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The relationships between the contents of various metals (Cu, Ni, Pb and Al)   in 38 different milk chocolate samples were studied using a chemometric   approach. The chemometric expressions were generated using a training set of   25 chocolate samples and the predictive ability of the resulting models was   evaluated against a test set of 13 chocolate samples. The chemometric   analysis was based on the application of multiple linear regression analysis   (MLR). MLR was performed in order to select the significant models for   predicting the metal contents. The MLR equations that represent the content   of one metal as a function of the contents of other metals were established.   High agreement between experimental and predicted values, obtained in the   validation procedure, indicated the good quality of the models. It enables   the researchers to establish reliable relationships between the contents of   various metals which can be used for their prediction in different types of   chocolate prior to their analysis. This can reduce the trial-and-error   element and experimental costs in the production.[Projekat Ministarstva nauke   Republike Srbije, br. 31055, br. 172012 i br. 172014

Chemometric analysis of metal contents in different types of chocolates