Real-time and rapid prediction of TVB-N of livestock and poultry meat at three depths for freshness evaluation using a portable fluorescent film sensor
2023
Zhang, Duoduo | Zhu, Li | Jiang, Qingwei | Ge, Xinyu | Fang, Yu | Peng, Junxia | Liu, Yongfeng
Traditional meat freshness evaluation methods are cumbersome and time consuming. In this study, the freshness of goat and duck meat at −1, 4, 10, and 25 °C was monitored by the fluorescent film sensor, and the content of total volatile basic nitrogen (TVB-N) and biogenic amines (BAs) of the samples was also determined using traditional methods. Correlation and partial least squares (PLS) regression analyses were performed between sensor response intensity (RI) and freshness indices. The results showed that the RI, TVB-N, and BAs contents of goat and duck meat at a subcutaneous sampling depth of 0–1 cm were highly correlated. Moreover, the regression coefficients (R²) of the PLS model of TVB-N were all higher than 0.8. Notably, the R² of duck meat at 25 °C in the PLS model was 1. This study accurately predicted TVB-N values in livestock and poultry meats by the fluorescent film sensor for the first time, which is real-time, and rapid, with great potential for meat freshness evaluation in future production.
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