Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle

In response to the increased concern over agriculture’s contribution to greenhouse gas (GHG) emissions, more detailed assessments of current methane emissions and their variation, within and across individual dairy farms and cattle, are of interest for research and policy development. This assessmen...

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Main Authors: X. Zhang, P.R. Amer, K. Stachowicz, C. Quinton, J. Crowley
Format: Article
Language:English
Published: Elsevier 2021-09-01
Series:Animal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1751731121001683
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spelling doaj-326e6a0061634e7dbb56a8a99b0cc28b2021-08-08T04:17:41ZengElsevierAnimal1751-73112021-09-01159100325Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattleX. Zhang0P.R. Amer1K. Stachowicz2C. Quinton3J. Crowley4AbacusBio Limited, PO Box 5585, Dunedin 9058, New ZealandCorresponding author.; AbacusBio Limited, PO Box 5585, Dunedin 9058, New ZealandAbacusBio Limited, PO Box 5585, Dunedin 9058, New ZealandAbacusBio Limited, PO Box 5585, Dunedin 9058, New ZealandAbacusBio Limited, PO Box 5585, Dunedin 9058, New ZealandIn response to the increased concern over agriculture’s contribution to greenhouse gas (GHG) emissions, more detailed assessments of current methane emissions and their variation, within and across individual dairy farms and cattle, are of interest for research and policy development. This assessment will provide insights into possible changes needed to reduce GHG emissions, the nature and direction of these changes, ways to influence farmer behavior and areas to maximize the adoption of emerging mitigation technologies. The objectives of this study were to (1) quantify the variation in enteric fermentation methane emissions within and among seasonal calving dairy farms with the majority of nutritional requirements met through grazed pasture; (2) use this variation to assess the potential of new individual animal emission monitoring technologies and their impact on mitigation policy. We used a large database of cow performance records for milk production and survival from 2 398 herds in New Zealand, and simulation to account for unobserved variation in feed efficiency and methane emissions per unit of feed. Results showed an average of 120 ± 31.4 kg predicted methane (CH4) per cow per year after accounting for replacement costs, ranging 8.9–323 kg CH4/cow per year. Whereas milk production, survival and predicted live weight were reasonably effective at predicting both individual and herd average levels of per cow feed intake, substantial within animal variation in emissions per unit of feed reduced the ability of these variables to predict variation in per animal methane output. Animal-level measurement technologies predicting only feed intake but not emissions per unit of feed are unlikely to be effective for advancing national policy goals of reducing dairy farming enteric methane output. This is because farmers seek to profitably utilize all farm feed resources available, so improvements in feed efficiency will not result in the reduction in feed utilization required to reduce methane emissions. At a herd level, average per cow milk production and live weight could form the basis of assigning a farm-level point of obligation for methane emissions. In conclusion, a comprehensive national database infrastructure that was tightly linked to animal identification and movement systems, and captured live weight data from existing farm-level recording systems, would be required to make this effective. Additional policy and incentivization mechanisms would still be required to encourage farmer uptake of mitigation interventions, such as novel feed supplements or vaccines that reduce methane emissions per unit of feed.http://www.sciencedirect.com/science/article/pii/S1751731121001683EmissionEntericIncentivizeMonitorPasture
collection DOAJ
language English
format Article
sources DOAJ
author X. Zhang
P.R. Amer
K. Stachowicz
C. Quinton
J. Crowley
spellingShingle X. Zhang
P.R. Amer
K. Stachowicz
C. Quinton
J. Crowley
Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle
Animal
Emission
Enteric
Incentivize
Monitor
Pasture
author_facet X. Zhang
P.R. Amer
K. Stachowicz
C. Quinton
J. Crowley
author_sort X. Zhang
title Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle
title_short Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle
title_full Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle
title_fullStr Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle
title_full_unstemmed Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle
title_sort herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle
publisher Elsevier
series Animal
issn 1751-7311
publishDate 2021-09-01
description In response to the increased concern over agriculture’s contribution to greenhouse gas (GHG) emissions, more detailed assessments of current methane emissions and their variation, within and across individual dairy farms and cattle, are of interest for research and policy development. This assessment will provide insights into possible changes needed to reduce GHG emissions, the nature and direction of these changes, ways to influence farmer behavior and areas to maximize the adoption of emerging mitigation technologies. The objectives of this study were to (1) quantify the variation in enteric fermentation methane emissions within and among seasonal calving dairy farms with the majority of nutritional requirements met through grazed pasture; (2) use this variation to assess the potential of new individual animal emission monitoring technologies and their impact on mitigation policy. We used a large database of cow performance records for milk production and survival from 2 398 herds in New Zealand, and simulation to account for unobserved variation in feed efficiency and methane emissions per unit of feed. Results showed an average of 120 ± 31.4 kg predicted methane (CH4) per cow per year after accounting for replacement costs, ranging 8.9–323 kg CH4/cow per year. Whereas milk production, survival and predicted live weight were reasonably effective at predicting both individual and herd average levels of per cow feed intake, substantial within animal variation in emissions per unit of feed reduced the ability of these variables to predict variation in per animal methane output. Animal-level measurement technologies predicting only feed intake but not emissions per unit of feed are unlikely to be effective for advancing national policy goals of reducing dairy farming enteric methane output. This is because farmers seek to profitably utilize all farm feed resources available, so improvements in feed efficiency will not result in the reduction in feed utilization required to reduce methane emissions. At a herd level, average per cow milk production and live weight could form the basis of assigning a farm-level point of obligation for methane emissions. In conclusion, a comprehensive national database infrastructure that was tightly linked to animal identification and movement systems, and captured live weight data from existing farm-level recording systems, would be required to make this effective. Additional policy and incentivization mechanisms would still be required to encourage farmer uptake of mitigation interventions, such as novel feed supplements or vaccines that reduce methane emissions per unit of feed.
topic Emission
Enteric
Incentivize
Monitor
Pasture
url http://www.sciencedirect.com/science/article/pii/S1751731121001683
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