Chemometric authentication of the organic status of milk on the basis of trace element content. (1st February 2018)

• Record Type: Journal Article
• Authors: Rodríguez-Bermúdez, R.; López-Alonso, M.; Miranda, M.; Fouz, R.; Orjales, I.; Herrero-Latorre, C.
• Is Part Of: Food chemistry. Volume 240(2018)
• Page Start: 686
• Page End: 693
• Publication Date: 2018-02-01
• Subjects: Milk -- Essential trace and toxic elements -- Chemometric analysis -- Organic and conventional farming -- ICP-MS; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2017.08.011
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: We used chemometric analysis to differentiate between organic and conventional milk. We designed mathematical models to predict type of milk based on metal content. The prediction model is capable of identifying types of milk in almost 95% of cases. The method is valuable for initial verification of organic products. Abstract: The objective of this study was to develop a method for authenticating organic milk samples in North Spain on the basis of its trace mineral composition. Fourteen elements in 98 samples were determined by inductively coupled plasma mass spectrometry. Although concentrations of Co, Cr, Cu, I, Se and Zn where statistically higher in conventional milk and As in organic, none of these elements by itself was able to discriminate between organic and conventional milk. The chemical data was examined by principal component analysis and cluster analysis, revealing a natural separation between organic and conventional milk. In a second step, several supervised pattern recognition techniques were used to construct mathematical models for predicting the type of milk (organic or conventional) based on the metal content. The results proved that the model constructed using the artificial neural network is capable of correctly identifying the type of milk in almost 95% of cases.