Development of electronic nose (Shrimp-Nose) for the determination of perishable quality and shelf-life of cultured Pacific white shrimp (Litopenaeus Vannamei)

被引:43
作者
Srinivasan, Parthasarathy [1 ,2 ]
Robinson, Jeyashakila [3 ]
Geevaretnam, Jeyasekaran [4 ]
Rayappan, John Bosco Balaguru [1 ,2 ]
机构
[1] SASTRA Deemed Univ, Ctr Nano Technol & Adv Biomat CeNTAB, Thanjavur 613401, Tamil Nadu, India
[2] SASTRA Deemed Univ, Sch Elect & Elect Engn SEEE, Thanjavur 613401, Tamil Nadu, India
[3] Tamil Nadu Dr J Jayalalithaa Fisheries Univ, Dept Fish Qual Assurance & Management, Fisheries Coll & Res Inst Campus, Thoothukudi 628008, Tamil Nadu, India
[4] Tamil Nadu Dr J Jayalalithaa Fisheries Univ, Vettar River View Campus, Nagapattinam 611002, Tamil Nadu, India
关键词
Pacific white shrimp; Perishable quality; Shelf life; Electronic nose; Microbial analysis; Texture analysis; DNA-BASED METHODS; FRESHNESS ASSESSMENT; FERULIC ACID; FOOD QUALITY; CHITOSAN; POLYPHENOLOXIDASE; INHIBITION; KINETICS; CATECHIN; FISH;
D O I
10.1016/j.snb.2020.128192
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Production and consumption of Pacific white shrimp (Litopenaeus vannamei) have drastically increased over the years, owing to its taste and high nutritional value. At the same time, monitoring its perishable quality and shelf-life to meet export standards is proving to be a major concern. In this context, Shrimp-Nose has been designed and developed using six partially selective metal oxide-based gas sensors (TGS 880, 823, 826, 2600, 2602, and 822 (Figaro, Japan)) for the rapid freshness assessment. To extensively investigate the quality changes in both the perishable and iced storage conditions, Shrimp-Nose measurements were observed at different time intervals (in terms of hours (h) for un-iced conditions and days for 2 degrees C refrigerated storage conditions). Pattern recognition algorithms based on multivariate analyses such as Principal Component Analysis (PCA), Decision Tree, Random Forest, K-Nearest Neighbour (KNN) and Soft-max Regression were implemented in which Soft-max Regression algorithm showed the decision accuracies of 96.29% and 95.73% towards un-iced and iced samples respectively. Supporting experiments such as pH, Total Volatile Base Nitrogen (TVBN), Fourier Transform Infrared (FTIR) spectra, texture, microbial, and sensory analysis were investigated at different time intervals to monitor the quality changes. Also, melanosis was investigated at different time intervals to estimate the shelf-life of shrimp samples. Shrimp-Nose measurements are found to be in good agreement with the results observed using supporting experiments.
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页数:12
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