Forecasting the optimal yielding period and profitability of maize cropping system using genetic algorithm

S.K. Rajesh Kanna, A.D. Jaisre

Abstract

Due to green revolution, many researches have been carried out in the field of agriculture to forecast the optimal crop that will yield maximum profitability. The profitability can be improved by controlling the predictable and unpredictable variables involved in yielding. As many strategies are available to control the predictable variables, a need arises to forecast the unpredictable variables. In this research, the unpredictable variables have been successfully forecasted for cropping productivity using genetic algorithm. The major variables considered for maize cropping system in this research are rainfall, temperature and irrigation. The details of the rainfall, temperature and irrigation for twelve months and for eight years have been collected and given as input to the Minitab software to generate the mathematical equation. This mathematical equation has been used as the fitness function equation for genetic algorithm. Thus the genetic algorithm can generate the best optimal yielding period for maize crop cultivation and also it can be used to forecast the best optimal combination of variables that can yield best productivity. This model has helped farmers to make efficient resource allocation decisions with the aim of forecasting productivity and profitability of maize cropping system.