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Climatic conditions, genotypes, and post-harvest processing methods influence coffee quality. Microbial fermentation during post-harvest processing has sparked researchers' interest due to the modulation of the sensory characteristics of coffee. However, the influence of microbial fermentation on different coffee genotypes has been little investigated. The objective of this study was to evaluate the chemical and sensory changes of Coffea arabica cultivars caused by different post-harvest processing and fermentations. Catucaí 785 and Catucaí Açú cultivars had better sensory evaluation than the Arara cultivar in the two years of sampling. However, dry fermentation proved to be a promising alternative to improve the sensory analysis of the Arara cultivar. Inoculation of Saccharomyces pastorianus yielded positive results in the chemical and sensory of the Catucaí Açú cultivar. Each coffee genotype is capable of expressing unique sensory and chemical attributes depending on the different post-harvest processing and fermentations applied. [ABSTRACT FROM AUTHOR]

[Display omitted] • HS-SPME-GC/MS and multivariate calibration aid with the sensory analysis of coffee. • The main volatile predictors of coffee quality have been identified. • The models showed good prediction, with RMSEp ranging from 0.20 to 0.25. • 1-Nonadecene was first reported as an impact compound in coffee. The chemical complexity of coffee influences the sensory evaluation of the beverage, the main method used to define the quality of the coffee. In view of the subjectivity that method offers, we propose the association of an instrumental method with multivariate calibration (PLS and GA-SVR) to predict the quality of arabica coffee as support for sensory analysis. Arabica coffee samples were submitted to sensory evaluation using the Specialty Coffee Association (SCA) protocol and HS-SPME-GC/MS analysis. The models presented RMSEp results from 0.20 to 0.25, within the evaluation range the quality levels of sensory attributes (0.25). For the fragrance/aroma attribute, a value of R2p equal to 0.8503 was reached. 15 volatile compounds were identified as responsible for predicting the quality of arabica coffee, among which, 1-nonadecene was first reported as an impact compound in the prediction of important sensory attributes. [ABSTRACT FROM AUTHOR]