Mid-infrared spectroscopic analysis of raw milk to predict the blood nonesterified fatty acid concentrations in dairy cows.


Journal

Journal of dairy science
ISSN: 1525-3198
Titre abrégé: J Dairy Sci
Pays: United States
ID NLM: 2985126R

Informations de publication

Date de publication:
Jul 2020
Historique:
received: 23 11 2019
accepted: 29 02 2020
pubmed: 12 5 2020
medline: 31 10 2020
entrez: 12 5 2020
Statut: ppublish

Résumé

In high-yielding dairy cattle, severe postpartum negative energy balance is often associated with metabolic and infectious disorders that negatively affect production, fertility, and welfare. Mobilization of adipose tissue associated with negative energy balance is reflected through an increased level of nonesterified fatty acids (NEFA) in the blood plasma. Earlier, identification of negative energy balance through detection of increased blood plasma NEFA concentration required laborious and stressful blood sampling. More recently, attempts have been made to predict blood NEFA concentration from milk samples. In this study, we aimed to develop and validate a model to predict blood plasma NEFA concentration using the milk mid-infrared (MIR) spectra that are routinely measured in the context of milk recording. To this end, blood plasma and milk samples were collected in wk 2, 3, and 20 postpartum for 192 lactations in 3 herds. The blood plasma samples were taken in the morning, and representative milk samples were collected during the morning and evening milk sessions on the same day. To predict plasma NEFA concentration from the milk MIR spectra, partial least squares regression models were trained on part of the observations from the first herd. The models were then thoroughly validated on all other observations of the first herd and on the observations of the 2 independent herds to explore their robustness and wide applicability. The final model could accurately predict blood plasma NEFA concentrations <0.6 mmol/L with a root mean square error of prediction of <0.143 mmol/L. However, for blood plasma with >1.2 mmol/L NEFA, the model clearly underestimated the true level. Additionally, we found that morning blood plasma NEFA levels were predicted with significantly higher accuracy using MIR spectra of evening milk samples compared with MIR spectra of morning samples, with root mean square error of prediction values of, respectively, 0.182 and 0.197 mmol/L, and R

Identifiants

pubmed: 32389474
pii: S0022-0302(20)30351-9
doi: 10.3168/jds.2019-17952
pii:
doi:

Substances chimiques

Fatty Acids, Nonesterified 0
3-Hydroxybutyric Acid TZP1275679

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

6422-6438

Informations de copyright

Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Auteurs

Ben Aernouts (B)

KU Leuven, Department of Biosystems, Biosystems Technology Cluster, Campus Geel, Kleinhoefstraat 4, 2440 Geel, Belgium; KU Leuven, Department of Biosystems, Mechatronics, Biostatistics and Sensors Division, Kasteelpark Arenberg 30, 3001 Leuven, Belgium; Natural Resources Institute of Finland (Luke), Maarintie 6, 02150 Espoo, Finland. Electronic address: ben.aernouts@kuleuven.be.

Ines Adriaens (I)

KU Leuven, Department of Biosystems, Biosystems Technology Cluster, Campus Geel, Kleinhoefstraat 4, 2440 Geel, Belgium; KU Leuven, Department of Biosystems, Mechatronics, Biostatistics and Sensors Division, Kasteelpark Arenberg 30, 3001 Leuven, Belgium.

José Diaz-Olivares (J)

KU Leuven, Department of Biosystems, Biosystems Technology Cluster, Campus Geel, Kleinhoefstraat 4, 2440 Geel, Belgium; KU Leuven, Department of Biosystems, Mechatronics, Biostatistics and Sensors Division, Kasteelpark Arenberg 30, 3001 Leuven, Belgium.

Wouter Saeys (W)

KU Leuven, Department of Biosystems, Mechatronics, Biostatistics and Sensors Division, Kasteelpark Arenberg 30, 3001 Leuven, Belgium.

Päivi Mäntysaari (P)

Natural Resources Institute of Finland (Luke), Tietotie 4, 31600 Jokioinen, Finland.

Tuomo Kokkonen (T)

University of Helsinki, Department of Agricultural Sciences, Koetilantie 5, 00014 Helsinki, Finland.

Terhi Mehtiö (T)

Natural Resources Institute of Finland (Luke), Tietotie 4, 31600 Jokioinen, Finland.

Sari Kajava (S)

Natural Resources Institute of Finland (Luke), Halolantie 31 A, 71750 Maaninka, Finland.

Paula Lidauer (P)

Natural Resources Institute of Finland (Luke), Tietotie 4, 31600 Jokioinen, Finland.

Martin H Lidauer (MH)

Natural Resources Institute of Finland (Luke), Tietotie 4, 31600 Jokioinen, Finland.

Matti Pastell (M)

Natural Resources Institute of Finland (Luke), Maarintie 6, 02150 Espoo, Finland.

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Classifications MeSH