Application of Fuzzy Inference System to Predict the Yield of Potato, Alfalfa and Wheat in Shahr-e-Kian area

Document Type : Research Paper

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Abstract

In this study the efficiency of fuzzy inference system to predict the main crops yield of Shahr-e-Kian area in Chaharmahal and Bakhtiari province was evaluated and compared to the Boolean logic-based land evaluation methods. To do this, soil samples were collected and analyzed physicochemicaly from 21 observation points located on the centers of a 1 km by 1 km grid framework in the study area according to the routine semi-detailed soil survey studies. Weighted average of soil characteristics up to depth of 1 m was used. Then the quantitative land suitability for wheat, alfalfa and potato using square root (conventional Boolean-based method) and fuzzy inference system (by calculating the membership functions of each land suitability class) approaches was determined. Also, the potential yields of the selected crops were calculated based on FAO model using the climatic parameters of the studied area. The expected yield for each observation points was predicted afterward. The accuracy assessment of fuzzy inference system and Boolean methods were carried out by comparing the regression coefficients between calculated land indices and observed (actual) yields in the field. The observed correlation coefficients for wheat, potato and alfalfa were 0.738, 0.642 and 0.6 in Boolean approach, respectively and the coefficients were 0.749, 0.885 and 0.713 in fuzzy inference system, respectively. The results showed that the fuzzy inference system approach had higher efficiency than Boolean method in this area.

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Water and Soil Science
Volume 26, Issue 3 - Serial Number 3
December 2016
Pages 265-275

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