Invited review: Determination of large-scale individual dry matter intake phenotypes in dairy cattle

Seymour, D.J.; Cánovas, A.; Baes, C. F.; Chud, T.C.S.; Osborne, V.R.; Cant, J.P.; Brito, L.F.; Gredler-Grandl, B.; Finocchiaro, R.; Veerkamp, R.F.; de Haas, Y.; Miglior, F. (2019). Invited review: Determination of large-scale individual dry matter intake phenotypes in dairy cattle. Journal of dairy science, 102(9), pp. 7655-7663. Elsevier 10.3168/jds.2019-16454

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Feed efficiency has been widely studied in many areas of dairy science and is currently seeing renewed interest in the field of breeding and genetics. A critical part of determining how efficiently an animal utilizes feed is accurately measuring individual dry matter (DM) intake. Currently, multiple methods are used to measure feed intake or determine the DM content of that feed, resulting in different levels of accuracy of measurement. Furthermore, the scale at which data need to be collected for use in genetic analyses makes some methodologies impractical. This systematic review aims to provide an overview of the current methodologies used to measure both feed intake in ruminants and DM content of feedstuffs, current methods to predict individual DM intake, and applications of large-scale intake measurements. Overall, advances in milk spectral data analysis present a promising method of estimating individual DM intake on a herd scale with further validation of prediction models. Although measurements of individual feed intake rely on the same underlying principle, the methods selected are largely dictated by the costs of capital, labor, and necessary analyses. Finally, DM methodologies were synthesized into a comprehensive protocol for use in a variety of feedstuffs.

Item Type:

Journal Article (Review Article)

Division/Institute:

05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH) > Institute of Genetics
05 Veterinary Medicine > Department of Clinical Research and Veterinary Public Health (DCR-VPH)

UniBE Contributor:

Baes, Christine Francoise

Subjects:

500 Science > 590 Animals (Zoology)
600 Technology > 630 Agriculture
500 Science > 570 Life sciences; biology

ISSN:

0022-0302

Publisher:

Elsevier

Language:

English

Submitter:

Christine Francoise Baes

Date Deposited:

23 Oct 2019 09:21

Last Modified:

23 Oct 2019 09:21

Publisher DOI:

10.3168/jds.2019-16454

PubMed ID:

31255263

BORIS DOI:

10.7892/boris.131750

URI:

https://boris.unibe.ch/id/eprint/131750

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