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ThesisItem Open Access Modelling and prediction of sweet corn (Zea mays L.) yield at district level under Tarai region of Uttarakhand(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2019-07) Bijlwan, Amit; Ravi KiranThe present study was conducted at the Norman E. Borlaug Crop Research Centre of G. B. Pant University of Agriculture and Technology, Pantnagar to analyze effect of different type of mulching on productivity of maize yield and prediction of maize yield at district level in Tarai region of Uttarakhand during 2018. The experiment was laid out in 2 factor randomized block design with three date of sowing and four type of mulching for hybrid maize cultivar (Maize Sugar 75). During crop growth period all recommended cultural practices were followed. The various ancillary observations on the growth were periodically recorded along with post-harvest studies to evaluate the treatment effects. Experimental analysis suggests that maize sugar 75 perform better when sown on 11th July as compared to 23rd July and 21st August. Green cob yield and grain yield of Maize sugar 75 was better when sowing was done on 11th July. Crop growth parameter such as plant height, leaf area index, and dry matter accumulation was higher under plastic film mulch. Under the mulching treatment, there was no significant effect on green cob yield but grain yield under plastic film mulch treatment was lower than the dhaincha mulch. The performance of the model CERES-Maize was satisfactory for all sowing dates during the period of study for germination, anthesis, silking and grain yield. The prediction of model was found good when compared with actual observation in case of anthesis where value of R2 was 0.71. The model output was also good for silking and grain yield, there was good relationship between observed and crop simulation model value and R2 was 0.66 and 0.88 for silking and grain yield respectively. Maize has adopted diverse set of climatic conditions therefore, it is grown from the plains land of Uttar Pradesh to lower hills of Uttarakhand. However, due to interannual variability in weather conditions, the large amount of year-to-year variability in productivity and production of maize is observed. Therefore, there is a need to develop a system for timely and accurate estimation/prediction of productivity and production of maize for Udam Singh Nagar district. Considering yield variability and importance of maize for farmer, an attempt has been made to develop an approach for large (district level) area yield estimation. The approach included i) calibration of crop simulation model CERESMaize on experimental data set, ii) use of CERES-Maize simulation model on district level for simulating response of maize crop to ambient environment conditions, iii) computation of year-to-year deviations in observed yields and simulation yield, iv) estimation of technological trend yields at district level and, v) incorporation of predicted deviation into trend yields for predicting district level maize yield . The district level maize yield prediction for a period of 10 years (2006 -07 to 2015- 16) shows quit good agreement between observed maize yield and predicted yield with RMSE of 298.98 kg and R2 0.51.