Utilizing HS-SPME-GC-MS for Regional Classification of Ethiopian Green Coffee Beans: An In-Depth Analysis of Volatile Compounds

Abstract

This study is intended to fingerprint the volatile aroma compounds of green Arabica coffee beans from different regions of Ethiopia by using headspace solid-phase microextraction coupled with gas chromatography and mass spectroscopy (HS-SPME-GC-MS) and a chemometrics approach. Green Arabica coffee samples from various regions of the country were successfully differentiated based on their volatile fractions and agroecological characteristics. A total of 23 volatiles were identified, including aldehydes (39%), terpenes (26%), alcohols (17.3%), ketones (4.4%), acids (4.4%), esters (4.4%), and thiazole (4.4%). Supervised partial least-squares discriminant analysis effectively distinguished the coffees, identifying major volatile metabolites contributing to sample discrimination. Variations in volatile compounds were attributed to differences in the coffee-growing altitude, annual rainfall, and daily average temperatures. This study has the advantage of being able to differentiate Ethiopian green Arabica coffee beans from different regions of the country using volatile metabolite profiles, which are highly related to their quality, and this could possibly be used as an intellectual property tool to protect and authenticate the Ethiopian green bean. Moreover, we suggest potential applications for distinguishing them from similar products. In conclusion, combining HS-SPME-GC-MS-based volatile compound analysis with a chemometrics approach offers a valuable tool for discerning the geographical origins of Ethiopian Arabica beans.