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An evaluation of the accuracy and precision of methane prediction equations for beef cattle fed high-forage and high-grain diets

Published online by Cambridge University Press:  01 July 2016

P. Escobar-Bahamondes ,
M. Oba  and
K. A. Beauchemin
P. Escobar-Bahamondes
Affiliation:
Agriculture and Agri-Food Canada (AAFC), 5403 1st Avenue S, PO Box 3000, Lethbridge, Canada, AB T1J 4B1 Department of Agricultural, Food & Nutritional Science, 4-10J Agriculture/Forestry Centre, University of Alberta, Edmonton, Canada, AB T6G 2P5 Instituto de Investigaciones Agropecuarias (INIA) Remehue, Osorno, Región de Los Lagos 5290000, Chile
M. Oba
Affiliation:
Department of Agricultural, Food & Nutritional Science, 4-10J Agriculture/Forestry Centre, University of Alberta, Edmonton, Canada, AB T6G 2P5
K. A. Beauchemin*
Affiliation:
Agriculture and Agri-Food Canada (AAFC), 5403 1st Avenue S, PO Box 3000, Lethbridge, Canada, AB T1J 4B1
*
†E-mail: karen.beauchemin@agr.gc.ca
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Abstract

The study determined the performance of equations to predict enteric methane (CH4) from beef cattle fed forage- and grain-based diets. Many equations are available to predict CH4 from beef cattle and the predictions vary substantially among equations. The aims were to (1) construct a database of CH4 emissions for beef cattle from published literature, and (2) identify the most precise and accurate extant CH4 prediction models for beef cattle fed diets varying in forage content. The database was comprised of treatment means of CH4 production from in vivo beef studies published from 2000 to 2015. Criteria to include data in the database were as follows: animal description, intakes, diet composition and CH4 production. In all, 54 published equations that predict CH4 production from diet composition were evaluated. Precision and accuracy of the equations were evaluated using the concordance correlation coefficient (rc), root mean square prediction error (RMSPE), model efficiency and analysis of errors. Equations were ranked using a combined index of the various statistical assessments based on principal component analysis. The final database contained 53 studies and 207 treatment means that were divided into two data sets: diets containing ⩾400 g/kg dry matter (DM) forage (n=116) and diets containing ⩽200 g/kg DM forage (n=42). Diets containing between ⩽400 and ⩾200 g/kg DM forage were not included in the analysis because of their limited numbers (n=6). Outliers, treatment means where feed was fed restrictively and diets with CH4 mitigation additives were omitted (n=43). Using the high-forage dataset the best-fit equations were the International Panel on Climate Change Tier 2 method, 3 equations for steers that considered gross energy intake (GEI) and body weight and an equation that considered dry matter intake and starch:neutral detergent fiber with rc ranging from 0.60 to 0.73 and RMSPE from 35.6 to 45.9 g/day. For the high-grain diets, the 5 best-fit equations considered intakes of metabolisable energy, cellulose, hemicellulose and fat, or for steers GEI and body weight, with rc ranging from 0.35 to 0.52 and RMSPE from 47.4 to 62.9 g/day. Ranking of extant CH4 prediction equations for their accuracy and precision differed with forage content of the diet. When used for cattle fed high-grain diets, extant CH4 prediction models were generally imprecise and lacked accuracy.

Keywords

beef cattlegreenhouse gasmethanemodeling
Type
Research Article
Information
animal , Volume 11 , Issue 1 , January 2017 , pp. 68 - 77
Copyright
© The Animal Consortium and Her Majesty the Queen in Right of Canada, as represented by the Minister of Agriculture and Agri-Food Canada 2016 

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