Prediction of enteric methane production, yield and intensity of beef cattle using an intercontinental database

Autor: Nico Peiren, Mark McGee, Zhongtang Yu, Sang Suk Lee, Sebastião de Campos Valadares Filho, Ali R. Bayat, Alexandre Berndt, Telma Teresinha Berchielli, Kristin E Hales, Angela Schwarm, André Bannink, E. Charmley, N. Andy Cole, Jan Dijkstra, Maguy Eugène, Cécile Martin, Ermias Kebreab, Carol Anne Duthie, David R. Yáñez-Ruiz, M. Niu, Michael Kreuzer, John Rooke, Les A. Crompton, David P. Casper, Christopher K. Reynolds, Juliana Duarte Messana, Padraig O'Kiely, Martin Hünerberg, Tim A. McAllister, Henk J. van Lingen, Alexander N. Hristov, Mariana Caetano, P. I. Hynd, Alex V. Chaves
Přispěvatelé: Federal Office for Agriculture (Switzerland), European Commission, National Institute of Food and Agriculture (US), Department of Agriculture, Food and Marine (Ireland), Department of Animal science, University of California [Davis] (UC Davis), University of California-University of California, Farmer’s Business Network, Animal Science Department, University of Tabriz [Tabriz], Scotland's Rural College (SRUC), Institute of Agricultural Sciences, Ecole Polytechnique Fédérale de Zurich, University of Adelaide, Department of Animal and Veterinary Bioscience, Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de la Recherche Agronomique (INRA)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Teagasc Agriculture and Food Development Authority (Teagasc), Department of Agricultural, Food and Nutritional Science, University of Alberta, Lethbridge Research and Development Centre, Agriculture and Agri-Food [Ottawa] (AAFC), Research Institute for Agricultural, Fisheries and Food (ILVO), Faculty of Science, School of Life and Environmental Sciences, University of Sydney, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), USDA-ARS : Agricultural Research Service, Department of Animal Science and Technology, Suncheon National University, Research and Development, EMBRAPA Southeast Livestock, School of Agriculture, Policy and Development, University of Reading (UOR), Milk Production, Production Systems, Natural resources institute Finland, Estacion Experimental del Zaidin-CSIC, Department of Animal Sciences, University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, Wageningen Livestock Research, Wageningen / Aeres University of Applied Sciences, Animal Nutrition Group, Wageningen University and Research [Wageningen] (WUR), Furst McNess Company, FACCE-JPI program Global Network (ANR-13-JFAC-0003-01), Scotland's Rural College (SCUR), Unité Mixte de Recherches sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de la Recherche Agronomique (INRA), Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), United States Department of Agriculture - Agricultural Research Service, Natural Resources Institute Finland, Wageningen University and Research Centre [Wageningen] (WUR), University of California, Farmer's Business Network Inc., Universidade Federal de Viçosa (UFV), SRUC, The University of Adelaide, Université Clermont Auvergne, Dunsany, Agriculture and Agri-Food Canada, Universidade Estadual Paulista (Unesp), Animal Sciences Unit, School of Life and Environmental Sciences, CSIRO Agriculture and Food, USDA-ARS, Sunchon National University, Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), University of Reading, Natural Resources Institute Finland (Luke), Estación Experimental del Zaidin (CSIC), The Ohio State University, Wageningen University & Research, The Pennsylvania State University, Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Rok vydání: 2018
Předmět:
Zdroj: Agriculture, Ecosystems and Environment
Agriculture, Ecosystems and Environment, Elsevier Masson, 2019, 283, pp.106575. ⟨10.1016/j.agee.2019.106575⟩
Agriculture, Ecosystems and Environment 283 (2019)
Agriculture, Ecosystems and Environment, 283
Digital.CSIC. Repositorio Institucional del CSIC
instname
Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
ISSN: 0167-8809
Popis: Enteric methane (CH) production attributable to beef cattle contributes to global greenhouse gas emissions. Reliably estimating this contribution requires extensive CH emission data from beef cattle under different management conditions worldwide. The objectives were to: 1) predict CH production (g d animal), yield [g (kg dry matter intake; DMI)] and intensity [g (kg average daily gain)] using an intercontinental database (data from Europe, North America, Brazil, Australia and South Korea); 2) assess the impact of geographic region, and of higher- and lower-forage diets. Linear models were developed by incrementally adding covariates. A K-fold cross-validation indicated that a CH production equation using only DMI that was fitted to all available data had a root mean square prediction error (RMSPE; % of observed mean) of 31.2%. Subsets containing data with ≥25% and ≤18% dietary forage contents had an RMSPE of 30.8 and 34.2%, with the all-data CH production equation, whereas these errors decreased to 29.3 and 28.4%, respectively, when using CH prediction equations fitted to these subsets. The RMSPE of the ≥25% forage subset further decreased to 24.7% when using multiple regression. Europe- and North America-specific subsets predicted by the best performing ≥25% forage multiple regression equation had RMSPE of 24.5 and 20.4%, whereas these errors were 24.5 and 20.0% with region-specific equations, respectively. The developed equations had less RMSPE than extant equations evaluated for all data (22.5 vs. 23.2%), for higher-forage (21.2 vs. 23.1%), but not for the lower-forage subsets (28.4 vs. 27.9%). Splitting the dataset by forage content did not improve CH yield or intensity predictions. Predicting beef cattle CH production using energy conversion factors, as applied by the Intergovernmental Panel on Climate Change, indicated that adequate forage content-based and region-specific energy conversion factors improve prediction accuracy and are preferred in national or global inventories.
Authors gratefully acknowledge project funding from the USDA National Institute of Food and Agriculture Federal Appropriations under Project PEN 04539 and Accession number 1000803; the Joint Programming Initiative on Agriculture, Food Security and Climate Change (FACCE-JPI)’s ‘GLOBAL NETWORK’ project and the ‘Feeding and Nutrition Network’ (http://animalscience.psu.edu/fnn) of the Livestock Research Group within the Global Research Alliance for Agricultural Greenhouse Gases (www.globalresearchalliance.org); the Sesnon Endowed Chair program (UC Davis); the Swiss Federal Office of Agriculture, Berne, Switzerland; AHDB Beef and Lamb, the Scottish Government, Defra and the devolved administrations through the UK Agricultural Greenhouse Gas Inventory Research Platform; French National Research Agency through the FACCE-JPI program (ANR-13-JFAC-0003-01); the Cooperative Research Program for Agriculture Science, (Project No. PJ013448012018), RDA, Republic of Korea; the Australian Government Department of Agriculture, Fisheries and Forestry (Carbon Farming Futures Action on the Ground program; AOTGR2-0400); the financial support of the Reducing Emissions from Livestock Research Program, the National Livestock Methane Program, Meat and Livestock Australia, CSIRO and Ridley AgriProducts Pty, Ltd; the Institute of Science and Technology in Animal Science (INCTCA 465377/2014-9), the Department of Agriculture, Food and the Marine (DAFM), Ireland (AGRI-I project); European Commission through SMEthane (FP7‐SME‐262,270); Beef Cattle Research Council of the Canadian Cattlemen’s Association; the Cofund for Monitoring & Mitigation of Greenhouse Gases from Agri- and Silvi-culture (FACCE ERA-GAS)’s project Capturing Effects of Diet on Emissions from Ruminant Systems and the Dutch Ministry of Agriculture, Nature and Food Quality (AF-EU-18010 & BO-4400159-01).
Databáze: OpenAIRE
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