Image analysis as non-destructive approach in characterization of Indian sweet meat spongy Rosogulla - Shekhar, Shubhra; Minz, P S (Journal of Postharvest Technology, 2020)
Quality characterization and sustenance of food quality is of major concern in food industry. The variability in the food texture is another concerning parameter affecting the acceptance of food products. The reliability and acceptability of the processed finished food products in the market depends on its overall quality characteristics. Most of the quality assessing approaches are destructive in nature and require more materials to analyze various parameters to judge its overall characteristics. Further, this approach requires several high-end equipment with trained technical man powers for handling such equipment and interpreting the complicated results. On the other hand, the Image analysis approach being non-destructive technique does not require the material to waste and not complicated even. The approach requires daily use equipment such as camera, laptop and software skills. Under the present investigation various characteristics of Indian made spongy rosogulla was performed using non-destructive offline approach. Multiple images of the samples were taken. In order to analyze and extract Gray-Level Co-occurrence (GLCM) matrix properties of the image a software program was developed using MATLAB software. The mean and standard deviation values were determined and compared for all the four offsets. The significant values were taken and compared for the selected properties among twenty-two properties.