Development of portable, non-destructive freshness indicative sensor for Indian Mackerel (Rastrelliger kanagurta) stored under ice

• Published in: Journal of food engineering Vol. 287; p. 110132
• Main Authors: Kunjulakshmi, S., Harikrishnan, S., Murali, S., D'Silva, Jeff Martin, Binsi, P.K., Murugadas, V., Alfiya, P.V., Delfiya, D.S. Aniesrani, Samuel, Manoj P.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-12-2020
• Subjects: Computer vision; Fish eye; Image processing; K-value; Pixel; Psychrophilic count; Computer vision; Psychrophilic count; Image processing; K-value; Pixel; Fish eye
• ISSN: 0260-8774; 1873-5770
• DOI: 10.1016/j.jfoodeng.2020.110132

A handheld, portable and non-destructive instrumental sensor was developed to assess the freshness of Indian Mackerel (Rastrelliger kanagurta) stored under ice. The freshness sensor consists of a webcam, raspberry-Pi (small single-board computer), LCD display and a power bank. The color changes in fish eye as a result of spoilage during iced storage was measured as pixel count using image processing technique. Simultaneously, destructive fish quality and freshness results were obtained by estimating K-value and Psychrophilic count during the storage. Multiple linear regression analyses were performed to assess the relationship between pixel count and quality indicators. The analysis of results of K-value and Psychrophilic count revealed that fish quality and freshness limits can be established in storage days as extremely fresh up to third day, fresh till thirteenth day and then spoiled. Further, these quality limits were correlated with pixel count against storage days to establish three different ranges in pixel count. The obtained pixel count ranges were provided as input to the sensor for classification of fish samples into three indicative freshness levels i.e. Extremely fresh, Fresh and Spoiled. The validation study of sensor was conducted by assessing fish samples collected from local markets and observed that sensor was accurately predicting the freshness of fish.
•Developed a handheld, portable, non-destructive freshness indicative sensor to assess the freshness of Indian Mackerel.•The color changes in fish eye during iced storage was correlated with degree of freshness of fish.•Image processing technique was used to objectively quantify the color changes in fish eye over storage days.•Pixel count was highly correlated with K-value and Psychrophilic count over storage days.•The sensor could be very useful to assess the freshness when there is no information on the time of harvest of fish.