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Accuracy and biases in predicting the chemical and physical traits of many types of cheeses using different visible and near-infrared spectroscopic techniques and spectrum intervals.

Authors
  • Stocco, Giorgia1
  • Cipolat-Gotet, Claudio2
  • Ferragina, Alessandro3
  • Berzaghi, Paolo4
  • Bittante, Giovanni3
  • 1 Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy; Department of Veterinary Science, University of Parma, Via del Taglio 10, 43126 Parma, Italy. Electronic address: [email protected] , (Italy)
  • 2 Department of Veterinary Science, University of Parma, Via del Taglio 10, 43126 Parma, Italy. , (Italy)
  • 3 Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy. , (Italy)
  • 4 Department of Animal Medicine, Production and Health (MAPS), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy. , (Italy)
Type
Published Article
Journal
Journal of Dairy Science
Publisher
American Dairy Science Association
Publication Date
Nov 01, 2019
Volume
102
Issue
11
Pages
9622–9638
Identifiers
DOI: 10.3168/jds.2019-16770
PMID: 31477307
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Near-infrared spectroscopy (NIRS) has been widely used to determine various composition traits of many dairy products in the industry. In the last few years, near-infrared (NIR) instruments have become more and more accessible, and now, portable devices can be easily used in the field, allowing the direct measurement of important quality traits. However, the comparison of the predictive performances of different NIR instruments is not simple, and the literature is lacking. These instruments may use different wavelength intervals and calibration procedures, making it difficult to establish whether differences are due to the spectral interval, the chemometric approach, or the instrument's technology. Hence, the aims of this study were (1) to evaluate the prediction accuracy of chemical contents (5 traits), pH, texture (2 traits), and color (5 traits) of 37 categories of cheese; (2) to compare 3 instruments [2 benchtop, working in reflectance (R) and transmittance (T) mode (NIRS-R and NIRS-T, respectively) and 1 portable device (VisNIRS-R)], using their entire spectral ranges (1100-2498, 850-1048, and 350-1830 nm, respectively, for NIRS-R, NIRS-T and VisNIRS-R); (3) to examine different wavelength intervals of the spectrum within instrument, comparing also the common intervals among the 3 instruments; and (4) to determine the presence of bias in predicted traits for specific cheese categories. A Bayesian approach was used to develop 8 calibration models for each of 13 traits. This study confirmed that NIR spectroscopy can be used to predict the chemical composition of a large number of different cheeses, whereas pH and texture traits were poorly predicted. Color showed variable predictability, according to the trait considered, the instrument used, and, within instrument, according to the wavelength intervals. The predictive performance of the VisNIRS-R portable device was generally better than the 2 laboratory NIRS instruments, whether with the entire spectrum or selected intervals. The VisNIRS-R was found suitable for analyzing chemical composition in real time, without the need for sample uptake and processing. Our results also indicated that instrument technology is much more important than the NIR spectral range for accurate prediction equations, but the visible range is useful when predicting color traits, other than lightness. Specifically for certain categories (i.e., caprine, moldy, and fresh cheeses), dedicated calibrations seem to be needed to obtain unbiased and more accurate results. Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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