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A genetic algorithm approach to maximize crop yields and sustain soil fertility

In order to increase crop production both for now and in future, conscious efforts need to be made towards sustaining soil fertility. One of the challenges facing farmers is how to increase crop yield and sustain soil fertility. Due to the multidimensional aspect of the challenge and, as a consequence, the huge set of potential solutions, field experiments are not well-suited for their choice and assessment. The objective of this study is to formulate, simulate and evaluate a genetic algorithm based model to maximize crop yields and sustain soil fertility. This study develops a nonlinear mixed-integer programming model to solve the maximization of crop yield problem with sustaining soil fertility. As it is an NP-hard problem, a genetic algorithms approach is proposed to determine the crop yield maximization while sustaining soil fertility. The soil fertility depends on several interrelated factors which have their respective determinants. Numerical analysis shows the effectiveness of the proposed method to deal with such a kind of complicated problem. The study identifies bio-physical, technical (including managerial) factors influencing soil fertility in the course of crop production. The regression result equally shows that for every hundred percent change in soil fertility, holding other factors constant, there is a substantial change in the crop yield. The findings of this study revealed that it is possible to scientifically appropriate all factors on sustainable basis (physical – such as soil nutrients, technical and managerial) with maximum crop yield achieved. On the basis of the findings, it is recommended that in order to have optimal utilization of resources on sustainable level, conscious efforts should be made by agricultural extension experts to ensure that farmers adopt management practices required for maximum yield.