Enhancing Traceability of Italian Almonds through IR Spectroscopy and Chemometric Classifiers

Abstract

Almonds are the seeds of the almond (Prunus Amygdalus) tree and are a nut consumed worldwide. The present study utilized the ATR FT-IR technique followed by a chemometric analysis to develop predictive models for determining the geographical origin of almonds from three regions in Southern Italy (Apulia, Calabria, and Sicily). IR spectra were collected on both the almond shell and the edible kernel to accurately characterize the three different geographical origins. The spectroscopic data obtained were processed using Soft Independent Modeling of Class Analogies (SIMCA) and Partial Least Squares Discriminant Analysis (PLS-DA). Both SIMCA and PLS-DA revealed that the shell spectra are more useful for assessing the geographical origin of samples. In particular, the PLS-DA model applied to these data achieved a 100% correct classification rate (on the external test set of individuals) for all the investigated classes.

Keywords

• almond
• nuts
• classification
• geographical origin
• traceability
• FT-IR