Changes in biochemical composition of Ethiopian Coffee arabica with growing region and traditional roasting - Mengesha, Dhaba; Retta, Negussie; Woldemariam, Henock Woldemichael; Getachew, Paulos (Frontiers in Nutrition, 2024)
Updating the biochemical composition of coffee beans across the years is necessary. This is important to understand the vulnerability of coffee toward climate adaptation longitudinally. Accordingly, in this study the influence of growing area and traditional roasting on the biochemical composition of five common Ethiopian Arabica coffee beans collected in the harvest year of 2021/22 were investigated. With an average of 11.34 g/100 g, the Hararge and Jimma coffee beans had the highest crude fat content (p < 0.05). The crude protein content of the five varieties was in the range of 13–15 g/100 g, with respective highest and lowest contents in the (Hararge and Nekemte) and (Sidama and Yirgachefe) coffee beans (p < 0.05). The total phenolic content (TPC) of the coffee beans was in the order of Jimma (46.52) > Nekemte (44.55) > Sidama (44.31) > Hararge (39.02) > Yirgachefe (34.25) mg GAE/100 g. The 50% inhibitory concentration (IC50) of ascorbic acid, coffee bean extract from Jimma and Hararge against 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical was 19.86, 20.22 and 20.02 μg/mL, respectively. The respective highest and lowest caffeine concentration was obtained in the Yirgachefe (10.38) and Hararge (7.55 g/100 g) coffee beans (p < 0.05). The Jimma, Sidama, and Nekemte coffee varieties had the highest chlorogenic acid content of 45 g/100 g (p > 0.05); whereas the lowest content was in Hararge coffee (36.78 g/100 g). While the caffeine concentration did not show significant (p > 0.05) difference, with all the coffee beans the roasting has reduced significantly the TPC, trigonelline and mainly the chlorogenic acid (p < 0.05). These data can update the existing facts on biochemical diversity of coffee beans in the country which can be used for evidence based innovations of climate adaptation in predicting the quality of coffee. Further recommendation of optimizing the traditional coffee processing method is supported from this study.