Exploratory analysis of south American wines using Artificial intelligence

Abstract

In this work, microwave-induced plasma optical emission spectrometry was applied for multielement determination in South American wine samples. The analytes were determined after acid digestion of 47 samples of Brazilian and Argentinian wines. Then, logistic regression, support vector machine, and decision tree for exploratory analysis and comparison of these algorithms in differentiating red wine samples by region of origin were carried out. All wine samples were classified according to their geographical origin. The quantification limits (mg L−1) were P: 0.06, B: 0.08, K: 0.17, Mn: 0.002, Cr: 0.002, and Al: 0.02. The accuracy of the method was evaluated by analyzing the wine samples by ICP OES for results’ comparison. The concentrations in mg L−1 found for each element in wine samples were as follows: Al (< 0.02–1.82), Cr (0.15–0.50), Mn (< 0.002–0.8), P (97–277), B (1.7–11.6), Pb (< 0.06–0.3), Na (8.84–41.57), and K (604–1701), in mg L−1.