Chemometric Differentiation of Pistachios (Pistacia vera, Greek ‘Aegina’ Variety) from Two Different Harvest Years Using FTIR Spectroscopy and DRIFTS and Disk Techniques

Abstract

Food quality is a topic of utmost importance as more and more emphasis is placed on quality rather than quantity of products. Previous studies have pointed out the interaction of quality with the harvest year. In this study, 22 Pistacia vera (Greek ‘Aegina’ variety) samples (11 from 2017 and 11 from 2018) were differentiated using Fourier transform infrared spectroscopy (FTIR) and (a) diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and (b) KBr/sample disk techniques. In both years, the pistachios trees’ growing followed standard cultivation methods and similar agronomic conditions. Two chemometric models were developed using partial least squares-discrimination analysis (PLS-DA). DRIFTS proved unable to statistically differentiate the samples (R2 = 0.96266, Q2 = 0.63152). On the contrary, the disk technique completely differentiated the pistachio samples (R2 = 0.99705, Q2 = 0.97719). The 1720–1800 cm−1 region mostly contributed to the discrimination. The disk-FTIR chemometric model is fast, robust, economical, and environmentally friendly for determining pistachio matrix quality.