Yvonne Roman-Maldonado, Ana L. Gutiérrez-Salomón, Judith Jaimez-Ordaz, Sergio E. García-Barrón & Jahir A. Barajas-Ramírez. Drivers of liking to predict consumers? acceptance of local coffee from indigenous Mexican regions. Eur Food Res Technol. 2022, 248, 467?475. https://doi.org/10.1007/s00217-021-03892-x
The objective of this study was to identify drivers of liking for local coffees cultivated in three indigenous regions from Hidalgo, Mexico. A conventional descriptive analysis was conducted to identify the sensory characteristics; 2-AFC discriminative test was performed to determine differences in acidity and bitter among coffee beverages. In addition, overall liking of four coffees was evaluated by 145 coffee consumers using a 9-point hedonic scale. Coffees from Sierra Gorda and Sierra Alta regions presented higher acidity than coffees from Sierra Otomí-Tepehua and coffees from Sierra Alta region were the most bitter (d??=?2.45, p?0.001). Partial Least Square (PLS) regressions allowed the identification of drivers of liking for three clusters: vanilla-smell and nutty aroma were the main drivers of liking for cluster 1; astringency, acidity and bitterness for cluster 2 and roasted smell and taste for cluster 3. The drivers of disliking were green, earthy and roasted notes for cluster 2. This is the first report of drivers of liking of local coffee from the Mexican indigenous regions studied. This information can be used to evaluate the native consumer?s acceptance for coffee from indigenous regions and to generate strategies to improve coffee processing for desirable consumer-driven sensory attributes.