School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China; College of Ocean Food and Biological Engineering, Jimei University, Xiamen 361021, PR China.
Food Chem. 2024 May 1;439:138172. doi: 10.1016/j.foodchem.2023.138172. Epub 2023 Dec 9.
Total volatile basic nitrogen content (TVB-N) is an important index of freshness for snakehead. This paper attempted the feasibility of determining TVB-N content level in snakehead fillets by a colorimetric sensor array (CSA) composed of twelve porphyrin materials and eight pH indicators. The nine feature variables in RGB, HSV and CIE Lab* color spaces were obtained by differentiating the images of the CSA before and after exposure to the headspace-gas of the samples. Competitive adaptive reweighted sampling combined with partial least squares regression (CARS-PLS) was used to build the relationship between the TVB-N content and the feature variables of CSA, and to select meaningful color-sensitive materials. The results showed that CARS-PLS had a correlation coefficient of 0.9325 in the prediction set and selected 13 informative color-sensitive materials. This study demonstrated that the CSA with CARS-PLS algorithm could be used successfully to quantify and monitor the TVB-N in snakehead fillets.
挥发性盐基氮(TVB-N)含量是评价鱼头鲜度的重要指标。本研究采用由 12 种卟啉材料和 8 种 pH 指示剂组成的比色传感器阵列(CSA),尝试通过该传感器阵列测定鱼头片中 TVB-N 含量的可行性。通过比较 CSA 在暴露于样品顶空气体前后的图像,获得 RGB、HSV 和 CIE Lab*颜色空间中的 9 个特征变量。采用竞争自适应重加权采样结合偏最小二乘回归(CARS-PLS)建立 CSA 特征变量与 TVB-N 含量之间的关系,并筛选出有意义的颜色敏感材料。结果表明,预测集中 CARS-PLS 的相关系数为 0.9325,选择了 13 种有信息的颜色敏感材料。本研究表明,采用 CARS-PLS 算法的 CSA 可成功用于定量和监测鱼头片中的 TVB-N。