Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/55798
Title: Análise de correspondência canônica não linear com ênfase na descrição da redundância da variabilidade de dados sensoriais de blends de cafés com diferentes variedades
Other Titles: Nonlinear canonical correspondence analysis with emphasis on the description of the redundancy of the variability of sensory data of coffee blends with different varieties
Authors: Cirillo, Marcelo Ângelo
Silva, Jackelya Araújo da
Silva, Augusto Maciel da
Freire, Evelise Roman Corbalan Gois
Keywords: Cafés especiais
Café comercial
Regressão polinomial multivariada
Blendas
Redução de dimensionalidade
Avaliadores sensoriais
Specialty coffees
Commercial coffee
Multivariate polynomial regression
Blends
Dimensionality reduction
Sensory assessors
Issue Date: 17-Jan-2023
Publisher: Universidade Federal de Lavras
Citation: SANTOS, H. S. P. T. Análise de correspondência canônica não linear com ênfase na descrição da redundância da variabilidade de dados sensoriais de blends de cafés com diferentes variedades. 2022. 79 p. Dissertação (Mestrado em Estatística e Experimentação Agropecuária)–Universidade Federal de Lavras, Lavras, 2022.
Abstract: The formulation of coffee blends is of paramount importance for the coffee industry, as it provides the final product with an expressive ability to compete in the market and adds sensory attributes that complement the consumption experience. Through redundancy analysis and canonical correspondence analysis, it is possible to study the relationships between a set of sensory notes and a set of blends with different proportions of coffee variety through multivariate linear regression models. However, it is unrealistic to assume that such sensory responses are given in a linear fashion in relation to the formulation of blends, since some types of coffee have greater weight in the sensory evaluation (quadratic terms) and the effect of blends must be considered (term of interaction). With this motivation, this work aims to propose the use of redundancy analysis and nonlinear correspondence analysis through multivariate polynomial regression to evaluate the acceptance of different varieties of coffee blends. The blends were formulated from proportions of specialty coffee varieties such as Arabica, Yellow Bourbon and Acaiá, Conilon coffee and a commercial brand of roasted coffee. The blends were evaluated receiving scores that ranged from 0 to 10 for the qualitative characteristics of the drink: flavor, bitterness, acidity, body and final note. The results showed significant gains in the percentage of total explained variance in the nonlinear models in relation to the linear ones.
URI: http://repositorio.ufla.br/jspui/handle/1/55798
Appears in Collections:Estatística e Experimentação Agropecuária - Mestrado (Dissertações)



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