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Artificial neural network approach to modelling of metal contents in different types of chocolates

Lidija Jevrić, Sanja Podunavac-Kuzmanović, Jaroslava Švarc-Gajić, Strahinja Kovačević, Ivana Vasiljević, Isidora Kecojević, Evica Ivanović

Abstract


The relationships between the contents of various metals in different types of chocolates were studied using chemometric approach. Chemometric analysis was based on the application of artificial neural networks (ANN). ANN was performed in order to select the significant models for predicting the metal contents. ANN equations, that represent the content of one metal as a function of the contents of other metals were established. The statistical quality of the generated mathematical models was determined by standard statistical measures and cross-validation parameters. High agreement between experimental and predicted values, obtained in the validation procedure, indicated the good quality of the models. The obtained results indicate the possibility of predicting the metal contents in different types of chocolate.


Keywords


chocolate; chemometric analysis; artificial neural networks; metal content

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DOI: http://dx.doi.org/10.17344/acsi.2014.888

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Copyright (c) 2015 Lidija Jevrić, Sanja Podunavac-Kuzmanović, Jaroslava Švarc-Gajić, Strahinja Kovačević, Ivana Vasiljević, Isidora Kecojević, Evica Ivanović

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