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

被引:14
作者
Kunjulakshmi, S. [1 ]
Harikrishnan, S. [1 ]
Murali, S. [1 ]
D'Silva, Jeff Martin [1 ]
Binsi, P. K. [2 ]
Murugadas, V [3 ]
Alfiya, P., V [1 ]
Delfiya, D. S. Aniesrani [1 ]
Samuel, Manoj P. [1 ]
机构
[1] ICAR Cent Inst Fisheries Technol, Engn Div, Cochin 682029, Kerala, India
[2] ICAR Cent Inst Fisheries Technol, Fish Proc Div, Cochin 682029, Kerala, India
[3] ICAR Cent Inst Fisheries Technol, Microbiol Fermentat & Biotechnol Div, Cochin 682029, Kerala, India
关键词
Pixel; Image processing; Fish eye; Computer vision; K-value; Psychrophilic count; FISH QUALITY; VISION SYSTEM; COLOR; CLASSIFICATION; MUSCLES; STORAGE; GILL;
D O I
10.1016/j.jfoodeng.2020.110132
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
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.
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页数:8
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