Prediction of consumer acceptance in some thermoprocessed food by physical measurements and multivariate modeling

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorNunes, Cleiton A.-
Autor(es): dc.creatorSouza, Vanessa R.-
Autor(es): dc.creatorRodrigues, Jéssica F.-
Autor(es): dc.creatorPinheiro, Ana Carla M.-
Autor(es): dc.creatorFreitas, Matheus P.-
Autor(es): dc.creatorBastos, Sabrina C.-
Data de aceite: dc.date.accessioned2026-02-09T12:27:18Z-
Data de disponibilização: dc.date.available2026-02-09T12:27:18Z-
Data de envio: dc.date.issued2018-07-09-
Data de envio: dc.date.issued2018-07-09-
Data de envio: dc.date.issued2017-10-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/29578-
Fonte completa do material: dc.identifierhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jfpp.13178-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1161671-
Descrição: dc.descriptionConsumer acceptances for French bread, fish bread, and roasted coffees were calibrated against physical measurements of those products using Multiple Linear Regression. The models obtained were then validated and tested using the widespread used methods of cross‐validation, y‐randomization and external validation. In all cases, multivariate models presented R2 for calibration greater than.9, which was superior to those univariate ones. For the French bread analysis, the multivariate model performed well and the length of the cut on bread surface is the parameter that most strongly influenced this model; on the other hand, a large width of the cut on bread surface would greatly contribute to a lower acceptance. The model for predicting the acceptance of the fish bread also showed a good performance; the bulkier fish breads received a better acceptance. An efficient model was also obtained for the data set of roasted coffee; redder coffees were more accepted.-
Idioma: dc.languageen-
Publicador: dc.publisherWiley-
Direitos: dc.rightsrestrictAccess-
???dc.source???: dc.sourceJournal of Food Processing and Preservation-
Palavras-chave: dc.subjectThermoprocessed food - Consumer acceptance-
Palavras-chave: dc.subjectMultiple linear regression-
Palavras-chave: dc.subjectAlimentos termoprocessados - Aceitação do consumidor-
Palavras-chave: dc.subjectRegressão linear múltipla-
Título: dc.titlePrediction of consumer acceptance in some thermoprocessed food by physical measurements and multivariate modeling-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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