Main Article Content
Brassica rapa L., image analysis, GLCM, nutritional quality, Raphanus sativus L., ImageJ
Microgreens have been recently introduced as a new category of vegetables, with unexploited potential as functional foods. Due to containerized production, they can be commercialized while growing on the medium, ready for being harvested before use. The chlorophyll content of vegetables is important for both health benefits and visual appearance of the produce. This paper aims to evaluate the feasibility of using simple tools to monitor chlorophyll content in microgreens of two different species, broccoli raab (Brassica rapa L., Broccoletto group) and radish (Raphanus sativus L.), in varying stages of cold storage in their growing vessel. Image acquisition with a CCD camera, followed by image analysis using preset algorithms of an open source software (ImageJ) was the approach used. Image color analysis (median values of L*, a*, and b* indices) and textural parameters obtained from the gray-level co-occurrence matrix (GLCM) allowed to obtain regression models for chlorophyll content with satisfactory fitting parameters (adjusted R2 was 0.765 and 0.843 for broccoli raab and radish, respectively). These results point out the possibility to set up low-cost, real time, non-destructive monitoring systems for microgreens quality during their growing as well as during storage.