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RESEARCH ARTICLE

Predicting metabolisable energy intake by free-ranging cattle using multiple short-term breath samples and applied to a pasture case-study

R. M. Herd https://orcid.org/0000-0003-4689-5519 A B F , P. F. Arthur C , R. S. Hegarty B , T. Bird-Gardiner D , K. A. Donoghue D and J. I. Velazco E
+ Author Affiliations
- Author Affiliations

A NSW Department of Primary Industries, Livestock Industry Centre, Armidale, NSW 2351, Australia.

B Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia.

C NSW Department of Primary Industries, Elizabeth Macarthur Agricultural Institute, Menangle, NSW 2568, Australia.

D NSW Department of Primary Industries, Agricultural Research Centre, Trangie, NSW 2823, Australia.

E National Institute of Agricultural Research, Treinta y Tres 33000, Uruguay.

F Corresponding author. Email: robert.herd@dpi.nsw.gov.au

Animal Production Science - https://doi.org/10.1071/AN20162
Submitted: 3 April 2020  Accepted: 11 October 2020   Published online: 4 November 2020

Abstract

Context: Research into improving feed efficiency by ruminant animals grazing pastures has historically been restrained by an inability to measure feed intake by large numbers of individual animals. Recent advances in portable breath measurement technology could be useful for this purpose but methodologies need to be developed.

Aims: To evaluate predictive models for metabolisable energy intake (MEI) by free-ranging cattle using multiple short-term breath samples and then apply these to predict MEI by free-ranging cattle in a historic grazing experiment with cattle genetically divergent for residual feed intake (feed efficiency).

Methods: Predictive models for MEI were developed using bodyweight (BW) data, and carbon dioxide production rate (CPR) and methane production rate (MPR) from multiple short-term breath measurements, from an experiment with long-fed Angus steers on a grain-based diet, and an experiment with short-fed Angus heifers on a roughage diet. Heat production was calculated using CPR and MPR. Energy retained (ER) in body tissue gain by steers was calculated from BW, ADG, initial and final subcutaneous fat depths, and for both groups using feeding-standards equations.

Key results: Metabolic mid-test BW (MBW) explained 49 and 47% of the variation in MEI in the steer and heifer experiment, respectively, and for the steers adding ADG and then subcutaneous fat gain resulted in the models accounting for 60 and then 65% of the variation in MEI. In the steer experiment, MBW with CPR explained 57% of the variation in MEI, and including MPR did not account for any additional variation. In the heifer experiment, MBW with CPR explained 50%, and with MPR accounted for 52% of the variation in MEI. Heat production plus ER explained 60, 35 and 85% of the variation in MEI in the steer and the heifer experiments, and in the pooled data from both experiments, respectively.

Conclusions: Multiple short-term breath measurements, together simple BW data, can be used to predict MEI by free-ranging cattle in studies in which animals do not have feed-intake or ADG recorded.

Implications: This methodology can be used for research into improving feed efficiency by farm animals grazing pastures.

Keywords: average daily gain, carbon dioxide, feed efficiency, feed intake, grazing, metabolisable energy intake, methane, methane production rate, oxygen, pasture.


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