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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Research@WURarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Research@WUR
Article . 2016
Data sources: Research@WUR
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Animal Production Science
Article . 2016 . Peer-reviewed
Data sources: Crossref
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Quantifying effects of grassland management on enteric methane emission

Authors: Bannink, A.; Warner, D.; Chuko, B.H.; St-Pierre, J.L.; Dijkstra, J.;

Quantifying effects of grassland management on enteric methane emission

Abstract

Data on the effect of grassland management on the nutritional characteristics of fresh and conserved grass, and on enteric methane (CH4) emission in dairy cattle, are sparse. In the present study, an extant mechanistic model of enteric fermentation was evaluated against observations on the effect of grassland management on CH4 emission in three trials conducted in climate-controlled respiration chambers. Treatments were nitrogen fertilisation rate, stage of maturity of grass and level of feed intake, and mean data of a total of 18 treatments were used (4 grass herbage treatments and 14 grass silage treatments). There was a wide range of observed organic matter (OM) digestibility (from 68% to 84%) and CH4 emission intensity (from 5.6% to 7.3% of gross energy intake; from 27.4 to 36.9 g CH4/kg digested OM; from 19.7 to 24.6 g CH4/kg dry matter) among treatment means. The model predicted crude protein, fibre and OM digestibility with reasonable accuracy (root of mean square prediction errors as % of observed mean, RMSPE, 6.8%, 7.5% and 3.9%, respectively). For grass silages only, the model-predicted CH4 correlated well (Pearson correlation coefficient 0.73) with the observed CH4 (which varied from 5.7% to 7.2% of gross energy intake), after predicted CH4 was corrected for nitrate consumed with grass silage, acting as hydrogen sink in the rumen. After nitrate correction, there was a systematic under-prediction of 18%, which reduced to 9% when correcting the erroneously predicted rumen volatile fatty acid (VFA) profile (RMSPE 15%). Although a small over-prediction of 3% was obtained for the grass herbages, this increased to 14% when correcting VFA profile. The model predictions showed a systematic difference in CH4 emission from grass herbages and grass silages, which was not supported by the observed data. This is possibly related to the very high content of soluble carbohydrates in grass herbage (an extra 170 g/kg dry matter compared with grass silages) and an erroneous prediction of its fate and contribution to CH4 in the rumen. Erroneous prediction of the VFA profile is likely to be due to different types of diets included in the empirical database used to parameterise VFA yield in the model from those evaluated here. Model representations of feed digestion and VFA profile are key elements to predict enteric CH4 accurately, and with further evaluations, the latter aspect should be emphasised in particular.

Country
Netherlands
Keywords

modelling, grass roughage, dairy cow, rumen fermentation.

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Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Average
Top 10%
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