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Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

A meta-analysis comparing four measurement methods to determine the relationship between methane emissions and dry-matter intake in New Zealand dairy cattle

Arjan Jonker https://orcid.org/0000-0002-6756-8616 A D , Peter Green A , Garry Waghorn B , Tony van der Weerden C , David Pacheco A and Cecile de Klein C
+ Author Affiliations
- Author Affiliations

A Grasslands Research Centre, AgResearch Ltd, Tennent Drive, Private Bag 11008, Palmerston North 4442, New Zealand.

B Independent Scientist, 6 Berkeley Avenue, Hamilton 3216, New Zealand.

C Invermay Agricultural Research Centre, AgResearch Ltd, Private Bag 50034, Mosgiel 9092, New Zealand.

D Corresponding author. Email: arjan.jonker@agresearch.co.nz

Animal Production Science 60(1) 96-101 https://doi.org/10.1071/AN18573
Submitted: 7 September 2018  Accepted: 7 November 2018   Published: 6 December 2018

Abstract

Enteric methane (CH4) emissions and dry-matter intake (DMI) can be accurately and precisely measured in respiration chambers (RC), whereas automated head chambers (GreenFeed; GF) and the SF6 tracer method can provide estimates of CH4 emissions from grazing cattle. In New Zealand, most dairy cattle graze pasture and, under these conditions, DMI also has to be estimated. The objective of the current study was to compare the relationship between CH4 production and DMI of New Zealand dairy cattle fed forages using the following four measurement methods: RC with measured DMI (RC); sulfur hexafluoride (SF6) with measured DMI (SF6-DMI); SF6 with DMI estimated from prediction equations or indigestible markers (SF6); GF with measured or estimated DMI (GF). Data were collected from published literature from New Zealand trials with growing and lactating dairy cattle fed forage-based diets and data were analysed using a mixed-effect model. The intercept of the linear regression between CH4 production and DMI was not significantly different from zero and was omitted from the model. However, residual variance (observed–predicted values) increased with an increasing DMI, which was addressed by log-transforming CH4 per unit of DMI and this model was used for final data analysis. The accuracy of the four methods for predicting log CH4 per unit of DMI was similar (P = 0.55), but the precision (indicated by residuals) differed (P < 0.001) among methods. The residual standard deviations for SF6, GF and SF6-DMI were 4.6, 3.4 and 2.1 times greater than the residuals for RC. Hence, all methods enabled accurate prediction of CH4 per unit of DMI, but methodology for determining both CH4 and DMI affected their precision (residuals).

Additional keywords: C-Lock GreenFeed, greenhouse gas, growing, lactating, non-lactating, respiration chamber, SF6 tracer technique.


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