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ThesisItem Open Access Impact of climate change on productivity of wheat and cotton in south west Punjab(Punjab Agricultural University, Ludhiana, 2020) Ramandeep Kaur; Gill, K.K.The study entitled "Impact of climate change on productivity of wheat and cotton in south west Punjab" was conducted to assess the shift, variation and deviation in climate of Punjab during 37 year (1981-2017) in Bathinda and 17 years (2001-2017) in Faridkot using correlation regression techniques and estimating the possible effects of climate and technology on the productivity of cotton (Gossypium spp.) and wheat (Triticum aestivum L.) crops. Three different statistical models i.e. Basic Model (Model 1), Modified Model (Model 2) and SPSS Software (Model 3) were used. The results showed that in case of maximum temperature at Bathinda, more variation has been found in fourth decade as compared to others and at Faridkot the variation was observed more during second pentad. More variation in minimum temperature has been found in fourth decade and third pentad at Bathinda and Faridkot, respectively. In case of rainfall at Bathinda, more variation has been found in fourth decade as compared to others. At Faridkot, the variation was more during second pentad. GStat was used for the development of multiple regression equation and correlation was developed for the sensitive crop periods in model I or basic model. The basic model is then modified through inclusion of an assumed composite index while other independent variables are kept constant. SPSS software was used as a model for wheat and cotton for forecast analysis. The use of basic model (model 1) has shown that the maximum temperature during 2nd and 3rd weeks of wheat growing season had negative effect on wheat yield at Bathinda district. At Faridkot, minimum temperature during 2nd week showed negative effect on wheat yield. The three models (i.e. basic model, modified model and SPSS software) predicted wheat and cotton yield and the error per cent of all these models was remained 30 per cent for two districts (Faridkot and Bathinda) of south west Punjab. For American cotton and desi cotton grown in Bathinda and Faridkot districts, SPSS software (model 3) was best fit as R2 value was highest for American cotton by 83 % ( Bathinda district) and 97% (Faridkot district), whereas, for desi cotton it was 82 % and 96 % for Bathinda and Faridkot district, respectively. For wheat grown in Bathinda, SPSS software was best fit as R2 value was 97 % while wheat grown in Faridkot, modified model (model 2) was best fit (95 %).
