Technical note: At-line prediction of mineral composition of fresh cheeses using near-infrared technologies.

Autor:	Manuelian CL; Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy., Currò S; Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy., Visentin G; Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy., Penasa M; Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy., Cassandro M; Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy., Dellea C; Department of Research and Development, Granarolo Group, via Cadriano 27/2, 40127 Bologna (BO), Italy., Bernardi M; Department of Research and Development, Granarolo Group, via Cadriano 27/2, 40127 Bologna (BO), Italy., De Marchi M; Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy. Electronic address: massimo.demarchi@unipd.it.
Jazyk:	angličtina
Zdroj:	Journal of dairy science [J Dairy Sci] 2017 Aug; Vol. 100 (8), pp. 6084-6089. Date of Electronic Publication: 2017 Jun 16.
DOI:	10.3168/jds.2017-12634
Abstrakt:	Milk and dairy products are important sources of macro- and trace elements for human health. However, fresh cheeses usually have a lower mineral content than other cheeses, and this makes mineral prediction more difficult. Although mineral prediction in several food matrices using infrared spectroscopy has been reported in the literature, very little information is available for cheeses. The present study was aimed at developing near-infrared reflectance (NIR, 866-2,530 nm) and transmittance (NIT, 850-1,050 nm) spectroscopy models to predict the major mineral content of fresh cheeses. We analyzed samples of mozzarella (n = 130) and Stracchino (n = 118) using reference methods and NIR and NIT spectroscopy. We developed prediction models using partial least squares regression analysis, and subjected them to cross- and external validation. Average Na content was 0.15 and 0.22 g/100 g for mozzarella and Stracchino, respectively. The NIR and NIT spectroscopy performed similarly, with few exceptions. Nevertheless, none of the prediction models was accurate enough to replace the current reference analysis. The most accurate prediction model was for the Na content of mozzarella cheese using NIT spectroscopy (coefficient of determination of external validation = 0.75). We obtained the same accuracy of prediction for P in Stracchino cheese with both NIR and NIT spectroscopy. Our results confirmed that mineral content is difficult to predict using NIT and NIR spectroscopy. (Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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