Easy classification of traditional Minas cheeses using artificial neural networks and discriminant analysis

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dc.creatorLeandro Soares Santos
dc.creatorRoberta Magalhães Dias Cardozo
dc.creatorNatália Moreira Nunes
dc.creatorAndreia Braga Inácio
dc.creatorAna Clarissa dos Santos Pires
dc.creatorMaximiliano Soares Pinto
dc.date.accessioned2022-03-31T12:33:16Z
dc.date.accessioned2025-09-09T00:48:01Z
dc.date.available2022-03-31T12:33:16Z
dc.date.issued2017-11
dc.description.sponsorshipOutra Agência
dc.identifier.doihttps://doi.org/10.1111/1471-0307.12370
dc.identifier.issn14710307
dc.identifier.urihttps://hdl.handle.net/1843/40656
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofInternational Journal of Dairy Technology
dc.rightsAcesso Restrito
dc.subjectQueijo-de-minas
dc.subjectQuimiometria
dc.subjectRedes neurais
dc.titleEasy classification of traditional Minas cheeses using artificial neural networks and discriminant analysis
dc.typeArtigo de periódico
local.citation.epage498
local.citation.issue4
local.citation.spage492
local.citation.volume70
local.description.resumoThe classification of traditional Minas cheese (TMC) from different regions is important to ensure authenticity. Different chemometric approaches were used to discriminate TMCs from three different regions (Serro, Canastra and Araxá) of Minas Gerais, Brazil. The data obtained from the literature were used to develop an artificial neural network and to obtain linear discriminant functions, which were able to classify 100% of cheeses from different regions as a function of physico-chemical composition. Both chemometric methods can be very useful tools to discriminate TMC from different regions based on physico-chemical data which are obtained in a very quick and simple way.
local.publisher.countryBrasil
local.publisher.departmentICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
local.publisher.initialsUFMG
local.url.externahttps://onlinelibrary.wiley.com/doi/10.1111/1471-0307.12370

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