Fish is a highly perishable commodity that experiences rapid quality deterioration after being caught, thus requiring a rapid, accurate, and practical freshness detection method. Conventional methods such as organoleptic tests have limitations due to their subjective nature, thereby necessitating the development of alternative methods based on digital technology. This study aims to develop a smartphone-based Digital Image Colorimetry (DIC) method to detect fish freshness using natural dye from butterfly pea extract (Clitoria ternatea), and evaluate the accuracy of DIC results compared to conventional organoleptic tests. This research employed an experimental quantitative approach by utilizing indicator paper labeled with butterfly pea extract. Anthocyanins contained in the extract functioned as pH indicators that respond sensitively to volatile compounds (ammonia) produced during fish storage. Color changes were analyzed through RGB values obtained using a smartphone application and compared with panelist-based organoleptic evaluations. The results showed that the DIC method was successfully developed using butterfly pea extract as a natural dye on indicator paper. The observed color changes during fish deterioration were consistent with the RGB value patterns. Furthermore, the DIC analysis demonstrated strong consistency with organoleptic test results, indicating that the DIC method is accurate, practical, and potentially applicable as an alternative to conventional methods for determining fish freshness using a smartphone-based system.
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