Abstract

ESPINOZA ROMANO, Vivian; FIGUEROA CAMACHO, Valeria Rafaela  and  ALDUNATE FLORES, Soledad Adriana. Analysis of Sensory Attributes that Influence the Perception of Coffee Quality through Multivariate Technique Main Components. RevActaNova. [online]. 2024, vol.11, n.4, pp.353-372.  Epub Nov 30, 2024. ISSN 1683-0789.  https://doi.org/10.35319/acta-nova.202425.

This study analyzes the perception of coffee quality using Principal Component Analysis (PCA), with the aim of identifying the key sensory factors that influence consumer satisfaction and at the same time characterizing some coffee farms based on these attributes. For data collection, the online platform Kaggle was used, and surveys were applied to 207 farms in 22 coffee producing and consuming countries, including Colombia, Brazil, Guatemala and Ethiopia. The research focused on the Coffea arabica L. variety, due to its wide production and differentiating characteristics in flavor, cultivation altitude and caffeine content. The database was provided by the Coffee Quality Institute (CQI) and was processed using SPSS vs. 28 and R Studio vs. 2022.02.0.

The PCA allowed reducing the complexity of the variables, highlighting two main components that explain 88.89% of the variability. The first component (83.11%) groups the most valued sensory attributes, while the second (5.78%) adds complementary information. A strong correlation was identified between flavor and quality perception (r = 0.878), being the most determining attribute. Aftertaste and balance also have a positive influence, although with less impact. In contrast, acidity and body have a lower correlation but are still relevant factors. Likewise, coffee farms in certain countries were characterized based on sensory variables.

The findings highlight the importance of improving the sensory profile of coffee, especially in terms of flavor and balance, to increase consumer satisfaction; these can be used by coffee shops and producers to develop strategies that optimize the customer experience and strengthen their positioning in the market.

In addition, the methodology used demonstrates the usefulness of PCA in the analysis of sensory perceptions, allowing for the development of more precise approaches to improve coffee quality and customer experience.

Keywords : Principal component analysis; sensory analysis; coffee.

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