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The growing global trading market for specialty coffee increases the need for better coffee quality evaluation methods. Several Arabica coffees in Indonesia have high commercial value. For this reason, the development of analytical methods with high sensitivity and accuracy for detection of its adulteration was important. This research evaluated the potential of UV-visible spectroscopy and partial least squares discriminant analysis (PLS-DA) for determining the geographic origin of three specialty coffees (Gayo, Kintamani and Wamena) in Indonesia. In this research, 296 coffee samples from three different origins (Gayo, Kintamani and Wamena) were used. All coffee samples were ground using a home-coffee-grinder. We sieved all coffee samples through a nest of US standard sieves (mesh number of 40) on a Meinzer II sieve shaker for 10 minutes to obtain a particle size of 420 µm. All samples were extracted with distilled water and then filtered. For each sample, 3 mL of extracted sample then was pipetted into 10 mm cuvettes for spectral data acquisition. The spectral data were acquired using a Genesys 10s UV-visible spectrometer in the range of 190-1100 nm. A PLS-DA classification model was estimated to classify the origin of specialty coffees by their UV-visible spectra. The best PLS-DA model accurately classified the specialty coffee samples of the prediction sample set with prediction ability of 100% of correct classification for Gayo, Kintamani and Wamena, respectively. The results demonstrate that UV-visible spectroscopy coupled with PLS-DA provides a sensitive and accurate analytical method to distinguish ground roasted coffee samples geographically.

The potential of UV-visible spectroscopy and chemometrics for determination of geographic origin of three specialty coffees in Indonesia