Dissection of weather parameters for forecasting oilseed crops yield

Most of the agricultural crops are sensitive to weather, particularly under Indian condition where monsoon play a key role in farming. Dissection of role of important weather parameters have become necessarily in the age when the effect of climate change has been expressing not only by the plants but also by the animals and human being. In the present paper we used multiple linear regressions, which is a simple linear regression analyses that is used to analyze the relationship between single response variable (rapeseed and mustered yield as a Dependent variable) with two or more controlled variables (minimum temperature, maximum temperature, rainfall as the independent variables). In this paper, stepwise multiple regressions have been used because this method is combination of forward selection and backward elimination method. The main objective of this paper is to select the suitable controlled variables to forecast the yields of oilseed crops(rapeseed and mustered)from 1958 to 2014 in India. The data about the yield was collected from handbook of statistics on the Indian economy(http://dbie.rbi.org.in) and for weather data of India from website www.gov.data.in, and data has been analyzed using SPSS 20.0.