Data standardization strategy to correct the effect of seasonality in the authentication of virgin olive oil

This study proposes a standardization strategy for dealing with seasonal variability in the authentication of extra virgin oils from the PDOs Les Garrigues and Siurana. Samples from four harvests were measured by fluorescence spectroscopy. A PLS-DA two-class model was developed and validated from samples from one of the harvests. When samples from three other harvests were predicted with the model developed, it was observed that the sensitivity and specificity were lower than when the model was validated. For the standardization process, we adapted the PDS technique to obtain the transfer function. The results obtained from the transformed spectra show that standardization is a good strategy for extending the usefulness of the models if the samples to be predicted are subject to seasonal variability.

Automated summary

This study proposes a standardization strategy for dealing with seasonal variability in the authentication of extra virgin oils from the PDOs Les Garrigues and Siurana. A PLS-DA two-class model was developed and validated using fluorescence spectroscopy measurements. The results show that standardization is a good strategy for extending the usefulness of the models when predicting samples subject to seasonal variability.