Thumbnail Image

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.

Browse

2011 - 20202
Reset filters
Subject: Genetics and Plant Breeding × Author: Pawan Kumar × Start date: 1993 × Thesis Type: Ph.D ×
Reset filters

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    ThesisItemOpen Access
    Population Structure Analysis and Genetic Diversity Studies for Yield Contributing Traits in Upland Cotton (Gossypium hirsutum L.)
    (CCSHAU, Hisar, 2020-11) Pawan Kumar; Somveer
    The present study was undertaken with the objectives i) investigate the phenotypic and genetic diversity of promising genotypes of G. hirsutum and ii) to estimate the population structure, linkage disequilibrium (LD) using SSR markers. The experimental material comprised of 190 genotypes of upland cotton out of which 96 genotypes were used for population structure and further analysis. The test enteries were evaluated for various quantitative traits under three environments (early, normal and late sown conditions) during kharif-2018 and kharif-2019. Among the qualitative characters studied leaf color, leaf hairiness, leaf appearance, plant stem hairiness, plant height, flower petal color, flower stigma position, flower pollen color, boll shape, boll prominence of tip, and boll opening proved to be useful and stable diagnostic characters which proved useful in the classification of test genotypes. Analysis of variance revealed significant differences among the genotypes for all traits under investigation. Highly significant positive association of seed cotton yield per plant with number of bolls per plant, boll weight, lint yield per plant, and seed index was recorded. All 96 genotypes were grouped into two clusters by population structure and analysis of molecular variance showed that most of the variation was among the genotypes as compare to among the sub-population. A total of 46, 48 and 46 significant marker-trait associations were identified in early, normal and late sown plantings, respectively. Out of these 21, 19 and 21 significant marker-trait associations were novel in early, normal and late sown environment, respectively.
  • Thumbnail Image
    ThesisItemOpen Access
    Genetic analysis of spike morphology and grain yield component traits in Triticum aestivum L. em Thell
    (CCSHAU, 2011) Pawan Kumar; Yadav, Ramesh Kumar
    The present investigation comprising six generation (Parents, F1, F2, BC1 and BC2) of five crosses wheat viz. HJP81 x Rm-Ts17, HS27 x PBW502, HJP81 x PBW502, HS67 x PBW502, HG2 x HD2009M was conducted for estimating the gene effects for the spike morphology and yield component traits under two successive growing seasons (2008-09 and 2009-10) for fifteen spike morphological and yield component traits at the experimental area of the Department of Genetics & Plant Breeding, CCS Haryana Agricultural University, Hisar, India. Generation mean analysis revealed significant differences for all traits where the A, B, C and D individual scales were also significant for most of the characters indicating thereby the presence of non-allelic interactions. In some of the cases, the non-significance of chi-square value indicated the fitness for additive-dominance model. Additive component was significant for most of the characters and even as preponderant in magnitude over the dominance component. Either all or any of the three types of epistatic interactions (i, j and 1) were significant for most of the cases and generally it is the “i" type of interaction which is more frequently prevailing for most of the traits studied over the crosses. However, the magnitude and direction of estimates changed for the cross and the seasons. Additive x additive type of interaction with overdominance was recorded for peduncle length in cross-II, where the chance of transgressive segregates was high. Duplicate type of interaction was apparent for plant height, peduncle length, spike length, spike compactness, spike biomass, 100 kernel weight, grain: spike biomass ratio and grain yield per plant. Complementary type of interaction was recorded for peduncle length, spike biomass, 100 kernel weights and days to heading. Significant heterosis was observed for plant height, peduncle length, spike length, grain: spike biomass ratio, grain yield per plant and days to heading. The magnitude and direction of heterosis was varying from cross to cross over both seasons, however, the inbreeding depression was also indicated as positive and significant in most cases. The potence ratio in F1 and F2 depicted the partial and over dominance was shown by all the traits under study. Genetic variability was estimated by GCV and PCV indicated maximum diversity for the cross-I followed by cross-IV, II, III and V. The genetic similarity coefficient analysis showed that extensive genetic diversity (from 26% to 93%) was present among parental genotypes. In cross-HJP81 x Rm-Ts17 the dendrogram constructed and clustered in six major groups. The hierarchical cluster analysis for cross-IV revealed that the F2 populations along with their parents were mainly divided into two major clusters and eight subgroups. Similar finding were revealed by PCA analysis. The F2 population SSR maker data for C-I and C-IV were subjected for the QTL analysis by WinQTL-Cartographer. Five QTL were detected for spike biomass at map positions, 88.1 (1A), 33.2(1B), 111.7(2D), 46.6(5A) and 97.8(5A) by SSR marker BARC263, BARC187, WMC601, XGWM443 and WMC475 respectively. Four QTL were detected for kernel weight per spike at map positions, 100.8 (1A), 45.9 (1B), 45.1 (5A), 103.0 (5A) by SSR marker WMC254, WMC416, XGWM443 and WMC110. These QTLs may be used for further improvement of the traits they represent.