TOMATO MATURITY CLASSIFICATION VIA IMAGE ANALYSIS

Abstract

This study aims to investigate the possibilities of using a simple image processing technique to evaluate tomato fruit quality. According to the USDA standard, green, pink and red tomatoes maturity coloring index is used to evaluate fruit quality. Maturity stage of fresh tomato fruit is an important factor that affects the fruit quality during ripening and marketability after ripening. Images obtained at top, bottom, side, and fruit opposite side, analyzed through algorithm were created in MATLAB computer software. Results of the image analysis are compared to the measured and calculated values of fruit physical properties and mechanical characteristics (dimensions, sphericity, rupture force and firmness) changes due to changes of maturity stages. Results at different ripening stages indicated that the captured image data at the bottom of tomato fruit were the most accurate to assist the fruit maturity. Results indicated that the proposed image processing technique for assessment of tomato fruit was accurate by 98%.