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Agriculture University, Jodhpur

Agriculture University, Jodhpur was established on 14th September, 2013 by Government of Rajasthan under Agriculture University, Jodhpur Act 21 of 2013 to focus on holistic development of arid and semi-arid regions of the state covering 6 districts (Jodhpur, Barmer, Nagaur, Pali, Jalore and Sirohi), constituting 28% of total geographical area which is sustaining 20.8% human and 28.4% animal population of the state. The districts under jurisdiction of the university cover 3 agro-ecological zones of the state. These are Arid Western Plain Zone Ia (Jodhpur and Barmer districts), Transitional plain of Luni Basin Zone IIb (Jalore, Pali, and Sirohi districts) and part of Transitional Plain of Inland Drainage Zone IIa (Nagaur district). The university has 1 institute of diploma and 3 colleges to produce highly competent educated human resources in agriculture and allied sciences besides 2 agricultural research stations, one each in zone Ia & IIb and 3 agricultural research sub stations, one in each zone to prepare, plan and perform highly need based research in this acute water scarce but naturally rich bio-diversified zone of the country. The third most important part in tri-pillar (Teaching, Research & Extension) of agricultural development, the extension for transfer of technologies are reached to doorsteps of the farming community by 6 Krishi Vigyan Kendras (K-V-Ks), 2 in Nagaur district and 1 each in Jodhpur, Barmer, Jalore & Sirohi districts under the umbrella of the university. The different units of teaching, research and extension are coordinating to systematically run by the headquarter situated at Mandor, Jodhpur.

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20211
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Subject: Genetics and Plant Breeding × Author: Bairwa, Ujala ×
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    ThesisItemOpen Access
    Genetic Variability, Correlation and Path Analysis in Finger Millet [Eleusine coracana (L.) Gaertn]
    (Agriculture University, Jodhpur, 2021-09-25) Bairwa, Ujala; Choudhary, B.R.; Kumhar, S.R.; Shukla, U.N.
    An experiment entitled “Genetic Variability, Correlation and Path analysis in Finger millet [Eleusine corocana (L.) Gaertn]” was conducted with 35 genotypes in Kharif 2020 at Research Farm of Agricultural Research Station, Mandor, Jodhpur (Rajasthan). The experiment was laid out in RandomizedBlock Design (RBD) with three replications to estimate the extent of genetic variability, heritability, genetic advance, correlation coefficient, path coefficient analysis and genetic divergence among all the genotypes. The analysis of variance exhibited significant difference among the genotypes for all the characters under study indicating the presence of substantial degree of variability. The phenotypic coefficient of variance (PCV) was higher than genotypic coefficient of variance (GCV) for all the traits under study, indicating influence of environment on expression of such traits. The highest value of PCV and GCV was observed for iron content and the lowest for days to 50% flowering. All the traits showed high heritability except number of fingers per ear, number of effective tillers per plant and biological yield per plant. High heritability coupled with high genetic advance as percent of mean were recorded for iron content, test weight, calcium content, finger length, protein content, flag leaf area and days to maturity hence these characters are most likely to be governed by additive gene action and selection for these characters will be very effective. Correlation studies among the characters revealed that grain yield per plant has a strong positive and significant association with characters like flag leaf area, finger length, test weight, biological yield per plant and harvest index at phenotypic and genotypic levels depicting that these are important yield contributing traits. Path coefficient analysis of various quantitative traits indicated that flag leaf area, test weight, biological yield per plant, harvest index and iron content had the maximum positive direct effect on grain yield per plant. Based on the relative magnitude of D2 values, Tochers’s method resulted in formation of seven clusters. Out of seven clusters, cluster I was the largest comprising of fifteen genotypes followed by cluster II with twelve genotypes and cluster III with four genotypes, clusters IV, V, VI and VII were monogenotypic suggested the existence of high degree of heterogeneity among the genotypes. The traits test weight contributed maximum towards genetic divergence. The highest intra cluster distance was recorded in cluster III and cluster II while maximum inter cluster distance was recorded between cluster III and cluster VII followed by cluster I and cluster VII indicated that superior recombinants can be achieved by mating between the lines of the clusters