Milk fraud by the addition of whey using an artificial neural network

ABSTRACT: The adulteration of milk by the addition of whey is a problem that concerns national and international authorities. The objective of this research was to quantify the whey content in adulterated milk samples using artificial neural networks, employing routine analyses of dairy milk samples...

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Main Authors: Vitor Augusto Condé, Gerson de Freitas Silva Valente, Eliene Carvalho Minighin
Format: Article
Language:English
Published: Universidade Federal de Santa Maria
Series:Ciência Rural
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782020000700453&lng=en&tlng=en
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author Vitor Augusto Condé
Gerson de Freitas Silva Valente
Eliene Carvalho Minighin
author_facet Vitor Augusto Condé
Gerson de Freitas Silva Valente
Eliene Carvalho Minighin
author_sort Vitor Augusto Condé
collection DOAJ
description ABSTRACT: The adulteration of milk by the addition of whey is a problem that concerns national and international authorities. The objective of this research was to quantify the whey content in adulterated milk samples using artificial neural networks, employing routine analyses of dairy milk samples. The analyses were performed with different concentrations of whey (0, 5, 10, and 20%), and samples were analyzed for fat, non-fat solids, density, protein, lactose, minerals, and freezing point, totaling 164 assays, of which 60% were used for network training, 20% for network validation, and 20% for neural network testing. The Garson method was used to determine the importance of the variables. The neural network technique for the determination of milk fraud by the addition of whey proved to be efficient. Among the variables of highest relevance were fat content and density.
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spelling doaj.art-1aa2b43c05f748988a8fcf56b1e20a772022-12-21T18:57:51ZengUniversidade Federal de Santa MariaCiência Rural0103-84781678-459650710.1590/0103-8478cr20190312S0103-84782020000700453Milk fraud by the addition of whey using an artificial neural networkVitor Augusto CondéGerson de Freitas Silva ValenteEliene Carvalho MinighinABSTRACT: The adulteration of milk by the addition of whey is a problem that concerns national and international authorities. The objective of this research was to quantify the whey content in adulterated milk samples using artificial neural networks, employing routine analyses of dairy milk samples. The analyses were performed with different concentrations of whey (0, 5, 10, and 20%), and samples were analyzed for fat, non-fat solids, density, protein, lactose, minerals, and freezing point, totaling 164 assays, of which 60% were used for network training, 20% for network validation, and 20% for neural network testing. The Garson method was used to determine the importance of the variables. The neural network technique for the determination of milk fraud by the addition of whey proved to be efficient. Among the variables of highest relevance were fat content and density.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782020000700453&lng=en&tlng=enartificial intelligenceglycomacropeptideannwheyadulterationfraud
spellingShingle Vitor Augusto Condé
Gerson de Freitas Silva Valente
Eliene Carvalho Minighin
Milk fraud by the addition of whey using an artificial neural network
Ciência Rural
artificial intelligence
glycomacropeptide
ann
whey
adulteration
fraud
title Milk fraud by the addition of whey using an artificial neural network
title_full Milk fraud by the addition of whey using an artificial neural network
title_fullStr Milk fraud by the addition of whey using an artificial neural network
title_full_unstemmed Milk fraud by the addition of whey using an artificial neural network
title_short Milk fraud by the addition of whey using an artificial neural network
title_sort milk fraud by the addition of whey using an artificial neural network
topic artificial intelligence
glycomacropeptide
ann
whey
adulteration
fraud
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782020000700453&lng=en&tlng=en
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