Multivariate Data Analysis for the Discrimination of Ions in Instant Coffee Samples

Coffee is one of the most consumed beverages worldwide, being an integral part of culture, economy, and daily life. Soluble coffee stands out for its practicality and wide acceptance in the market. Its chemical composition can vary according to the origin of the beans, processing, and storage conditions, directly affecting its quality and authenticity. In this context, the determination and discrimination of ions in soluble coffee samples are relevant strategies for quality control and detection of possible adulterations. In this study, five brands of soluble coffee marketed in Vitória da Conquista, Brazil, were analyzed by ion chromatography (IC) for the quantification of K⁺, Na⁺, Mg²⁺, NH₄⁺ and Ca²⁺. Multivariate data analysis, using principal component analysis (PCA), was applied to explore the ionic profiles. Two principal components explained 75.86% of the total variance. PC1 (48.23%) was dominated by K⁺, Na⁺ and Mg²⁺, while PC2 (27.63%) was mainly influenced by NH₄⁺ and Ca²⁺. Score plots revealed two distinct groups of soluble coffee samples, reflecting heterogeneity in ionic composition and highlighting differences among manufacturers. The results demonstrate that IC combined with exploratory data analysis is effective for the discrimination of soluble coffee samples, contributing to quality monitoring, authenticity verification, and food safety.