Abstract
Discrimination of geographical origin can satisfy the demand for food authenticity while decreasing the risk of adulteration in high-quality food products. Rice is among the most important cultivated crops worldwide, providing food for more than half of the Earth's population. The aim of this study is to discriminate the geographical origin of rice cultivated in three regions: Agrinio (Western Greece), Serres, and Chalastra (Central Macedonia). In total, 120 samples were collected from Agrinio and 160 samples from Serres during each cultivation period (2021 and 2022), as well as 90 samples from Chalastra (sampling periods 2023 and 2024). The isotope ratios of the light elements (C, N, and S) were measured using isotope ratio mass spectrometry (IRMS), and the results obtained were analyzed using chemometric techniques, one-way ANOVA, Multivariate Analysis of Variance (MANOVA), and a decision tree algorithm. The mean values of delta permille (δ ‱) calculated from the one-way ANOVA were δ(15)N = 4.64‱, δ(13)C = -26.8‱, and δ(34)S = 3.62 for rice from Agrinio; δ(15)N = 5.34‱, δ(13)C = -26.1‱, and δ(34)S = -0.903 for rice from Serres; and δ(15)N = 5.90‱, δ(13)C = -28‱, and δ(34)S = 4.01 for rice from Chalastra. The decision tree algorithm achieved high accuracy (91.9%), sensitivity (from 86.1% for Agrinio to 97.9% for Serres), and specificity. The results obtained from the decision tree algorithm show that this method could be used to discriminate rice cultivars from the three Greek regions.