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Prediction of enteric methane production in beef cattle Open Access

Descriptions

Other title
Subject/Keyword
Methane
Beef cattle
Equations
Modeling
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Escobar, Carlos Paul
Supervisor and department
Beauchemin, Karen (Agriculture & Agri-Food Canada - Department of Agricultural, Food and Nutritional Science [Adj.])
Oba, Masahito (Department of Agricultural, Food and Nutritional Science)
Examining committee member and department
Beauchemin, Karen (Agriculture & Agri-Food Canada - Department of Agricultural, Food and Nutritional Science [Adj.])
Oba, Masahito (Department of Agricultural, Food and Nutritional Science)
Tim McAllister (Agriculture & Agri-Food Canada - Department of Agricultural, Food and Nutritional Science [Adj.])
Carolyn Fitzsimmons (Department of Agricultural, Food and Nutritional Science)
Kroebel, Roland (Agriculture & Agri-Food Canada)
Cole, Andy (USDA-ARS)
Department
Department of Agricultural, Food, and Nutritional Science
Specialization
Animal Science
Date accepted
2016-09-29T09:17:20Z
Graduation date
2016-06:Fall 2016
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
Methane (CH4) is a greenhouse gas with an elevated global warming potential (GWP) equivalent to 28 times that of CO2. Also, production of enteric CH4 results in a 2 to 12% loss of the gross energy intake of cattle thus knowing the amount of CH4 released to the environment is important. The overall objective of this research was to evaluate the accuracy and precision of predicted values of enteric CH4 production from models compared with observed values. The first study used concordance correlation coefficient (rc), root mean square prediction error (RMSPE, g d-1), model efficiency, and analysis of errors to assess precision and accuracy of fifty-one published empirical models that predict CH4 production. An original database comprised of 221 treatment means of CH4 production from 53 in vivo beef studies divided into high- and low- forage datasets was used to evaluate the predictions. Using a combined index of statistics, the best-fit models for the high-forage dataset were ranked in decreasing order: Intergovernmental Panel on Climate Change (IPCC) Tier 2 method (IPCC 2006), 3 models from Moraes et al. (2014; steers animal level, simulated gross energy (GE) at the animal level, steers GE level), and equation N from Ellis et al. (2009). For the high-grain diets, the best-fit models were: equation I Ellis et al. (2009), equation GEI from Ricci et al. (2013), and equations for steers at the GE level, animal level and simulated GE level from Moraes et al. (2014). Two conclusions emerge from this study: 1) Ranking of models differs with forage content of the diet and, 2) Extant models are generally imprecise and lack accuracy, especially when used for low- forage diets. The second study was conducted to develop universally applicable empirical models that predict CH4 specifically for high- and low- forage diets using traditional and resampled databases to obtain new models. The best fit models for high- and low- forage diets were obtained from Monte Carlo datasets and included the following variables: body weight (kg) and intakes (kg d-1) of dry matter, fat, neutral detergent fiber (NDF), acid detergent fiber (ADF), crude protein:NDF and starch:NDF ratios. For high- and low forages, best-fit models had rc ≥ 0.70 and RMSPE ≤ 40 g CH4 d-1, rc ≥ 0.90 and RMSPE ≤ 15 g eCH4 d-1, respectively. In this study it was concluded that the uncertainty of estimating beef cattle enteric CH4 emission compared with the IPCC Tier 2 methodology is reduced when using models specific to dietary forage proportion. The third study was conducted to estimate the variability of CH4 emissions using sixteen different models including the newly developed models and monthly simulated diets for mature beef cows and growing beef cattle in Eastern and Western Canada. Predictions were compared to those using an IPCC (2006) Tier 2 approach. Results indicated that there was variability in predicted CH4 production and conversion factor (Ym, percentage of gross energy intake) among models. Models that use variables that indirectly contain other variables such as dry matter intake (DMI) or energy predict stable Ym values and generate results similar to those using IPCC (2006). However, these models are less sensitive to changes in diet composition. In contrast, variability in Ym predictions was greater for models that consider diet composition. Using high- and low-forage datasets that were globally represented, it was found that extant beef cattle enteric CH4 models lack accuracy. Due to the lack of accurate models, the 2nd study developed new models that improved the prediction of CH4 production from beef cattle. Using a simulated production system for mature beef cows and growing steers in Canada the final study revealed variability of CH4 predictions between IPCC 2006 Tier 2 and models that account for nutrient intakes of cattle consuming high- or low-forage diets. The results of this research enable beef farm advisers, researchers and government policy advisors to choose appropriate equations to estimate enteric CH4 emissions from beef cattle under various dietary conditions. Accurate prediction of enteric CH4 emission is critical for the beef industry to develop suitable policies and adopt feeding strategies to decrease the quantity of enteric CH4 released to the atmosphere.
Language
English
DOI
doi:10.7939/R3KS6J93F
Rights
This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for the purpose of private, scholarly or scientific research. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
Citation for previous publication
Escobar-Bahamondes, P., Oba, M. and Beauchemin, K. A. 2016. An evaluation of the accuracy and precision of methane prediction equations for beef cattle fed high forage and high-grain diets. Animal. First view. Online 01 July 2016.Escobar-Bahamondes, P., Oba, M. and Beauchemin, K. A. 2016. Universally applicable methane prediction equations for beef cattle fed high- or low forage diets. Canadian Journal of Animal Science (in press).

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