Qualitative and quantitative analysis of toxic materials in adulterated fruit pickle samples by a colorimetric sensor array
Qualitative and quantitative analysis of toxic materials in adulterated fruit pickle samples by a colorimetric sensor array
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DOI：
10.1016/j.snb.2017.11.010
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发表时间：
2018-03-01
影响因子：
8.4
通讯作者：
Hemmateenejad, Bahram
中科院分区：
文献类型：
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作者：
Bordbar, Mohammad Mandi;Tashkhourian, Javad;Hemmateenejad, Bahram
提出了一种基于新型灵敏比色传感器阵列的检测和测定欺诈泡菜中明矾和合成乙酸两种主要有毒物质的简单、低成本方法。该传感器由（4 × 5） pH和氧化还原指示剂阵列组成。颜色变化谱是每个具体分析物的单独指纹，可以用普通的平板扫描仪进行监测，然后使用无监督模式识别方法，如主成分分析（PCA）和层次聚类分析（HCA）。所产生的颜色图案依赖于用于生产泡菜的水果类型，因此它们用于根据所产水果的类型来区分醋。此外，传感器的响应取决于明矾和合成乙酸添加到泡菜的量。采用偏最小二乘（PLS）回归作为多元校正方法，通过图像分析估计了腌菜样品中明矾和合成乙酸的含量。明矾的校准和预测均方根误差分别为0.469和0.446，醋酸的校准和预测均方根误差分别为1.34和0.933。该比色传感器阵列在水果泡菜样品的定性和定量控制方面具有良好的潜力。(c) 2017 Elsevier B.V.版权所有
A simple and low cost method was presented for detection and determination of two major toxic materials including alum and synthetic acetic acid in fraud pickles based on a novel and sensitive colorimetric sensor array. This sensor was composed of a (4 x 5) array of pH and redox indicators. The color change profiles were individual fingerprints for each specifics analytes and can be monitored with an ordinary flatbed scanner followed by unsupervised pattern recognition method such as principal component analysis (PCA) and hierarchical clustering analysis (HCA). The produced color patterns were dependent on the type of fruit used for producing of pickle and hence they used for discrimination of the vinegar based on the type of fruits they originated. Also, the responses of the sensors were dependent on the amounts of alum and synthetic acetic acid added to the pickles. Partial least square (PLS) regression as a multivariate calibration method was used to estimate the content of alum and synthetic acetic acid in pickle samples through image analysis. A root mean square error for calibration and prediction of 0.469 and 0.446 for alum and also 1.34 and 0.933 for acetic acid were obtained, respectively. This colorimetric sensor array demonstrates excellent potential for qualitative and quantitative control of fruit pickle samples. (c) 2017 Elsevier B.V. All rights reserved.