Machine vision analysis for industrial beet color change kinetics and total soluble solid content

Abstract. A machine vision system (MVS) for the measurement of color change kinetics in crushed industrial beet to evaluate the total soluble solid content (°Brix) was developed in this study. It is expected that higher the °Brix faster the color change and modeling this color change kinetics helps in assessing the ground beet quality for juice extraction. The central portion from the whole beet was chopped off for preparing the ground sample. Laboratory blender was used to grind the beets. Five different concentration of beet samples were prepared by mixing the crushed beets with varying quantities of cold water followed by draining. Digital images at regular time intervals were acquired for all the samples using a digital camera with an auto timer setting under a constant lighting condition. MVS was calibrated using the ColorChecker before the experimentation. Quadratic model was used for converting the RGB to L*,a*,b* values. For each sample a constant representative window of the image were cropped and analyzed for L*, a*, b* (CIELAB color space) and total color change (∆E). Program for calibrating, cropping and analyzing the images was written in MATLAB. Different color kinetics models (∆E with respect to time) were fitted separately for samples of different soluble solid concentration. Out of the models tested, the Page model gave the best fit (R² = 0.91-0.99) for the color kinetics. Out of the model constants, Page model’s constant (n) gave an excellent linear fit (R² = 0.995) with TSS of the crushed beets. The developed machine vision system can be successfully used for modeling the color change kinetics as well as measuring the beet sugar content by correlation that is mostly represented by the TSS.