Review of the contributions of some statistical methodologies related to the quality of specialty coffee
DOI:
https://doi.org/10.25186/.v19i.2250Abstract
Sensory perception involves psychological issues and cognitive skills. The greatest individual differences are observed in sensory experiments, since tasters’ senses assign positive or negative attributes to a product, which are numerically represented by means of a hedonic scale. Thus, when considering statistical methodologies to evaluate the results, the question becomes a challenge to answer because its application requires presumptions that are not always met. In addition, answering a single objective limits the search for the state of the art, contextualized in the exploration of other results that arises from new applied methodologies. Based on this argument, this study aims to present a methodological review that presents the results and contributions of different statistical techniques, addressed by mixing distributions, resampling techniques to build indices robust to outliers, machine learning to I'm prove multivariate classifiers and visualization techniques of the data. These are derived from a single database, which references analyses of the quality of specialty coffees with denomination of known origins that are evaluated by heterogeneous groups of tasters. Based on the knowledge base of the researchers and a review of the literature, the aforementioned methodological procedures are applied, and their advantages and aggregate results are compared to the understanding of the behavioral attitudes that lead to the distinction of the quality of the coffees evaluated.
Key words: Taster; attributes; data mining; models; machine learning
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