The potential of handheld near infrared spectroscopy to detect food adulteration: Results of a global, multi-instrument inter-laboratory study
•Low cost handheld NIR/ single device chemometric model for oregano adulteration.•Greater than 85% correlation in results compared to ISO 17,025 FTIR method.•Interlaboratory study: 27 participants from 22 countries using 34 unique devices.•Participants correctly predicted >98% genuine oregano aft...
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Veröffentlicht in: | Food chemistry 2021-08, Vol.353, p.128718, Article 128718 |
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Sprache: | eng |
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Zusammenfassung: | •Low cost handheld NIR/ single device chemometric model for oregano adulteration.•Greater than 85% correlation in results compared to ISO 17,025 FTIR method.•Interlaboratory study: 27 participants from 22 countries using 34 unique devices.•Participants correctly predicted >98% genuine oregano after device standardisation.•Participants correctly predicted 100% adulterated samples after standardisation.
Fraud in the food supply system will be exacerbated by shortages caused by climate change and COVID-19′s impact. The dried herbs market exemplifies complex supply chains attractive to criminals seeking financial gain. Real-time remote testing is achievable through development of globally accessible chemometric models for portable near infrared devices, deployed throughout supply chains. This study describes building of models for detection of oregano adulteration, on portable near infrared devices, and comparison to a laboratory-based Fourier-Transform Infrared spectroscopy method. 33/34 portable devices were able to correctly classify 5 out of 6 samples successfully with all adulterated samples being correctly classified following the use of appropriate transferability pre-processing routines. The devices native setup shows limited ability to perform a true screening of oregano using the setup offered. However modifications to the setup could in the future offer a solution that facilitates fit-for-purpose real time detection of adulterated samples within the supply chain. |
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ISSN: | 0308-8146 1873-7072 |
DOI: | 10.1016/j.foodchem.2020.128718 |