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Назив: Chemometric prediction of the content of essential metals with potentially toxic effects determined in confectionery products
Аутори: Kovačević, Strahinja 
Lončarević, Ivana 
Pajin, Biljana 
Fišteš, Aleksandar 
Vasiljević, Ivana 
Lazović, Milana
Mrkajić, Danica
Karadžić Banjac, Milica 
Podunavac-Kuzmanović, Sanja 
Датум издавања: 1-дец-2019
Издавач: John Wiley & Sons, Inc.
Часопис: Journal of Food Processing and Preservation
Сажетак: © 2019 Wiley Periodicals, Inc. Waffles, cookies, and crackers are considered to be one of the most often consumed confectionery products. Their complex composition in terms of raw materials used for their production often implies more than one source of heavy metals that end up in the final product. Therefore, the analysis of the heavy metals in these types of products is necessary. The present study deals with the determination of the correlations between the content of essential metals with potential toxic effects (copper, iron, zinc, manganese, and cobalt) determined by inductively coupled plasma-atomic emission spectrometry in waffles, cookies, and crackers collected from the market in Autonomous Province of Vojvodina, Republic of Serbia. The concentrations determined were in the following ranges: Cu (0.299–0.5015 mg/kg d.w.), Fe (3.301–65.35 mg/kg d.w.), Zn (1.962–15.58 mg/kg d.w.), Mn (1.406–27.7 mg/kg d.w.), and Co (0.01–0.26 mg/kg d.w.). The mutual dependence of their concentrations was determined by chemometric linear and nonlinear regression methods which showed to be useful in the fast and easy determination of iron, manganese, zinc, and cobalt concentrations in the studied groups of confectionery products. Practical applications: The practical application of the established chemometric models is reflected in the possibility of predicting the concentration of one metal in waffles, cookies, and crackers based on the concentration of the other one. In this way, the additional experiments can be avoided and the concentration of particular metal can be precisely determined, which is confirmed by the internal and external statistical validation procedures of the established chemometric models.
URI: https://open.uns.ac.rs/handle/123456789/12504
ISSN: 01458892
DOI: 10.1111/jfpp.14289
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