A Fuzzy Kansei Engineering for Evaluating Comfort and Sensory Preferences in Robusta Coffee Intake

Abstract

Coffee provides a comforting experience that varies among individuals, making fuzzy logic a suitable method for 
evaluating perceived comfort. This study aimed to assess the comfort experienced after the intake of Robusta coffee 
processed through different postharvest methods (wet, semi-wet, and hybrid), using Kansei Engineering and sensory 
preference analysis. Thirty panellists (13 women, 17 men), aged 17–65 years and regular coffee consumers, participated in 
the study. Descriptive analysis was conducted using XLStat, and comfort modelling was performed using a Mamdani-type 
Fuzzy Inference System via Python Scikit-Fuzzy. The results showed that: (1) significant heart rate changes occurred after 
the intake of hybrid- and semi-wet-processed coffee, while significant blood pressure changes were found only after the 
intake of hybrid-processed coffee; (2) postharvest processing affected Kansei physiological responses, with heart rate and 
oxygen saturation as key indicators of comfort; (3) increased heart rate and decreased oxygen saturation were associated 
with reduced comfort; (4) the intake of hybrid-processed coffee resulted in the highest comfort and sensory preference; and 
(5) aroma showed the strongest association with perceived comfort. These findings suggest that Kansei physiological
responses can be applied as a reliable tool for evaluating comfort in coffee intake. Coffee that induces positive physiological
responses may enhance emotional well-being, providing valuable input for product development aligned with consumers’
affective needs.