发酵
相关系数
化学
色谱法
偏最小二乘回归
残余物
决定系数
人工神经网络
生物系统
数学
食品科学
人工智能
计算机科学
算法
生物
统计
作者
Li Wang,Feng Xiong,Xingyi Huang,Joshua Harrington Aheto,Shanshan Yu,Yu Wang,Xiaorui Zhang,Yi Ren
出处
期刊:Food Chemistry
[Elsevier]
日期:2022-03-31
卷期号:387: 132867-132867
被引量:26
标识
DOI:10.1016/j.foodchem.2022.132867
摘要
In this work, a colorimetric sensor array (CSA) for quantitative determination of total acids in apple vinegar during fermentation was constructed. The sensor array was properly designed based on indicators displacement assay (IDA) using three metal ions (Cu2+, Zn2+ and Ni2+) as receptors to organic acids. The time stability results showed that the prepared CSA had good operational stability. Three quantitative models, including one linear (partial least square, PLS) and two nonlinear (support vector regression, SVR and back propagation artificial neural network, BP-ANN) models were used to estimate the content of total acids in fermentation broth of apple vinegar through image analysis. The correlation coefficient (RP), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) of the better SVR model were 0.8708, 0.0545 and 10.91, respectively. The results implied that the CSA had an excellent potential for quantitative monitoring of total acids in apple vinegar during fermentation.
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