Affiliation:
1. Universidade Federal de Viçosa (UFV), Brazil
Abstract
ABSTRACT: This research was performed to ascertain the most suitable Artificial Neural Network (ANN) model to quantify the degree of fraud in powdered milk through the addition of powdered whey via regular standard physicochemical analyses. In this study, an evaluation was done on 103 samples with different quantities of added whey powder to whole milk powder. Using Fourier Transform Infrared Spectroscopy the fat, cryoscopy, total solids, defatted dry extract, lactose, protein and casein were analyzed. The hyperbolic tangent transformation function was used with 45 topologies, and the Holdback and K-fold validation methods were tested. In the Holdback method, 75% of the database was employed for training, while 25% was used for validation. In the K-fold method, the database was categorized into five equal sized subsets, which alternated between training and validation. Of the two methods, the K-fold method was proven to have superior efficiency. Next, analysis was done on three models of multilayer perceptron networks with feedforward architecture. In Model 1, the input layer contained all the physicochemical analyses conducted, in model 2 the casein analysis was excluded, and in model 3 the routine analyses performed for dairy products was done (fat, defatted dry extract, cryoscopy and total solids). From Model 3 an ANN was derived which could satisfactorily predict fraud calculated from using the routine and standard analyses for dairy products, containing 64 nodes in the hidden layer, with R2 of 0.9935 and RMSE of 0.5779 for training, and R2 of 0.9964 and RMSE of 0.4358 for validation.
Subject
General Veterinary,Agronomy and Crop Science,Animal Science and Zoology
Reference21 articles.
1. Quantification of whey in fluid milk using confocal Raman microscopy and artificial neural network.;ALVES DA ROCHA R.;Journal of Dairy Science,2015
2. Classification of cow milk using artificial neural network developed from the spectral data of single- and three-detector spectrophotometers;BEHKAMI S.;Food Chemistry,2019
3. Milk composition of holstein cows: A retrospective study.;BONDAN C.;Ciencia Rural,2018
4. Instrução Normativa no69, de 13 de dezembro de 2006. Critério de avaliação da qualidade do leite in natura, concentrado e em pó, reconstituídos com base no método analítico oficial físico-químico denominado “Índice CMP”.;Diário Oficial da União,2006
5. Instrução Normativa no53 de 1 de outubro de 218. Regulamento Técnico Mercosul Para Fixação de Identidade e Qualidade de Leite em Pó.;Diário Oficial da União,2018
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