Navegando por Autor "Resende, Mariana"

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An index to evaluate the acceptance of specialty coffees in consumer groups
(Associação Brasileira de Engenharia Agrícola, 2020) Resende, Mariana; Cirillo, Marcelo Â.; Borém, Flávio M.
Numerous factors are related to the individual sensory perception of consumers, which makes it impossible to adapt a model that explains their behavior. In this context and given the scarcity of statistical indexes that evaluate preferences for specialty coffees, new statistical methods should be studied. To this end, our study aimed to create an index that measures the acceptance of specialty coffees. The index was built considering the fit of regression models as a function of principal component scores. Validation was done by significance tests, whose probabilities were obtained by bootstrapping, considering the main measures used in diagnosing outliers as weights, with application to real data from different consumer groups. The coffee varieties Acaia and Bourbon were discriminated in relation to altitude. In conclusion, the index was adequate for the analysis and characterization of specialty coffees grown at different altitudes.
Case study of modeling covariance between external factors and sensory perception of coffee
(Universidade Federal de Lavras, 2023-08-18) Resende, Mariana; Borém, Flávio Meira; Cirillo, Marcelo Ângelo
Analysis and inference of sensory perceptions in coffee beverages are complex due to numerous random causes intrinsic to productivity, preparation, and especially consumer and/or taster subjectivity. In this context, latent variables often composed of a combination of other observed variables are discarded from conventional analyses. Following this argument, this study aimed to propose a model of structural equations applied to a database, geographical indication of coffees in Serra da Mantiqueira, with a methodological contribution characterized by inclusion of a treatment effect, contemplated by different altitudes at which coffees were produced. From the methodology used, a covariance structure was estimated, and used in another statistical methodology to discriminate the effects. It is concluded that the proposed model proved to be advantageous for allowing the analysis of the relationship of latent variables, production and environmental variations, which are not considered in a sensorial analysis, and showed that, in fact, they influence the sensorial perception, for the coffees produced in the Serra da Mantiqueira region. The correlation structure generated from the covariance matrix adjusted by the model resulted in estimates that could be used in other statistical methodologies more appropriate to discriminate the effects, exemplifying the use of principal components.