Yield prediction of rice using weather based statistical model in Bilaspur District of Chhattisgarh (2019)

Abstract

Weather and climatic condition plays on important role for growing the crops. Weather affect the crop growth at different phenological phase and thus responsible for variation in yields from year to year and place to place. These differences in weather and climatic conditions at different areas, regions and states helps us to select or grow the suitable crops according to that area so, that the formers can achieve maximum yield and profit. A research has been made in this paper to study the effect of vital weather parameters on rice yield and to develop a multivariate statistical model for yield forecast of Bilaspur district of Chhattisgarh. On the basis of 18 years (2000-2017) weather and rice production data 7 models have been developed using SPSS software. Result revealed that model 7 has the highest R2 value 0.99, which describes the 99% variability in rice yield due to weather parameters i.e. Bright Sunshine Hours of 12th Week after Sowing, Minimum Relative Humidity of 4th Week after Sowing, Bright Sunshine Hours of 10th Week after Sowing, Minimum Temperature of 9th Week after Sowing, Maximum Relative Humidity of 1th Week after Sowing, Maximum Temperature of 10th Week after Sowing and Rainfall of 11th Week after Sowing. This may be due to more weather factors involved in the Model 7, instead of any other models.