A STUDY ON THE SELECTION OF AGRICULTURAL ADAPTIVE DEVELOPMENT AREAS USING GENETIC ALGORITHMS APPLIED TO MORE THAN ONE CROP
Jaime Hidehiko Tsuruta, Takashi Hoshi
Abstract
Geographical information on large areas can be obtained in a macroscopic way based on image data of natural resource satellites. Application examples in agriculture, with experiments for selection of areas for agricultural development have been based on geographical information, and others related with soils and existing research on climate. However, the existent methods were efficient for a small number of areas, and for one crop only. This work selected areas for agricultural development for more than one crop using a genetic algorithms approach. With these algorithms, that are part of computational models inspired by nature, and used to solve search and optimization problems, maximization of the total net income of the planted crops was sought. The study area is located in the district of Ira{ de Minas, and the production of two crops: soybean and corn was studied. In this model, the production of crops is a function of the application of basic inputs: lime and the fertilizer, as well as production costs. The quantities of these inputs were adjusted to the cost of the production systems of that region. The introduction of irrigation systems to avoid loss of production by drought was considered. With the evolution of genetic research, productivity of new varieties was also considered. The results show that the selection of agricultural adaptive development areas using genetic algorithms for more than one crop was made operational.
Keywords
References
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