Prediction of tomatoes maturity using TCS3200 color sensor

Abstract

Abstract Vitamin C (ascorbic acid) increased as the maturity advances from green to fully ripe stage and ascorbic acid showed continuously increasing patterns throughout ripening until the red stage. Vitamin C analysis with an invasive method at a laboratory, will cause damage to the sample, require a long time, and can not be used in further measurements. Digital image processing techniques as noninvasive method can predict the maturity of tomatoes and vitamin C non-destructively. The purpose of this study was to design a digital image system to predict tomatoes maturity automatically, simply and practically. RGB digital image and vitamin C content are used as a database system to predict maturity on tomatoes. The performance test used 30 pieces of unripe, medium and ripe tomatoes. The result shows each maturity phase of the tomato has a different RGB value. The Green value decreases with an increasing level of tomato maturity. Red values tend to be the same because tomatoes have a red index from the beginning of their ripeness. From the database of RGB and vitamin C, the equipment shows that unripe level of maturity with RGB values below 10 have vitamin C content about 29.5, medium level of maturity with RGB value between 11-23 have vitamin C content about 33.4, and ripe level with RGB values above 23 have vitamin C content approximately 36.9. The result of the performance test shows that it can detect tomatoes maturity by obtaining a success rate of 93%.