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Easy classification of traditional Minas cheeses using artificial neural networks and discriminant analysis
Author(s) -
Santos Leandro S,
Cardozo Roberta M D,
Nunes Natália Moreiria,
Inácio Andréia B,
Pires Ana Clarissa dos S,
Pinto Maximiliano S
Publication year - 2017
Publication title -
international journal of dairy technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.061
H-Index - 53
eISSN - 1471-0307
pISSN - 1364-727X
DOI - 10.1111/1471-0307.12370
Subject(s) - linear discriminant analysis , artificial neural network , pattern recognition (psychology) , discriminant function analysis , artificial intelligence , discriminant , mathematics , computer science , statistics
The classification of traditional Minas cheese ( TMC ) from different regions is important to ensure authenticity. Different chemometric approaches were used to discriminate TMC s 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.