Short communication: Selecting the most informative mid-infrared spectra wavenumbers to improve the accuracy of prediction models for detailed milk protein content

Journal of Dairy Science
G NieroMassimo De Marchi

Abstract

The objective of this study was to investigate the ability of mid-infrared spectroscopy (MIRS) to predict protein fraction contents of bovine milk samples by applying uninformative variable elimination (UVE) procedure to select the most informative wavenumber variables before partial least squares (PLS) analysis. Reference values (n=114) of protein fractions were measured using reversed-phase HPLC and spectra were acquired through MilkoScan FT6000 (Foss Electric A/S, Hillerød, Denmark). Prediction models were built using the full data set and tested with a leave-one-out cross-validation. Compared with MIRS models developed using standard PLS, the UVE procedure reduced the number of wavenumber variables to be analyzed through PLS regression and improved the accuracy of prediction by 6.0 to 66.7%. Good predictions were obtained for total protein, total casein (CN), and α-CN, which included αS1- and αS2-CN; moderately accurate predictions were observed for κ-CN and total whey protein; and unsatisfactory results were obtained for β-CN, α-lactalbumin, and β-lactoglobulin. Results indicated that UVE combined with PLS is a valid approach to enhance the accuracy of MIRS prediction models for milk protein fractions.

References

Oct 29, 1997·Journal of Chromatography. B, Biomedical Sciences and Applications·I RecioR López-Fandiño
Nov 1, 1996·Analytical Chemistry·V CentnerC Sterna
Oct 29, 2011·Journal of Dairy Science·A CaroliD Cocchi
Oct 29, 2011·Journal of Dairy Science·M J M RuttenJ A M van Arendonk
Sep 25, 2012·The Journal of Dairy Research·Denis PrettoMartino Cassandro
Jan 21, 2014·Journal of Dairy Science·M De MarchiM Penasa
May 8, 2014·Nutrition·Paula C Pereira
Jul 21, 2015·Journal of Dairy Science·G NieroM Cassandro

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Citations

Oct 23, 2019·Sensors·Abraham Gastélum-BarriosDaniel Jauregui-Vazquez
Apr 21, 2019·Animals : an Open Access Journal From MDPI·Marco FranzoiMassimo De Marchi
Dec 17, 2020·Animals : an Open Access Journal From MDPI·Giovanni NieroMauro Penasa

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