Oregano herb adulteration detection through rapid spectroscopic approaches: Fourier transform-near infrared and laser photoacoustic spectroscopy facilities

Oregano is a culinary herb known and used worldwide, whose demand and cost encourage illegal activities in terms of fraud, especially adulteration. The scope of this study is to provide a rapid, cost-effective and easy-to-use approach to detect the adulteration of oregano with a common matrix, the olive leaves. Two analytical solutions were considered, Fourier transform near infrared (FT-NIR), using two different instruments, and laser photoacoustic spectroscopy (LPAS). Different raw data preprocessing procedures were applied, Principal Component Analysis (PCA) was used for preliminary data visualisation, while Partial Least Squares Regression (PLS-R) and Discriminant Analysis (PLS-DA) allowed the authors to classify samples with different adulteration percentages. FT-NIR performed better than LPAS, perhaps also because the photoacoustic system is still an experimental prototype. For example, the coefficient of determination R2 between actual and predicted adulterant concentrations was in the range 0.93–1.00 for FT-NIR and in the range 0.86–0.96 for LPAS. Nevertheless, this allowed the use of a low level data fusion approach to increase the consistency of the statistical model. The fusion between raw data from the LPAS prototype and one of the FT-NIR instruments gave optimal results, confirming the potential of these analytical solutions for the identification of oregano adulterants. The approaches used in the present work could be applied to the identification of other adulterants in herbs and spices by food companies for quality control measurements, possibly for on line and in field analysis.