Dose-Dependent Differentiation of Gamma-Irradiated Hazelnut Samples by Mid-Infrared Spectroscopy Coupled with Chemometrics

Abstract

Gamma irradiation is used as a food preservation method. It is known that high-dose irradiation causes several structural and functional damages. Therefore, the detection of high-dose irradiated food samples is a critical issue in international trade. The objective of this work is to evaluate the potential of Fourier transform infrared (FTIR) spectroscopy for the differentiation of γ-irradiated hazelnuts at higher doses (3 kGy and 10 kGy) from the lower (1.5 kGy) and nonirradiated ones using multivariate statistical analysis, namely, principal component analysis (PCA) and hierarchical cluster analysis (HCA). This study showed that high-dose irradiated hazelnut samples can be clearly differentiated from the low-dose irradiated samples using unsupervised methods based on the spectral differences. Furthermore, dose-dependent discrimination was also achieved. In conclusion, FTIR spectroscopy combined with multivariate statistical analysis has potential for the development of a reliable and fast methodology for separation of high-dose irradiated food samples.