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一种用于真实性筛选的快速食品链方法:使用两台手持式近红外光谱(NIRS)设备的化学计量学模型的开发、验证及可转移性

A rapid food chain approach for authenticity screening: The development, validation and transferability of a chemometric model using two handheld near infrared spectroscopy (NIRS) devices.

作者信息

McVey Claire, McGrath Terry F, Haughey Simon A, Elliott Christopher T

机构信息

Institute for Global Food Security, ASSET Technology Centre, School of Biological Sciences, Queen's University Belfast, Northern Ireland, UK.

Institute for Global Food Security, ASSET Technology Centre, School of Biological Sciences, Queen's University Belfast, Northern Ireland, UK.

出版信息

Talanta. 2021 Jan 15;222:121533. doi: 10.1016/j.talanta.2020.121533. Epub 2020 Aug 17.

Abstract

This study assesses the application of a handheld, near infrared spectroscopy (NIRS) device, namely the NeoSpectra Micro, for the determination of oregano authenticity. Utilising a large sample set of oregano (n = 295) and potential adulterants of oregano (n = 109), models were developed and validated using SIMCA 15 software. The models demonstrated excellent predictability for the determination of authentic oregano and adulterant samples. The optimal model resulted in a 93.0% and 97.5% correct prediction for oregano and adulterants, respectively. Different standardisation approaches were assessed to determine model transferability to a second NIRS device. In the case of the second device, the best predictions were achieved with data that had not undergone any spectral standardisation (raw). Subsequently, the optimal model was able to correctly predict 90% of authentic oregano samples and 100% of the adulterant samples on the second device. This study demonstrates the potential of the device to be used as a simple, cost effective, reliable and handheld screening tool for the determination of oregano authenticity, at various stages of the food supply chain. It is believed that such forms of monitoring could be highly beneficial in other areas of food authenticity analysis to help combat the negative economical and health implications of food fraud.

摘要

本研究评估了一种手持式近红外光谱(NIRS)设备,即NeoSpectra Micro,在测定牛至叶真伪方面的应用。利用大量牛至叶样本集(n = 295)和牛至叶潜在掺假物样本集(n = 109),使用SIMCA 15软件建立并验证了模型。这些模型在测定纯正牛至叶和掺假物样本方面显示出出色的预测能力。最优模型对牛至叶和掺假物的正确预测率分别为93.0%和97.5%。评估了不同的标准化方法,以确定模型向另一台NIRS设备的可转移性。对于第二台设备,未经过任何光谱标准化(原始)的数据实现了最佳预测。随后,最优模型能够正确预测第二台设备上90%的纯正牛至叶样本和100%的掺假物样本。本研究证明了该设备作为一种简单、经济高效、可靠的手持式筛查工具,在食品供应链各个阶段测定牛至叶真伪的潜力。据信,这种监测形式在食品真伪分析的其他领域可能非常有益,有助于应对食品欺诈带来的负面经济和健康影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5cb/7430240/a42dd548f7ac/fx1_lrg.jpg

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