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http://hdl.handle.net/1843/40656| Tipo: | Artigo de Periódico |
| Título: | Easy classification of traditional Minas cheeses using artificial neural networks and discriminant analysis |
| Autor(es): | Leandro Soares Santos Roberta Magalhães Dias Cardozo Natália Moreira Nunes Andreia Braga Inácio Ana Clarissa dos Santos Pires Maximiliano Soares Pinto |
| Resumen: | 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 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. |
| Asunto: | Queijo-de-minas Quimiometria Redes neurais |
| Idioma: | eng |
| País: | Brasil |
| Editor: | Universidade Federal de Minas Gerais |
| Sigla da Institución: | UFMG |
| Departamento: | ICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS |
| Tipo de acceso: | Acesso Restrito |
| Identificador DOI: | https://doi.org/10.1111/1471-0307.12370 |
| URI: | http://hdl.handle.net/1843/40656 |
| Fecha del documento: | nov-2017 |
| metadata.dc.url.externa: | https://onlinelibrary.wiley.com/doi/10.1111/1471-0307.12370 |
| metadata.dc.relation.ispartof: | International Journal of Dairy Technology |
| Aparece en las colecciones: | Artigo de Periódico |
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