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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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ThesisItem Open Access Prediction of milk production using penalized regression techniques in cattle(CCSHAU, 2013) Hemant Kumar; Hooda, B.K.Multiple linear regression models (MLR) have been widely used in dairy sciences to predict lifetime milk production in cattle on the basis of lactation traits. MLR often gives unsatisfactory results in the presences of high multicollinearity among the explanatory variables. Choice of functional form and selection of xplanatory variables is also important for getting a parsimonious and useful model for explaining any phenomenon. In the presence of multicollinearity and model mis-specification ordinary least square estimators of regression parameters generally have low bias and large variances resulting poor predictive performance. Keeping in view the presence of multicollinearity in mind shrinkage and penalized regression techniques have been used along with the artificial neural network for prediction of lifetime milk production on the basis of lactation traits. In the present study lactation traits such as previous lactation yield, age at first calving, lactation length, calving interval, service period, and dry period have been used for prediction of lifetime milk yield in crossbred cattle data. The lifetime milk production has been defined as total amount of milk produced by cattle from initiation of first lactation till the completion of third lactation. Small eigen values of correlation matrix of predictor variables, high value of variance inflation factor and higher condition index indicated presence of multicollinearity in crossbred cattle data. Consequently biased and penalized regression models have been adopted to take care of multicollinearity among the predictors. In addition to ridge regression the relatively recent techniques of penalized regression called LASSO and elastic net given by Tibshirani (1996) and Zou and Hastie (2005) respectively were also applied for developing prediction model for lifetime milk production and selection of principal lactation traits. On the basis of AIC and BIC values LASSO and elastic net outperformed the ridge regression and elastic net techniques was found most satisfactory. Forward selection, backward elimination, LASSO and elastic net were used for selection of best subset of lactation traits for prediction of lifetime milk production. It was observed that seven variables out of eleven were selected by LASSO and six by elastic net using optimal value of regularization parameters. The optimum value of regularization parameters was computed using 10- fold cross validation. The number of traits in best subset was found to six for backward elimination and four for forward selection method. On the basis of adjusted R2, AIC and BIC values and simplicity of the model it was concluded that subset selected by LASSO techniques having just two significant traits was best. Evaluation of predicting performance of multiple regression, ridge regression, LASSO, elastic net and ANNs models has been done by dividing the sample under study into two sets, by taking 90% observations in training set and 10% observations on test set. Coefficient of determination, root mean square error, mean absolute error, mean absolute percentage error and Theil’s U-statistics were computed for the test set, and based on these performance measures elastic net was found most satisfactory techniques for prediction of lifetime milk yield using lactation traits in crossbred cattle.ThesisItem Open Access Structural Equation Modeling With Latent Variables For Assessment Of Regional Development In Haryana(College Of Basic Sciences And Humanities Chaudhary Charan Singh haryana Agricultural University : Hisar, 2010) Sheoran,Parkash.Om.; Rai,Lajpat.ThesisItem Open Access A study on two-sex parity dependent population growth model(CCSHAU, 2011) Rout, Manoj Kumar; Gupta, S.C.The classical model of Lewis and Leslie (1945, 1948) has been extensively used for the study of population growth in various fields. However, complex growth structures require the use of more general models. The model of Kapur (1979) allows harvesting in the system, is an initial step to move in this direction. However, the need is being felt to develop more general models considering the effect of harvesting on the reproductive structure of living organisms. In the present work, a two-sex parity dependent population growth model is proposed where birth, death and harvest rates of males and females are the functions of two parity groups viz. zero parity and non-zero parity. The conditions for growth, extinction and stability of the population have also been derived. The model has been applied on the crossbred cattle population by taking 11 years data (2000-2010) collected from Department of Animal breeding, CCS HAU, Hisar. The sex-wise projected cattle population in two parity groups have also been found and the validity of model has been tested by applying chi-square for goodness of fit and found that the model fits well. A uniform harvesting strategy have also been derived for stable population structure. Observed and projected cattle population structure for males and females of two parity groups under different harvesting situations have also been shown by tables and graphs.ThesisItem Open Access Co-integration approach for estimation of supply response of major crops in Haryana(CCSHAU, 2011) Vikas; Manocha, VeenaThe present study is an attempt to estimate the acreage and yield response functions for major crops in Haryana within the framework of co integration and error correction model and to compare the short-run and long-run supply elasticities of major crops. The long-run acreage response to lagged price was positive and significant in the case of rice, rapeseed-mustard and sugarcane with elasticity values 0.19, 0.22 and 0.29, respectively. In case of other crops except bajra and gram, very low positive but non significant price elasticities have been observed. In the short-run, lagged price elasticities were found to be positive for all the crops. However, the positive significant values have been observed in case of rapeseed-mustard, sugarcane and bajra. The long-run acreage response to lagged year yield was found to be positive and significant in case of rice, wheat and cotton (Am.) with elasticity values 0.26, 0.18 and 0.29, respectively,. Irrigation elasticity has been observed to be positive for all the crops in the long-run, while it is positive for all the crops except gram and rapeseed-mustard in the short-run. However, only wheat and sugarcane are found to be positively and significantly responsive to irrigation in the long-run as well as short-run. The long- run yield response to price has been observed to be very low and non-significant in case of all the crops except wheat, rapeseed-mustard and sugarcane. The yield response to irrigation has been observed to be positive and significant in case of wheat, rapeseedmustard and cotton (Am.) only.