10 research outputs found

    Mapping QTL for important seed traits in an interspecific F2 population of pigeonpea

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    Seed traits present important breeding targets for enhancing grain yield and quality in various grain legume crops including pigeonpea. The present study reports significant genetic variation for six seed traits including seed length (SL), seed width (SW), seed thickness (ST), seed weight (SWT), electrical conductivity (EC) and water uptake (WU) among Cajanus cajan (L.) Millspaugh acc. ICPL 20340 and Cajanus scarabaeoides (L.) Thouars acc. ICP 15739 and an F2 population derived from this interspecific cross. Maximum phenotypic values recorded for the F2 population were higher than observed in the parent ICPL 20340 [F2 max vs ICPL 20340: SW (7.05 vs 5.38), ST (4.63 vs 4.51), EC (65.17 vs 9.72), WU (213.17 vs 109.5)], which suggested contribution of positive alleles from the wild parent, ICP 15739. Concurrently, to identify the QTL controlling these seed traits, we assayed two parents and 94 F2 individuals with 113 polymorphic simple sequence repeat (SSR) markers. In the F2 population, 98 of the 113 SSRs showed Mendelian segregation ratio 1:2:1, whereas significant deviations were observed for 15 SSRs with their χ2 values ranging between 6.26 and 20.62. A partial genetic linkage map comprising 83 SSR loci was constructed. QTL analysis identified 15 marker-trait associations (MTAs) for seed traits on four linkage groups i.e. LG01, LG02, LG04 and LG05. Phenotypic variations (PVs) explained by these QTL ranged from 4.4 (WU) to 19.91% (EC). These genomic regions contributing significantly towards observed variability of seed traits would serve as potential candidates for future research that aims to improve seed traits in pigeonpea

    Breeding Progress and Future Challenges: Abiotic Stresses

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    Mungbean is a short-season tropical grain legume grown on some six million hectares each year. Though predominantly a crop of smallholder farmers and subsistence agriculture mungbean is increasingly seen as a high value crop for international markets with broad acre production under modern farming systems established in Australia, South America, West Asia and Africa. Key benefits of mungbean are its nutritional and monetary value. It provides a short duration, flexible disease break when fit into intensive wheat, rice and summer cereal rotations and its self-sufficiency for nitrogen. The short growing season of 55–100 days places a ceiling on productivity which is further impacted by the traditional low-input farming systems where mungbean is most frequently produced; global yield averages are 0.5 tonnes per hectare though 3 tonnes per hectare is considered achievable under favourable conditions. Increased reliability of mungbean in subsistence systems has been achieved by developing shorter duration, more determinate ideotypes and by the manipulation of sowing time. The strategy of reducing exposure to risk was very successful in transforming mungbean rather than identifying and breeding inherent resilience. The major abiotic stresses of mungbean presented here are drought, heat, waterlogging, low temperatures and salinity. Sources of tolerance identified for all of these stresses have been identified in the germplasm collections of cultivated mungbean as well as wild relatives. Future research efforts must combine known sources of genetic variation with the investigation into the biochemical and physiological processes in order to understand and breed for tolerance to abiotic stress in mungbean

    Data_Sheet_1_Multi-location evaluation of mungbean (Vigna radiata L.) in Indian climates: Ecophenological dynamics, yield relation, and characterization of locations.doc

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    Crop yield varies considerably within agroecology depending on the genetic potential of crop cultivars and various edaphic and climatic variables. Understanding site-specific changes in crop yield and genotype × environment interaction are crucial and needs exceptional consideration in strategic breeding programs. Further, genotypic response to diverse agro-ecologies offers identification of strategic locations for evaluating traits of interest to strengthen and accelerate the national variety release program. In this study, multi-location field trial data have been used to investigate the impact of environmental conditions on crop phenological dynamics and their influence on the yield of mungbean in different agroecological regions of the Indian subcontinent. The present attempt is also intended to identify the strategic location(s) favoring higher yield and distinctiveness within mungbean genotypes. In the field trial, a total of 34 different mungbean genotypes were grown in 39 locations covering the north hill zone (n = 4), northeastern plain zone (n = 6), northwestern plain zone (n = 7), central zone (n = 11) and south zone (n = 11). The results revealed that the effect of the environment was prominent on both the phenological dynamics and productivity of the mungbean. Noticeable variations (expressed as coefficient of variation) were observed for the parameters of days to 50% flowering (13%), days to maturity (12%), reproductive period (21%), grain yield (33%), and 1000-grain weight (14%) across the environments. The genotype, environment, and genotype × environment accounted for 3.0, 54.2, and 29.7% of the total variation in mungbean yield, respectively (p 0.05) for all the genotypes except PM 14-11. Results revealed that the south zone environment initiated early flowering and an extended reproductive period, thus sustaining yield with good seed size. While in low rainfall areas viz., Sriganganagar, New Delhi, Durgapura, and Sagar, the yield was comparatively low irrespective of genotypes. Correlation results and PCA indicated that rainfall during the crop season and relative humidity significantly and positively influenced grain yield. Hence, the present study suggests that the yield potential of mungbean is independent of crop phenological dynamics; rather, climatic variables like rainfall and relative humidity have considerable influence on yield. Further, HA-GGE biplot analysis identified Sagar, New Delhi, Sriganganagar, Durgapura, Warangal, Srinagar, Kanpur, and Mohanpur as the ideal testing environments, which demonstrated high efficiency in the selection of new genotypes with wider adaptability.</p
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