A paper-based colorimetric sensor array for discrimination of monofloral European honeys based on gold nanoparticles and chemometrics data analysis
A paper-based colorimetric sensor array for discrimination of monofloral European honeys based on gold nanoparticles and chemometrics data analysis
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DOI：
10.1016/j.saa.2020.119076
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发表时间：
2021-02-15
影响因子：
4.4
通讯作者：
Hemmateenejad, Bahram
中科院分区：
文献类型：
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作者：
Chaharlangi, Mahsa;Tashkhourian, Javad;Hemmateenejad, Bahram
开发了一种灵敏且简单的基于纳米材料的比色传感器阵列（NBCSA），用于基于三种植物来源如金合欢、卡诺拉和蜜露来区分来自不同欧洲国家的单花蜂蜜。NBCSA通过点样使用六种不同的还原剂和/或封端剂合成的金（AuNPs）和银（AgNPs）纳米颗粒来设计。当与蜂蜜样品顶空中出现的挥发性有机化合物相互作用时，AuNPs的颜色强度表示差异变化。色差图被计算为暴露于样品蒸气之前和之后传感器的颜色强度之间的差异，其被用作指纹以基于植物来源来区分蜂蜜样品。利用数据预处理和化学计量学数据分析实现分类。偏最小二乘判别分析和线性判别分析的拟合精度分别为88%和86%，而支持向量机的拟合精度为100%。(C)2020爱思唯尔B. V.保留所有权利。
A sensitive and simple nanomaterial based colorimetric sensor array (NBCSA) was developed for discrimination of monofloral honey from various European countries based on three botanical origins as Acacia, Canola and Honeydew. The NBCSA was designed by spotting gold (AuNPs) and silver (AgNPs) nanoparticles synthesized using six different reducing and/or capping agents. The colour intensity of AuNPs represented differential changes when interacting with volatile organic compounds appeared in the headspace of the honey samples. The color difference maps, which are calculated as the difference between color intensity of the sensor before and after exposing to the sample vapors, were used as a fingerprint to discriminate the honey samples based on botanical origin. Classification was achieved utilizing data pre-processing and chemometrics data analysis. Fitting accuracies of 88% and 86% were obtained by partial least squares discriminant analysis and linear discriminant analysis whereas 100% was achieved using support vector machine. (C) 2020 Elsevier B.V. All rights reserved.