Journal of Researches in Mechanics of Agricultural Machinery

Journal of Researches in Mechanics of Agricultural Machinery

Application of intelligence system to determine Rials-value of white rice grains based on appearance properties and percentage of chalky grains

Authors
بهرام حسین زاده
Zahra Esmaeili
Sajad Rostami
hemad Zareiforoush
Abstract
Qualitative grading and classifying of rice are one of the factors affecting on the marketing and customer satisfaction. The objective of this study was to develop an accurate algorithm for characterization of three important qualitative indices of rice including percentage of broken grains, percentage of chalky grains and degree of milling. Some rice samples of a variety namely 'AliKazemi' were provided from Rice Research Institute of Iran. After questioning expert persons, three quantitative levels (Low, Medium and High) were defined. The images of each of the 270 samples of rice grains were captured under the same conditions. In development of fuzzy inference model for the product pricing, the Mamdani inference system was applied and defuzzification process was done using Center of Area defuzzifier. Results indicated that the average accuracy of the image processing algorithm in detecting percentage of broken grains, percentage of chalky grains and degree of milling was respectively as 95.2%, 90.74% and 98.99%. The decisions made by the fuzzy model were consistent with the expert’s judgment in 95.2% of the cases. This system can be good alternative to traditional methods used in market and rice processing factory to characterize the rice key propertiesfast and more accurately