Stable isotope and trace element analyses with non-linear machine-learning data analysis improved coffee origin classification and marker selection.
Journal:
Journal of the science of food and agriculture
Published Date:
Mar 25, 2023
Abstract
BACKGROUND: This study investigated the geographical origin classification of green coffee beans from continental to country and regional levels. An innovative approach combined stable isotope and trace element analyses with non-linear machine learning data analysis to improve coffee origin classification and marker selection. Specialty green coffee beans sourced from three continents, eight countries, and 22 regions were analyzed by measuring five isotope ratios (δ C, δ N, δ O, δ H, and δ S) and 41 trace elements. Partial least squares discriminant analysis (PLS-DA) was applied to the integrated dataset for origin classification.