Discrimination between arabica and robusta coffees using NIR-integrating sphere spectroscopy coupled with hierarchical clustering analysis

Abstract

In Indonesia, coffee farmers preferred to produce arabica and robusta coffee. Regarding its superior quality and commercial values, now the demand for specialty arabica and fine robusta coffee is increasing. In this research, discrimination between the two coffees was evaluated using NIR-integrating sphere spectroscopy coupled with the hierarchical clustering analysis (HCA) method. NIR spectral data in the region of 1175-1650 nm was measured using a portable fiber optic NIR spectrometer equipped with an integrating sphere from Ocean Optics (NIR-Quest, Ocean Optics, USA). Arabica (n=10) and robusta (n=10) ground roasted coffee (with mesh 50) was prepared as samples. The principal component analysis (PCA) and hierarchical cluster analysis (HCA) were utilized in data analysis to discriminate between the specialty arabica and fine robusta coffee samples. The PCA and HCA results confirmed the good separation between the two coffees with arabica and robusta coffee samples were grouped in two distinct clusters. This result reveals that NIR-integrating sphere spectroscopy seems to be a potential analytical method dedicated to the discrimination of arabica and robusta coffee with minimum sample preparation.