cam a22 4500 528792040 20200309064606.0 cr unu---uuuuu 180924e201807 xx s 000 0 eng 10.3929/ethz-b-000272817 doi 10.3168/jds.2017-13536 doi (ETHRESEARCH)oai:www.research-collection.ethz.ch:20.500.11850/272817 (ETHRESEARCH)oai:www.research-collection.ethz.ch:20.500.11850/275211 Symposium review: Uncertainties in enteric methane inventories, measurement techniques, and prediction models [Elektronische Daten] [Alexander N. Hristov, Ermias Kebreab, Mutian Niu, Joonpyo Oh, André Bannink, Ali R. Bayat, Tommy Boland, André F. Brito, David Casper, Les A. Crompton, Jan Dijkstra, Maguy A. Eugène, Philip C. Garnsworthy, Najmul Haque, Anne L.F. Hellwing, Pekka J. Huhtanen, Michael Kreuzer, Björn Kuhla, Peter Lund, Jørgen Madsen, Cécile Martin, Shelby C. McClelland, Peter J. Moate, Peter J. Moate, Stefan Muetzel, Camila Muñoz, Padraig O'Kiely, Nico Peiren, Christopher K. Reynolds, Angela; id_orcid 0000-0002-5750-2111 Schwarm, Kevin J. Shingfield, Tonje M. Storlien, Martin R. Weisbjerg, David R. Yáñez Ruiz, Zhongtang Yu] J. dairy sci. Savoy, IL Elsevier 2018 Open access ethresearch Ruminant production systems are important contributors to anthropogenic methane (CH4) emissions, but there are large uncertainties in national and global livestock CH4 inventories. Sources of uncertainty in enteric CH4 emissions include animal inventories, feed dry matter intake (DMI), ingredient and chemical composition of the diets, and CH4 emission factors. There is also significant uncertainty associated with enteric CH4 measurements. The most widely used techniques are respiration chambers, the sulfur hexafluoride (SF6) tracer technique, and the automated head-chamber system (GreenFeed; C-Lock Inc., Rapid City, SD). All 3 methods have been successfully used in a large number of experiments with dairy or beef cattle in various environmental conditions, although studies that compare techniques have reported inconsistent results. Although different types of models have been developed to predict enteric CH4 emissions, relatively simple empirical (statistical) models have been commonly used for inventory purposes because of their broad applicability and ease of use compared with more detailed empirical and process-based mechanistic models. However, extant empirical models used to predict enteric CH4 emissions suffer from narrow spatial focus, limited observations, and limitations of the statistical technique used. Therefore, prediction models must be developed from robust data sets that can only be generated through collaboration of scientists across the world. To achieve high prediction accuracy, these data sets should encompass a wide range of diets and production systems within regions and globally. Overall, enteric CH4 prediction models are based on various animal or feed characteristic inputs but are dominated by DMI in one form or another. As a result, accurate prediction of DMI is essential for accurate prediction of livestock CH4 emissions. Analysis of a large data set of individual dairy cattle data showed that simplified enteric CH4 prediction models based on DMI alone or DMI and limited feed- or animal-related inputs can predict average CH4 emission with a similar accuracy to more complex empirical models. These simplified models can be reliably used for emission inventory purposes. 2017 ADSA Annual Meeting in Pittsburgh, PA, USA (June 25-28, 2018) Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported http://creativecommons.org/licenses/by-nc-nd/3.0 ethresearch enteric methane ethresearch uncertainty ethresearch prediction model ethresearch livestock ethresearch Hristov Alexander N. joint author Kebreab Ermias joint author Niu Mutian joint author Oh Joonpyo joint author Bannink André joint author Bayat Ali R. joint author Boland Tommy joint author Brito André F. joint author Casper David joint author Crompton Les A. joint author Dijkstra Jan joint author Eugène Maguy A. joint author Garnsworthy Philip C. joint author Haque Najmul joint author Hellwing Anne L.F. joint author Huhtanen Pekka J. joint author Kreuzer Michael joint author Kuhla Björn joint author Lund Peter joint author Madsen Jørgen joint author Martin Cécile joint author McClelland Shelby C. joint author Moate Peter J. joint author Muetzel Stefan joint author Muñoz Camila joint author O'Kiely Padraig joint author Peiren Nico joint author Reynolds Christopher K. joint author Schwarm Angela; id_orcid 0000-0002-5750-2111 joint author Shingfield Kevin J. joint author Storlien Tonje M. joint author Weisbjerg Martin R. joint author Yáñez Ruiz David R. joint author Yu Zhongtang joint author Journal of Dairy Science, 101 (7) Savoy, IL : Elsevier pp. 6655-6674 0022-0302 http://hdl.handle.net/20.500.11850/272817 text/html WWW-Backlink auf das Repository (Open access) 1 Other Conference Item ethresearch ETHRESEARCH 856 40 http://hdl.handle.net/20.500.11850/272817 text/html WWW-Backlink auf das Repository (Open access) ETHRESEARCH 700 1- Hristov Alexander N. joint author ETHRESEARCH 700 1- Kebreab Ermias joint author ETHRESEARCH 700 1- Niu Mutian joint author ETHRESEARCH 700 1- Oh Joonpyo joint author ETHRESEARCH 700 1- Bannink André joint author ETHRESEARCH 700 1- Bayat Ali R. joint author ETHRESEARCH 700 1- Boland Tommy joint author ETHRESEARCH 700 1- Brito André F. joint author ETHRESEARCH 700 1- Casper David joint author ETHRESEARCH 700 1- Crompton Les A. joint author ETHRESEARCH 700 1- Dijkstra Jan joint author ETHRESEARCH 700 1- Eugène Maguy A. joint author ETHRESEARCH 700 1- Garnsworthy Philip C. joint author ETHRESEARCH 700 1- Haque Najmul joint author ETHRESEARCH 700 1- Hellwing Anne L.F. joint author ETHRESEARCH 700 1- Huhtanen Pekka J. joint author ETHRESEARCH 700 1- Kreuzer Michael joint author ETHRESEARCH 700 1- Kuhla Björn joint author ETHRESEARCH 700 1- Lund Peter joint author ETHRESEARCH 700 1- Madsen Jørgen joint author ETHRESEARCH 700 1- Martin Cécile joint author ETHRESEARCH 700 1- McClelland Shelby C. joint author ETHRESEARCH 700 1- Moate Peter J. joint author ETHRESEARCH 700 1- Muetzel Stefan joint author ETHRESEARCH 700 1- Muñoz Camila joint author ETHRESEARCH 700 1- O'Kiely Padraig joint author ETHRESEARCH 700 1- Peiren Nico joint author ETHRESEARCH 700 1- Reynolds Christopher K. joint author ETHRESEARCH 700 1- Schwarm Angela; id_orcid 0000-0002-5750-2111 joint author ETHRESEARCH 700 1- Shingfield Kevin J. joint author ETHRESEARCH 700 1- Storlien Tonje M. joint author ETHRESEARCH 700 1- Weisbjerg Martin R. joint author ETHRESEARCH 700 1- Yáñez Ruiz David R. joint author ETHRESEARCH 700 1- Yu Zhongtang joint author ETHRESEARCH 773 0- Journal of Dairy Science, 101 (7) Savoy, IL : Elsevier pp. 6655-6674 0022-0302 ETHRESEARCH 856 40 http://hdl.handle.net/20.500.11850/275211 text/html WWW-Backlink auf das Repository (Open access) CL050000 XL050000 XC000500 ETHRESEARCH ETHRESEARCH ETHRESEARCH Other Conference Item Open access ETHRESEARCH ETHRESEARCH ETHRESEARCH Other Conference Item Open access