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应用比色传感器阵列结合化学计量学方法监测乌头鱼片的新鲜度。

Application of colorimetric sensor array coupled with chemometric methods for monitoring the freshness of snakehead fillets.

机构信息

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.

出版信息

Food Chem. 2024 May 1;439:138172. doi: 10.1016/j.foodchem.2023.138172. Epub 2023 Dec 9.

Abstract

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.

摘要

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。

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