College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an 710119, Shaanxi, China.
School of Materials Science and Engineering, Shaanxi Normal University, Xi'an 710119, Shaanxi, China.
Food Chem. 2023 Jan 30;400:134041. doi: 10.1016/j.foodchem.2022.134041. Epub 2022 Aug 28.
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 (R) of the PLS model of TVB-N were all higher than 0.8. Notably, the R 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.
传统的肉类新鲜度评估方法繁琐且耗时。在本研究中，通过荧光膜传感器监测了-1、4、10 和 25°C 下羊肉和鸭肉的新鲜度，并采用传统方法测定了样品中总挥发性碱性氮（TVB-N）和生物胺（BAs）的含量。对传感器响应强度（RI）与新鲜度指标之间进行了相关性和偏最小二乘（PLS）回归分析。结果表明，0-1cm 皮下取样深度下羊肉和鸭肉的 RI、TVB-N 和 BAs 含量高度相关。此外，TVB-N 的 PLS 模型的回归系数（R）均高于 0.8。值得注意的是，PLS 模型中 25°C 下鸭肉的 R 为 1。本研究首次通过荧光膜传感器准确预测了畜禽肉中的 TVB-N 值，该方法实时快速，在未来的生产中具有肉类新鲜度评估的巨大潜力。
