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Chaudhary Charan Singh Haryana Agricultural University, Hisar

Chaudhary Charan Singh Haryana Agricultural University popularly known as HAU, is one of Asia's biggest agricultural universities, located at Hisar in the Indian state of Haryana. It is named after India's seventh Prime Minister, Chaudhary Charan Singh. It is a leader in agricultural research in India and contributed significantly to Green Revolution and White Revolution in India in the 1960s and 70s. It has a very large campus and has several research centres throughout the state. It won the Indian Council of Agricultural Research's Award for the Best Institute in 1997. HAU was initially a campus of Punjab Agricultural University, Ludhiana. After the formation of Haryana in 1966, it became an autonomous institution on February 2, 1970 through a Presidential Ordinance, later ratified as Haryana and Punjab Agricultural Universities Act, 1970, passed by the Lok Sabha on March 29, 1970. A. L. Fletcher, the first Vice-Chancellor of the university, was instrumental in its initial growth.

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2013 - 20172
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Subject: Genetics and Plant Breeding × Author: Neeru × End date: 2018 ×
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    ThesisItemOpen Access
    Genetic diversity analysis for heat tolerance in wheat [Triticum aestivum L. em. Thell]
    (CCSHAU, 2017) Neeru; Panwar, I.S.
    The present investigation entitled Genetic Diversity Analysis for Heat Tolerance in Wheat (Triticum aestivum L. em. Thell)” was conducted on 592 accessions of wheat during 2014-15 at IIWBR, Karnal and on sixty genotypes of wheat during 2016-17 to evaluate genetic variability, character association and genetic divergence for the identification of most diverse and promising genotypes. Observations were recorded on various morphological and physiological characters. A considerable amount of genetic variability was observed among all the genotypes for all the characters under study. From principal component analysis (PCA) the first six components account for more than 65% of the total variance among the germplasm were found. Grain yield per meter and effective tillers per meter showed moderate value of PCV and GCV under both timely and late sown condition. Above mentioned traits also showed high heritability coupled with high genetic advance. Grain yield showed positive and significant correlation with effective tillers per meter, canopy temperature under timely sown and with days to anthesis, plant height, effective tillers per meter, canopy temperature and grain weight under late sown condition. Path analysis revealed that effective tillers per meter had highest positive direct effect on grain yield followed by days to anthesis, grain weight, canopy temperature and chlorophyll fluorescence under both the conditions. D2 analysis grouped 60 genotypes into7 clusters for both timely and late sown conditions. Cluster IV and VII under timely cluster I and VI under late sown condition exhibited maximum inter cluster distance. Therefore, genotypes in these clusters may be used to produce the superior progenies and transgressive segregants. The NTSYS-PC UPGMA cluster tree as well as two and three dimensional PCA analysis led to the grouping of 30 genotypes into two groups at similarity index of 0.67. The group I was very large and include 29 genotypes while group II includes only one genotype (ATLAS 66) which indicates that this genotype was highly diverged with respect to other genotypes.
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    ThesisItemOpen Access
    Characterisation and Classification of Indian mustard [(Brassica juncea (L.) Czern & Coss.)] genotypes using multivariate analysis
    (CCSHAU, 2013) Neeru; Thakral, N.K.
    The present study was conducted on 60 Indian mustard genotypes which was grown during rabi 2011-2012 to evaluate, categorize and classify them and for computation of principal components to determine the relative importance of principal components and characters involved in them. Observations were recorded on 16 quantitative and 9 qualitative traits involving seed yield, its attributes and oil content. All the genotypes were characterized for 25 agro-morphological characters ranging from seedling emergence to crop maturity. A considerable level of variability was noticed for a number of agro-morphological traits. Results revealed that maximum variation was found among genotypes on the basis of seed yield in which seven genotypes were grouped into low, thirty two genotypes in medium and twenty one genotypes in high seed yield/ plant category whereas, oil content varied from low (40 genotypes) and medium (20 genotypes) category. In case of 1000-seed weight, twelve genotypes had very low, thirty eight genotypes had medium and remaining ten genotypes had high 1000-seed weight. Thirty three genotypes were having few numbers of seeds/ siliqua whereas, intermediate number of seeds/ siliqua was recorded in twenty seven genotypes. On the basis of siliqua density on main shoot, fifty two genotypes were grouped into medium, six in high and two in low siliqua density category. Classification of genotypes on the basis of DUS traits provided identification of key characteristics of various genotypes. Hierarchical cluster analysis classified the genotypes into ten clusters containing one to twenty three genotypes. The cluster III and IV showed superiority for seed yield/ plant due to possessing of more number of siliquae/ plant. To know the relative importance and usefulness of variables and genotypes, principal component analysis was done which explained 75.26% variability through eleven principal components having eigen value more than one. Data were further analyzed using principal factor analysis to offset the limitations of principal component analysis. All the variables exhibited high loadings on different factors in such a manner that they could be designated as growth rate factor, leafiness factor, yield factor and color factor etc. depending upon the type of variables loaded on a particular factor. Genotypes JMM-937, RC-199, RH-0401(YS), Pusa bold, Pusa bahar and KM-888 were found to be better performers on the basis of principal factor scores with regard to seed yield and its components when all the principal factors were considered simultaneously.