A low cost smart system to analyze different types of edible Bird's nest adulteration based on colorimetric sensor array.
A low cost smart system to analyze different types of edible Bird's nest adulteration based on colorimetric sensor array.
复制标题
基于比色传感器阵列分析不同类型食用燕窝掺假的低成本智能系统
DOI：
10.1016/j.jfda.2019.06.004
复制
发表时间：
2019-10
影响因子：
3.6
通讯作者：
Xuetao Hu
中科院分区：
文献类型：
--
作者：
Xiaowei Huang;Zhihua Li;Xiaobo Zou;Jiyong Shi;Elrasheid Tahir, H.;Yiwei Xu;Xiaodong Zhai;Xuetao Hu
本研究旨在开发一种低成本的智能系统，用于鉴定和定量掺假食用燕窝（EBN）。该智能系统由比色传感器阵列（CSA）、智能手机和多层网络模型组成。利用CSA采集EBN的气味特征，并通过智能手机系统捕获CSA的响应信号。采用主成分分析（PCA）和层次聚类分析（HAC）对正品和掺假ebn进行相似性分析。建立了多层网络模型来分析EBN掺假。在该模型中，利用反向传播神经网络（BPNN）算法实现了正品EBN和掺假EBN的判别。然后，建立了另一个基于bpnn的模型来识别混合EBN中的掺杂物类型。最后，利用偏最小二乘（PLS）方法建立了各类掺假EBN的掺假率预测模型。结果表明，正品和掺假的EBN的识别率高达90%。百分比预测模型对校正集的相关系数为0.886，对预测集的相关系数为0.869。这种低成本的智能系统为客户和零售商提供了一种实时的、非破坏性的工具来验证EBN。
This study was performed to develop a low-cost smart system for identification and quantification of adulterated edible bird’s nest (EBN). The smart system was constructed with a colorimetric sensor array (CSA), a smartphone and a multi-layered network model. The CSA were used to collect the odor character of EBN and the response signals of CSA were captured by the smartphone systems. The principal component analysis (PCA) and hierarchical cluster analysis (HAC) were used to inquiry the similarity among authentic and adulterated EBNs. The multi-layered network model was constructed to analyze EBN adulteration. In this model, discrimination of authentic EBN and adulterated EBN was realized using back-propagation neural networks (BPNN) algorithm. Then, another BPNN-based model was developed to identify the type of adulterant in the mixed EBN. Finally, adulterated percentage prediction model for each kind of adulterate EBN was built using partial least square (PLS) method. Results showed that recognition rates of the authentic EBN and adulterated EBN was as high as 90%. The correlation coefficient of percentage prediction model for calibration set was 0.886, and 0.869 for prediction set. The low-cost smart system provides a real-time, nondestructive tool to authenticate EBN for customers and retailers.