Application of Neural Classifier for Automated Detection of Extraneous Water in Milk

J. Daunoras, V. Gargasas, A. Knys, G. Narvydas


The investigation results of application of neural classifier for automated detection of extraneous water in milk are presented. Advantages and shortcomings of analytical methods that are currently used to determine extraneous water in milk are discussed. The structures of proposed system of milk sample analysis and analytical automated milk quality control system are presented. Using laboratory milk testing results optimal structure of neural classifier for detecting extraneous water in milk sample with minimum error is selected and proofed. The results permit us to affirm that the proposed method enables detection of extraneous water in milk sample with desired accuracy and minimizes possibility of operator error as the detection of fact that extraneous water is present in sample is carried out by the control system, not by the operator judging by sample freezing point depression. Ill. 3, bibl. 5, tabl. 2 (in English; abstracts in English and Lithuanian).

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Print ISSN: 1392-1215
Online ISSN: 2029-5731