Using an image processing technique, correlating the lycopene and moisture content in dried tomatoes

Abstract

Food staples like tomatoes (Lycopersicon esculentum) are rich in lycopene, which provides ripe tomatoes their deep red colour and is thought to provide health benefits. The consumer's acceptance of the food item depends on the tomatoes' appearance and colour. The traditional methods for determining colour, such as the Dr. Lange and Minolta colorimeters, which worked on surface characteristics, that renders the measurements extremely anomalous & makes it more challenging to conduct a global examination of the food's surface. In order to evaluate tomatoes' colour as they dry and to associate that hue to lycopene and moisture content of tomatoes, this study provides a computer vision system-based technique. Additionally, the colour was determined using a Hunter lab colorimeter, and the results were connected with the moisture and lycopene levels. L*a*b* was chosen as the colour space because of the consistent distribution of hues and how closely it resembles how people perceive colour. According to the findings, drying caused a considerable drop in the L*a*b* values as measured by Hunter Lab and by image analysis. The regression of moisture content generated a very strong association with the moisture content trial data. Lycopene and the results of the experiments on its content correlated well.