Economic yield prediction in six rice (Oryza sativa L.) genotypes by applying Mamdani rule based fuzzy model - Pandey, Veena; Kumar, Sanjay; Shankhdhar, Shailesh Chandra; Shankhdhar, Deepti (ORYZA-An International Journal of Rice, 2018)
In the area of agricultural practices, yield prediction relies on human expertise but it is not always reliable due to many reasons. Fuzzy logic system is a mathematical method of rule-based decision making and can be used to predict the yield of crops very effectively. It plays an essential role in the remarkable human ability to make rational decisions in an environment of uncertainty which affects the yield of seasonal crops. In the present study, Mamdani fuzzy rule based system is developed for prediction of economic yield of six different rice genotypes, KRH-2, PA-6129, PHB-71, AK-DHAN, NDR-359, VARADHAN. The proposed Mamdani rule based model uses different values of total dry matter and number of effective tillers of all the genotypes as input variables. No remarkable difference was found in the prediction of economic yield of all the rice genotypes obtained by fuzzy rule based model and yield obtained by field grown crop. Out of six genotype fuzzy system also predicted that KRH-2 is best in terms of economic yield when grown in normal sowing conditions.