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ThesisItem Open Access Variable selection for classification and discrimination of Indian Mustard (Brassica juncea) genotypes for yield and oil content(CCSHAU, Hisar, 2019-07-10) Godara, Poonam; Hooda, BKThe present study deals with the problem of variable selection for classification and discrimination of Indian Mustard (Brassica juncea) genotypes for yield and oil content. The study used secondary data on 310 Indian mustard genotypes obtained from Oilseeds section of the department of Genetics and Plant Breeding, CCS HAU, Hisar. The experiment was conducted during rabi season of 2015-16. Five variable selection methods (Univariate Two-Sample t-test, Rao´s F test for Additional Information, STEPDISC Procedure (backward and forward) using Wilk´s Lambda criterion and Random Forests Algorithm) for classification and discrimination were compared using Monte Carlo simulation. Performance of the methods was assessed in terms of leave one out cross validation error for classification. Comparing the performance of various methods affecting seed yield for samples of equal sizes in scheme I, Rao's F test, Wilkˊs lambda (Backward) and Wilkˊs lambda (Forward) were found better than others. In scheme II, the most suitable methods affecting oil content with least leave one out cross validation error rate were Wilkˊs lambda (Backward) and Wilkˊs lambda (Forward). Based on results of the scheme I and II, Wilk´s Lambda (backward and forward) were found most suitable method for classification affecting the seed yield and oil content significantly. In scheme I using leave one out cross validation error rate four important variables for discrimination affecting the seed yield per plants were secondary branches, primary branches, days to maturity and siliqua number on main shoot with least error of rate of 21.72 per cent. The important variables for discrimination which significantly affected the oil content were siliqua length, Secondary branches, primary branches and days to maturity with least error rate of 33.90 per cent. Secondary branches, siliqua number on main shoot, seeds per siliqua and 1000 seed weight were found to be important variables in scheme III with least error rate of 27.68 per cent. Three characters which discriminate the groups having low seed yield and high seed yield were 1000 seed weight, siliqua length and seeds per siliqua, while siliqua length 1000 seed weight and primary branches were found the most discriminating variables affecting oil content. Using the correlation between variables and discriminant score, the most important variables affecting the seed yield were secondary branches, primary branches and days to maturity. The three most important variables discriminating between oil content were siliqua length, secondary branches and seeds per siliqua. Most important variables discriminating between low seed yield with low oil content and high seed yield with high oil content groups were secondary branches, primary branches and siliqua number of main shoot. The variable, number of secondary branches have been found to be the most important for classification and discrimination of Indian mustard genotypes for seed yield and oil content.ThesisItem Open Access Multidimensional analysis of poverty in Haryana: A fuzzy set approach(CCSHAU, 2018) Tanwar, Nitin; Hooda, B.K.The present investigation was carried out to measure aspect based multidimensional poverty in Haryana. The necessary data for the study was obtained from the consumer expenditure survey (68th round conducted in 2011-12 and 69th round conducted in 2012) of NSSO on drinking water, sanitation, hygiene and housing conditions. The Multidimensional Poverty Index (MPI) suggested by Alkire & Foster (2011) using the dual cut-off method based on the counting approach has been applied for poverty estimation in rural and urban areas of Haryana. The Totally Fuzzy and Relative Approach due to Costa and Angelis (2008) have been used to measure multidimensional poverty in Haryana. Univariate techniques for poverty measurement such as Head Count Ratio (HCR), Income Gap Ratio (IGR) and Poverty Gap Ratio (PGR) based on monetary data have also been used to estimate the proportion of deprived households at district levels in Haryana. The HCR indicated that the districts of Mewat and Fatehabad have maximum proportion of the poor households in rural Haryana while, the districts of Mewat and Yamuna Nagar have the maximum proportion of poor households in urban Haryana. The districts of Jhajjar, Gurgaon, Sonipat and Karnal have the minimum proportion of the poor households in rural Haryana while the districts of Hisar, Fatehabad and Gurgaon have the minimum proportion of poor households in urban Haryana. The maximum PGR has been observed in the districts of Fatehabad, Yamuna Nagar and Mewat in rural Haryana while the urban households in the districts of Mewat and Yamuna Nagar have the maximum poverty gap ratio. The fuzzy MPI based on the aspects of drinking water facilities, sanitation facilities and housing conditions for Haryana indicated that 33.28% households in overall Haryana are multidimensionally poor with 36.64% households in rural and 30.46% in urban Haryana. The decomposition of the households by social groups indicated that there is not much difference in multidimensional poverty index values among households related to schedule castes (SC), other backward classes (OBC) and others. The index values varied from 30.49 to 34.24 per cent among the social groups. Using the Alkire-Foster aspect based MPI, it was observed that the rural households in the districts of Mewat, Panipat, Mahendragarh, Rohtak, Gurgaon and Palwal have high MPI values indicating high level of poverty or deprivedness in these districts. Similarly the households in urban areas of the districts of Mewat, Panipat, Jhajjar, Rohtak and Mahendragarh were found multidimensionally poor as indicated by high MPI values.ThesisItem Open Access On Construction and Analysis of Bio-assay Designs(College of Basic Sciences and Humanities Chaudhary Charan Singh Haryana Agricultural University Hisar, 1984) Rai, Lajpat; Puri, P. D.ThesisItem Open Access Regression Method with Dummy Variables in Linear Models for Unbalanced Data(College of Basic Sciences and Humanities Chaudhary Charan Singh Haryana Agricultural University Hisar, 1983) Goswami, Ram Prasad; Singh, UmedThesisItem Open Access Farmers Perceptin abut the Coverage and the Utility of Agricultural News in Leading Tamil Dailies(College of Agriculture Chaudhary Charan Singh Haryana Agricultural University Hisar, 1981) Hermina, J. Queeni; Varma, N. SThesisItem Open Access Some contributions to model selection strategies in regression analysis(Department of Mathematics And Statistics College of Basic Sciences and Humanities Punjab Agricultural University, 2000) Sharma, Saroj Kumari; Cheema, H. SThesisItem Open Access A Study on Improvement of Genetic Gains through Restricted Selection Index(College Of Basic Sciences And Humanities Chaudhary Charan Singh Haryana Agricultural University Hisar, 2000) Chander, Subhash; Jaiswal, U. SThesisItem Open Access Studies on Sludge Granulation in a Uasb Reactor Treating Distillery Effluent(College of Agriculture Chaudhary Charan Singh Haryana Agricultural University Hisar, 1995) Sharma, Jitender; Singh, RajendraThesisItem Open Access Estimation of Parameters in Econometric Models From Grouped Data With Grou Errors are Correlated(College of Basic Sciences and Humanities Chaudhary Charan Singh Haryana Agricultural University Hisar, 1997) Grover, Deepak K.; Kaushik, L. S