Rapid determination of lycopene content and fruit grading in tomatoes using a smart device camera

Lycopene is one of the most important functional components produced in tomatoes. Traditional methods for determining lycopene content usually rely on destructive sampling followed by chemical analysis. This report introduces the use of a smart device camera combined with a new Android application as a novel, rapid, and nondestructive method for determining tomato lycopene content and fruit grade. We first measured chromaticity values and lycopene content in 60 tomato fruits to develop an effective predictive model for lycopene estimation. Second, a method based on color differences between test fruit and several standard colors was designed as a color classification algorithm for fruit grading. Third, an Android application for lycopene estimation and fruit grading was developed. Finally, application functionality was evaluated using an Android 4.2.2 tablet. The results demonstrated that this new approach was functional and its ability to estimate lycopene content and fruit grade was satisfactory.