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

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.