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Multiple Breeds and Countries’ Predictions of Mineral Contents in Milk from Milk Mid-Infrared Spectrometry

Measuring the mineral composition of milk is of major interest in the dairy sector. This study aims to develop and validate robust multi-breed and multi-country models predicting the major minerals through milk mid-infrared spectrometry using partial least square regressions. A total of 1281 samples...

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Autores principales: Christophe, Octave S., Grelet, Clément, Bertozzi, Carlo, Veselko, Didier, Lecomte, Christophe, Höeckels, Peter, Werner, Andreas, Auer, Franz-Josef, Gengler, Nicolas, Dehareng, Frédéric, Soyeurt, Hélène
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8470342/
https://www.ncbi.nlm.nih.gov/pubmed/34574345
http://dx.doi.org/10.3390/foods10092235
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author Christophe, Octave S.
Grelet, Clément
Bertozzi, Carlo
Veselko, Didier
Lecomte, Christophe
Höeckels, Peter
Werner, Andreas
Auer, Franz-Josef
Gengler, Nicolas
Dehareng, Frédéric
Soyeurt, Hélène
author_facet Christophe, Octave S.
Grelet, Clément
Bertozzi, Carlo
Veselko, Didier
Lecomte, Christophe
Höeckels, Peter
Werner, Andreas
Auer, Franz-Josef
Gengler, Nicolas
Dehareng, Frédéric
Soyeurt, Hélène
author_sort Christophe, Octave S.
collection PubMed
description Measuring the mineral composition of milk is of major interest in the dairy sector. This study aims to develop and validate robust multi-breed and multi-country models predicting the major minerals through milk mid-infrared spectrometry using partial least square regressions. A total of 1281 samples coming from five countries were analyzed to obtain spectra and in ICP-AES to measure the mineral reference contents. Models were built from records coming from four countries (n = 1181) and validated using records from the fifth country, Austria (n = 100). The importance of including local samples was tested by integrating 30 Austrian samples in the model while validating with the remaining 70 samples. The best performances were achieved using this second set of models, confirming the need to cover the spectral variability of a country before making a prediction. Validation root mean square errors were 54.56, 63.60, 7.30, 59.87, and 152.89 mg/kg for Na, Ca, Mg, P, and K, respectively. The built models were applied on the Walloon milk recording large-scale spectral database, including 3,510,077. The large-scale predictions on this dairy herd improvement database provide new insight regarding the minerals’ variability in the population, as well as the effect of parity, stage of lactation, breeds, and seasons.
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spelling pubmed-84703422021-09-27 Multiple Breeds and Countries’ Predictions of Mineral Contents in Milk from Milk Mid-Infrared Spectrometry Christophe, Octave S. Grelet, Clément Bertozzi, Carlo Veselko, Didier Lecomte, Christophe Höeckels, Peter Werner, Andreas Auer, Franz-Josef Gengler, Nicolas Dehareng, Frédéric Soyeurt, Hélène Foods Article Measuring the mineral composition of milk is of major interest in the dairy sector. This study aims to develop and validate robust multi-breed and multi-country models predicting the major minerals through milk mid-infrared spectrometry using partial least square regressions. A total of 1281 samples coming from five countries were analyzed to obtain spectra and in ICP-AES to measure the mineral reference contents. Models were built from records coming from four countries (n = 1181) and validated using records from the fifth country, Austria (n = 100). The importance of including local samples was tested by integrating 30 Austrian samples in the model while validating with the remaining 70 samples. The best performances were achieved using this second set of models, confirming the need to cover the spectral variability of a country before making a prediction. Validation root mean square errors were 54.56, 63.60, 7.30, 59.87, and 152.89 mg/kg for Na, Ca, Mg, P, and K, respectively. The built models were applied on the Walloon milk recording large-scale spectral database, including 3,510,077. The large-scale predictions on this dairy herd improvement database provide new insight regarding the minerals’ variability in the population, as well as the effect of parity, stage of lactation, breeds, and seasons. MDPI 2021-09-21 /pmc/articles/PMC8470342/ /pubmed/34574345 http://dx.doi.org/10.3390/foods10092235 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Christophe, Octave S.
Grelet, Clément
Bertozzi, Carlo
Veselko, Didier
Lecomte, Christophe
Höeckels, Peter
Werner, Andreas
Auer, Franz-Josef
Gengler, Nicolas
Dehareng, Frédéric
Soyeurt, Hélène
Multiple Breeds and Countries’ Predictions of Mineral Contents in Milk from Milk Mid-Infrared Spectrometry
title Multiple Breeds and Countries’ Predictions of Mineral Contents in Milk from Milk Mid-Infrared Spectrometry
title_full Multiple Breeds and Countries’ Predictions of Mineral Contents in Milk from Milk Mid-Infrared Spectrometry
title_fullStr Multiple Breeds and Countries’ Predictions of Mineral Contents in Milk from Milk Mid-Infrared Spectrometry
title_full_unstemmed Multiple Breeds and Countries’ Predictions of Mineral Contents in Milk from Milk Mid-Infrared Spectrometry
title_short Multiple Breeds and Countries’ Predictions of Mineral Contents in Milk from Milk Mid-Infrared Spectrometry
title_sort multiple breeds and countries’ predictions of mineral contents in milk from milk mid-infrared spectrometry
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8470342/
https://www.ncbi.nlm.nih.gov/pubmed/34574345
http://dx.doi.org/10.3390/foods10092235
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