroxide value (CPV), as well as lipase and lipoxygenase (LOX) enzyme activities under both fresh and stored conditions. High heritability and genetic advance for CPV and LOX under both fresh and stored conditions indicated the presence of additive genetic effects. Positive associations were noted among all the rancidity-related biochemical parameters. Principal component analysis (PCA) further illustrated the positive correlation between CAV and lipase activity, and between CPV and LOX activity. Based on lower values of CAV under fresh conditions and all other biochemical parameters under fresh and stored conditions, lines IP 5695 and IP 19334 were identified as low rancid lines. Additionally, genotypes were categorized into low, medium, and high rancidity groups based on CAV and CPV, providing valuable insights into trait variability. These findings hold significant promise for the development of breeding material, variety and hybrids of pearl millet with longer shelf life and wider utilization.

Pearl millet is a climate-resilient nutri-cereal with the potential to improve food security. This study aims to identify stable pearl millet genotypes for grain yield and associated traits using various multi-trait models. A highly diverse global set of 248 pearl millet genotypes was evaluated for seven agronomic traits across diverse environments in India. The pooled ANOVA revealed significant genetic variability and interaction for all traits. Four multi-trait stability models—multi-trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), multi-trait mean performance and stability (MTMPS), and multi trait index based on factor analysis and ideotype-design (FAI-BLUP) were compared to assess their selection efficiency in identifying ideal genotypes for grain yield and associated traits. The MGIDI showed positive selection differentials for 5 out of 7 traits. The MTSI and MTMPS models showed the highest coincidence with 9 common genotypes. In our study, G57 (IP-12298), a traditional cultivar from Nigeria, was selected by the MTSI, MTMPS, and FAI-BLUP models for its consistent performance and stability across environments. Similarly, IP 8767 from Botswana, along with IP 4542 and IP 3138 from India, were consistently identified by the MGIDI, MTMPS, and FAI-BLUP models. In pearl millet this is the first attempt to simultaneously apply BLUP, WAASB, and four multi-trait stability models to delineate G × E interactions. These identified stable and high-yielding genotypes could contribute to the development of improved pearl millet cultivars and can play a significant role in ensuring the food and nutritional security of arid and semi-arid regions of world.

Context Micronutrient enrichment of pearl millet (Pennisetum glaucum (L.) R.Br.), an important food source in arid and semi-arid Asia and Africa, can be achieved by using stable genotypes with high iron and zinc content in breeding programs. Aims We aimed to identify stable expression of high grain iron and zinc content in pearl millet lines across environments. Methods In total, 29 genotypes comprising 25 recombinant inbred lines (RILs), two parental lines and two checks were grown and examined from 2014 to 2016 in diverse environments. Best performing genotypes were identified through genotype + genotype × environment interaction (GGE) biplot and additive main-effects and multiplicative interaction (AMMI) model analysis. Key results Analysis of variance showed highly significant (P < 0.01) variations. The GGE biplot accounted for 87.26% (principal component 1, PC1) and 9.64% (PC2) of variation for iron, and 87.04% (PC1) and 6.35% (PC2) for zinc. On the basis of Gollob’s F validation test, three interaction PCs were significant for both traits. After 1000 validations, the real root-mean-square predictive difference was computed for model diagnosis. The GGE biplot indicated two winning RILs (G4, G11) across environments, whereas AMMI model analysis determined 10 RILs for iron (G12, G23, G24, G7, G15, G13, G25, G11, G4, G22) for seven for zinc (G14, G15, G4, G7, G11, G4, G26) as best performers. The most stable RILs across environments were G12 for iron and G14 for zinc. Conclusions High iron and zinc lines with consistent performance across environments were identified and can be used in the development of biofortified hybrids. Implications The findings suggest that AMMI and GGE, as powerful and straightforward techniques, may be useful in selecting better performing genotypes.

Pearl millet is endowed with important nutritional attributes and climate resilience and has been identified as potential staple food crop to address nutritional and food security. Gene action studies for different traits will assist in devising suitable breeding strategies. The present study was conducted to determine gene actions for grain iron and zinc concentrations and agro-morphological traits using generation mean analysis for biofortified pearl millet breeding. Six generations P1, P2, F1, F2, BC1 and BC2 were evaluated during South-west monsoon season 2021 and 2022. Analysis of variance showed significant variability for all the traits in both seasons. Six parameter models revealed the predominance of additive and dominant gene effects and non-allelic interactions for plant height, spike length, spike girth 1000- seed weight, iron and zinc content. Seed yield per spike was predominantly under non-additive gene control (maximum in cross I where d was 29.53 and l was -49.53); however, additive genetic control also contributed significantly. Likewise, for day to 50% flowering, days to maturity and number of productive tillers, dominant and additive x dominance type of gene effects were substantial. These findings provide deeper insights for strategizing breeding methods to increase iron and zinc content as well as yield potentially.

Genomics and genome editing promise enormous opportunities for crop improvement and elementary research. Precise modification in the specific targeted location of a genome has profited over the unplanned insertional events which are generally accomplished employing unadventurous means of genetic modifications. The advent of new genome editing procedures viz; zinc finger nucleases (ZFNs), homing endonucleases, transcription activator like effector nucleases (TALENs), Base Editors (BEs), and Primer Editors (PEs) enable molecular scientists to modulate gene expressions or create novel genes with high precision and efficiency. However, all these techniques are exorbitant and tedious since their prerequisites are difficult processes that necessitate protein engineering. Contrary to first generation genome modifying methods, CRISPR/Cas9 is simple to construct, and clones can hypothetically target several locations in the genome with different guide RNAs. Following the model of the application in crop with the help of the CRISPR/Cas9 module, various customized Cas9 cassettes have been cast off to advance mark discrimination and diminish random cuts. The present study discusses the progression in genome editing apparatuses, and their applications in chickpea crop development, scientific limitations, and future perspectives for biofortifying cytokinin dehydrogenase, nitrate reductase, superoxide dismutase to induce drought resistance, heat tolerance and higher yield in chickpea to encounter global climate change, hunger and nutritional threats.

Background: To study the genetic basis of the impact of genotypes and morpho-physio-biochemical traits under different organic and inorganic fertilizer doses on the shelf life attribute of tomatoes, field experiments were conducted in randomized block designs during the rabi seasons of 2018–2019 and 2019–2020. The experiment comprised three diverse nutrient environments [T1—organic; T2—inorganic; T3—control (without any fertilizers)] and five tomato genotypes with variable growth habits, specifically Angoorlata (Indeterminate), Avinash-3 (semi-determinate), Swaraksha (semi-determinate), Pusa Sheetal (semi-determinate), and Pusa Rohini (determinate).Results: The different tomato genotypes behaved apparently differently from each other in terms of shelf life. All the genotypes had maximum shelf life when grown in organic environments. However, the Pusa Sheetal had a maximum shelf life of 8.35 days when grown in an organic environment and showed an increase of 12% over the control. The genotype Pusa Sheetal, organic environment and biochemical trait Anthocyanin provides a promise as potential contributor to improve the keeping quality of tomatoes.Conclusion: The genotype Pusa Sheetal a novel source for shelf life, organic environment, and anthocyanin have shown promises for extended shelf life in tomatoes. Thus, the identified trait and genotype can be utilized in tomato improvement programs. Furthermore, this identified trait can also be targeted for its quantitative enhancement in order to increase tomato shelf life through a genome editing approach. A generalized genome editing mechanism is consequently suggested.

Iron (Fe) and zinc (Zn) deficiency has been identified as a major food-related health issue, affecting two billion people globally. Efforts to enhance the Fe and Zn content in food grains through plant breeding are an economic and sustainable solution to combat micronutrient deficiency in resource-poor populace of Asia and Africa. Pearl millet, Cenchrus americanus (L). Morrone, considered as a hardy nutri-cereal, is the major food crop for millions of people of these nations. As an effort to enhance its grain mineral content, an investigation was conducted using line × tester analysis to generate information on the extent of heterosis, gene action, combining ability for grain yield potential, and grain mineral nutrients (Fe and Zn). The partitioning of variance attributable to parents indicated that the lines and testers differed significantly for the traits studied. For most of the attributes, hybrids that were superior to the parents in the desired direction in terms of per se performance were identified. The analysis of combining ability variance indicated the preponderance of both additive and non-additive genetic effects. Thus, reciprocal recurrent selection can be used to develop a population with high–grain Fe and Zn contents. The Fe and Zn content in grain exhibited a highly significant and positive association between them, whereas the Fe and Zn contents individually showed a negative, albeit weak, correlation with grain yield and a moderate positive relation with grain weight. This indicates that mineral nutrient contents in grains can be improved without significant compromise on yield. The consistency of these trends across the environment suggests that these findings could be directly used as guiding principles for the genetic enhancement of Fe and Zn grain content in pearl millet.

Grain color in pearl millet is a combination of the color and thickness of the pericarp, particularly the mesocarp, and the color and vitreosity of the endosperm. Pearl millet has a thin pericarp which allows endosperm color and texture to appear through pericarp. Segregation analysis involving F 1 , F 2 , and BC1 populations from six crosses WGI 100 × ICMB 13222, HFeIT 17/2 × PPMI 1229, ICMB 13222 × PPMI 1229, HFeIT 17/2 × WGI 100, ICFD 14-R-61 × WGI 100 and ICFD 14-R-61 × PPMI 1229 revealed that single pair of major genes governs cream grain color in pearl millet. Cream grain color was found to be dominant over grey grain color. Two DNA pools were established from the homozygote cream and grey grain color plants for bulked segregant analysis. Among the 313 pairs of microsatellite primers used in the present study, three markers showed polymorphism in DNA pools, parents, F 1 and F 2 populations. Molecular mapping and validation revealed that the gene controlling cream grain color is present on linkage group 2 and flanked by markers Xpsmp 2089 and Xipes 0218 at a distance of approximately 16.9 cM and 17.9 cM, respectively. This work is the first report on the molecular mapping of the gene that controls the color of cream grains in pearl millet.