Post-harvest processing (PHP) is a key determinant of coffee quality, flavor profile, and commercial classification.
A recent study by a group of British researchers (Santos-Rivera et al., 2025) aimed to use near-infrared (NIR) spectroscopy, combined with chemometrics, for the rapid, non-destructive classification of coffee based on its PHP method.
Specifically, the study distinguished between seven distinct PHP categories—Alchemy, Anaerobic Processing (Deep Fermentation), Dry-Hulled, Honey, Natural, Washed, and Wet-Hulled—encompassing 20 different processing protocols carried out under varying environmental and fermentation conditions.
NIR spectra (350–2500 nm) from 524 samples of green Arabica coffee were analyzed using PCA-LDA models. These models achieved classification accuracies of up to 100% for underrepresented categories and high performance (91–95%) for the dominant PHP groups when tested on an independent dataset.
These findings demonstrate that NIR spectroscopy can detect subtle chemical characteristics associated with different PHP techniques, providing a scalable tool for quality control, fraud prevention, and traceability within global coffee supply chains.
Bibliographic references: M. Santos-Rivera et al., Spectroscopy Journal, 3, 2025, 1-17.
