DEVELOPMENT OF DIGITAL IMAGE COLORIMETRY (DIC) METHOD FOR DETERMINING THE FRESHNESS OF MULLET FISH (Mugil cephalus) USING A SMARTPHONE

Abstract

Fish is a highly perishable fishery commodity that rapidly deteriorates after being caught; therefore, a rapid, accurate, and practical method for freshness detection is required. Conventional methods such as organoleptic tests are limited by their subjectivity, thus necessitating the development of alternative approaches based on digital technology. This study aimed to develop a smartphone-based Digital Image Colorimetry (DIC) method for detecting fish freshness using a natural dye extracted from Butterfly Pea Flower (Clitoria ternatea) and to compare its accuracy with the conventional organoleptic method. The sample used was Mullet Fish (Mugil cephalus), which was filleted (without bones) and divided into three portions, each weighing 5 grams. The fish portions were placed in transparent bottles equipped with indicator labels made from Butterfly Pea extract, and color changes were observed during storage at room temperature. The indicator labels were periodically photographed using a smartphone camera, and the captured images were analyzed using ImageJ software to obtain RGB values as color change parameters. Anthocyanins in the Butterfly Pea extract act as pH indicators sensitive to volatile compounds (ammonia) produced during spoilage. The results showed a gradual color change of the indicator label from purple to blue as storage time increased, with RGB value patterns consistent with the deterioration process. Based on organoleptic tests, the fish was categorized as spoiled after 12 hours of storage, which was consistent with the DIC results. Therefore, the Digital Image Colorimetry (DIC) method using Butterfly Pea extract was proven to be accurate, practical, and promising as a smartphone-based alternative for detecting fish freshness.