A fuzzy logic based model for detecting leaf blast disease in rice crop with ANFIS and linear regression technique
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Date
2019-07
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G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand)
Abstract
This model uses the fuzzy logic advancement in detection analysis for agriculture sector using fuzzification tool in MATLAB. It is considered to be a good technique in precision agriculture. In this work, the first focus is to detect the level of leaf blast disease in rice crop by using three specific symptoms. The detected levels of disease grading level are Level 1- Mild, Level 2- Moderate, Level 3- Extreme corresponding to the disease occurrence. Then this disease grade level will be used to obtain the risk level in percentage form. The techniques used here are the fuzzy logic implementation in two level, the linear regression technique to identify the relationship between the disease level and risk level also dataset was generated by regression then used in ANFIS tool in MATALB and finally the decision tree is used to detect disease and the major symptom among all symptoms and which plays vital role in deciding the disease severity class label.
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