Bayesian Analysis of Rice Productivity Data

Crop yield forecasting is an important aspect for a developing economy of a country so that adequate planning exercise is undertaken for sustainable growth and overall development of the country. Weather fluctuations affect crop yield significantly during different stages of crop growing season. The present book is the outcome of the research work carried out by the authoress during P.G. studies under the guidance of the co-author. The objective was to develop linear or/and non-linear models for forecasting the yield of rice on the basis of 19 years rice productivity data and six weather characteristics viz. temperature, rainfall, humidity, sunshine, wind velocity and evaporation. Bayesian analysis of the models is also performed. The findings of the study reveal that both the methods yield satisfactory results with a very high value of coefficient of prediction (almost 99%). The abovesaid models are applicable for estimating rice yield in the region of study and are not universally true, as the weather conditions may change from one region to another and may affect the yield of rice differently in different regions.