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.

中文翻译：

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中红外光谱结合化学计量学对γ射线照射的榛子样品的剂量依赖性区分

伽马射线被用作食品保存方法。众所周知，高剂量辐射会引起一些结构和功能上的损害。因此，高剂量辐照食品样品的检测是国际贸易中的关键问题。这项工作的目的是评估傅里叶变换红外（FTIR）光谱用于区分γ的潜力-使用多变量统计分析，即主成分分析（PCA）和层次聚类分析（HCA），以较低剂量（1.5 kGy）和较高剂量（3 kGy和10 kGy）辐照的榛子。这项研究表明，可以使用基于光谱差异的无监督方法将高剂量辐照的榛子样品与低剂量辐照的榛子样品区分开。此外，还实现了剂量依赖性鉴别。总之，FTIR光谱技术与多元统计分析相结合，具有开发可靠且快速的方法来分离高剂量辐照食品样品的潜力。