IMPACT OF THE HARVESTING YEAR ON THE POSSIBLE AUTHENTICATION OF GEOGRAPHICAL ORIGIN OF GREEN COFFEA ARABICA USING PROFILE OF VOLATILES

Abstract

Authentication of coffee is highly required. This study aimed to understand the relative abundance of volatiles of green coffee harvested during two years. Using volatiles (GC-MS) and Linear Discriminant Analysis, we focused on the geographical origin identification. We analyzed samples of green Coffea arabica from Africa, Central America, and South America, harvested in 2018 and the same samples harvested in 2019. A total of 215 different volatiles were detected. Based on their chemical structure and the functional chemical group, they were divided into categories: furan derivates, aldehydes, ketones, alcohols, organic acids, hydrocarbons (alkanes, alkenes, alkynes, aromatic hydrocarbons), terpenoids, heterocyclic compounds, nitriles, amines. Green Arabica contained mostly organic acids and esters, aldehydes, hydrocarbons, and alcohols. We observed significant differences in aromatic hydrocarbons and furan derivates by comparing the volatiles profiles of African coffee beans collected in 2018 and 2019. The profile of Central American samples (both years) was homogenous; thus, no significant differences were observed. The aroma profile of South American coffees had significant differences in aromatic hydrocarbons and alkanes (p-value < 0.05). Rao’s approximation and Bartlett’s test proved a significant difference between 3 continents by applying LDA. More than 94% of the variability between Africa, Central, and South America coffees harvested in 2018 was explained by organic acids and esters, alkenes, aldehydes, and ketones. By adding samples from 2019, LDA calculations reduced input parameters to aldehydes and ketones, organic acids and esters, alkenes, terpenoids, and aldehydes. These appear to be useful for geographical authentication regardless of the year of harvesting.