Journal
INTERNATIONAL JOURNAL OF DAIRY TECHNOLOGY
Volume 70, Issue 4, Pages 492-498Publisher
WILEY
DOI: 10.1111/1471-0307.12370
Keywords
Chemometrics; Physico-chemical composition; Cheese classification; Linear discriminant analysis; Neural networks
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Funding
- Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG)
- Fundacao de Amparo a Pesquisa do Estado da Bahia (FAPESB)
- Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ)
- Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)
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The 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 Araxa) 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.
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