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

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.