Publication

Abstract : 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 °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.