The use of milk Fourier transform mid-infrared spectra and milk yield to estimate heat production as a measure of efficiency of dairy cows.

Dairy cattle Heat production Milk spectra Partial least square regression Respiration chamber

Journal

Journal of animal science and biotechnology
ISSN: 1674-9782
Titre abrégé: J Anim Sci Biotechnol
Pays: England
ID NLM: 101581293

Informations de publication

Date de publication:
2020
Historique:
received: 03 12 2019
accepted: 01 04 2020
entrez: 14 5 2020
pubmed: 14 5 2020
medline: 14 5 2020
Statut: epublish

Résumé

Transformation of feed energy ingested by ruminants into milk is accompanied by energy losses via fecal and urine excretions, fermentation gases and heat. Heat production may differ among dairy cows despite comparable milk yield and body weight. Therefore, heat production can be considered an indicator of metabolic efficiency and directly measured in respiration chambers. The latter is an accurate but time-consuming technique. In contrast, milk Fourier transform mid-infrared (FTIR) spectroscopy is an inexpensive high-throughput method and used to estimate different physiological traits in cows. Thus, this study aimed to develop a heat production prediction model using heat production measurements in respiration chambers, milk FTIR spectra and milk yield measurements from dairy cows. Heat production was computed based on the animal's consumed oxygen, and produced carbon dioxide and methane in respiration chambers. Heat production data included 168 24-h-observations from 64 German Holstein and 20 dual-purpose Simmental cows. Animals were milked twice daily at 07:00 and 16:30 h in the respiration chambers. Milk yield was determined to predict heat production using a linear regression. Milk samples were collected from each milking and FTIR spectra were obtained with MilkoScan FT 6000. The average or milk yield-weighted average of the absorption spectra from the morning and afternoon milking were calculated to obtain a computed spectrum. A total of 288 wavenumbers per spectrum and the corresponding milk yield were used to develop the heat production model using partial least squares (PLS) regression. Measured heat production of studied animals ranged between 712 and 1470 kJ/kg BW The PLS model using weighted average FTIR spectra and milk yield has higher potential to predict heat production of dairy cows than models applying FTIR spectra or milk yield only.

Sections du résumé

BACKGROUND BACKGROUND
Transformation of feed energy ingested by ruminants into milk is accompanied by energy losses via fecal and urine excretions, fermentation gases and heat. Heat production may differ among dairy cows despite comparable milk yield and body weight. Therefore, heat production can be considered an indicator of metabolic efficiency and directly measured in respiration chambers. The latter is an accurate but time-consuming technique. In contrast, milk Fourier transform mid-infrared (FTIR) spectroscopy is an inexpensive high-throughput method and used to estimate different physiological traits in cows. Thus, this study aimed to develop a heat production prediction model using heat production measurements in respiration chambers, milk FTIR spectra and milk yield measurements from dairy cows.
METHODS METHODS
Heat production was computed based on the animal's consumed oxygen, and produced carbon dioxide and methane in respiration chambers. Heat production data included 168 24-h-observations from 64 German Holstein and 20 dual-purpose Simmental cows. Animals were milked twice daily at 07:00 and 16:30 h in the respiration chambers. Milk yield was determined to predict heat production using a linear regression. Milk samples were collected from each milking and FTIR spectra were obtained with MilkoScan FT 6000. The average or milk yield-weighted average of the absorption spectra from the morning and afternoon milking were calculated to obtain a computed spectrum. A total of 288 wavenumbers per spectrum and the corresponding milk yield were used to develop the heat production model using partial least squares (PLS) regression.
RESULTS RESULTS
Measured heat production of studied animals ranged between 712 and 1470 kJ/kg BW
CONCLUSION CONCLUSIONS
The PLS model using weighted average FTIR spectra and milk yield has higher potential to predict heat production of dairy cows than models applying FTIR spectra or milk yield only.

Identifiants

pubmed: 32399210
doi: 10.1186/s40104-020-00455-0
pii: 455
pmc: PMC7204237
doi:

Types de publication

Journal Article

Langues

eng

Pagination

43

Informations de copyright

© The Author(s) 2020.

Déclaration de conflit d'intérêts

Competing interestsThe authors declare that they have no competing interests.

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Auteurs

Sadjad Danesh Mesgaran (SD)

1Institute of Nutritional Physiology "Oskar Kellner," Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany.

Anja Eggert (A)

2Institute of Genetics and Biometry, Leibniz Institute for Farm Anih8mal Biology (FBN), Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany.

Peter Höckels (P)

IfM GmbH & Co. KG - Institut für Milchuntersuchung (Milk Testing Services North Rhine-Westphalia), Bischofstraße 85, 47809 Krefeld, Germany.

Michael Derno (M)

1Institute of Nutritional Physiology "Oskar Kellner," Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany.

Björn Kuhla (B)

1Institute of Nutritional Physiology "Oskar Kellner," Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany.

Classifications MeSH