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Prediction of methane emission from beef cattle using data measured in indirect open-circuit respiration calorimeters

Published online by Cambridge University Press:  01 October 2009

T. Yan ,
M. G. Porter  and
C. S. Mayne
T. Yan*
Affiliation:
Agri-Food and Biosciences Institute, Hillsborough, Co Down BT26 6DR, UK
M. G. Porter
Affiliation:
Agri-Food and Biosciences Institute, Hillsborough, Co Down BT26 6DR, UK
C. S. Mayne
Affiliation:
Agri-Food and Biosciences Institute, Hillsborough, Co Down BT26 6DR, UK
*
†E-mail: tianhai.yan@afbini.gov.uk
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Abstract

The objectives of the present study were to examine relationships between methane (CH4) output and animal and dietary factors, and to use these relationships to develop prediction equations for CH4 emission from beef cattle. The dataset was obtained from 108 growing-to-finishing beef steers in five studies and CH4 production and energy metabolism data were measured in indirect respiration calorimeter chambers. Dietary forage proportion ranged from 29.5% to 100% (dry matter (DM) basis) and forages included grass silage, fresh grass, dried grass and fodder beet. Linear and multiple regression techniques were used to examine relationships between CH4 emission and animal and dietary variables, with the effects of experiment or forage type removed. Total CH4 emission was positively related to live weight (LW), feeding level and intake of feed (DM and organic matter) and energy (gross energy (GE), digestible energy (DE) and metabolisable energy (ME)) (P < 0.001), while CH4/DM intake (DMI) was negatively related to energy digestibility and ME/GE (P < 0.05 or less). Using LW alone to predict CH4 emission produced a poor relationship when compared to DMI and GE intake (GEI) (R2 = 0.26 v. 0.68 and 0.70 respectively). Adding feeding level, dietary NDF concentration and CP/ME or feeding level, energy digestibility and ME/GE to support LW resulted in a R2 of 0.66 or 0.84. The high R2 (0.84) was similar to that obtained using DMI or GEI together with energy digestibility and ME/GE as predictors. Further inclusion of dietary forage proportion and ADF and NDF concentration to the multiple relationships using GEI as the primary predictor resulted in a R2 of 0.87. These equations were evaluated through internal validation, by developing a range of similar new equations from two-thirds of the present data and then validating these new equations with the remaining one-third of data. The validation indicated that addition of energy digestibility and ME/GE to support LW with feeding level, DMI and GEI considerably increased the prediction accuracy. It is concluded that CH4 emission of beef steers can be accurately predicted from LW plus feeding level, DMI or GEI together with energy digestibility and ME/GE. The dataset was also used to validate a range of prediction equations for CH4 production of cattle published elsewhere.

Keywords

beef cattlecalorimetermethaneprediction equation
Type
Full Paper
Information
animal , Volume 3 , Issue 10 , October 2009 , pp. 1455 - 1462
Copyright
Copyright © The Animal Consortium 2009

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References

Agricultural and Food Research Council (AFRC) 1993. Energy and protein requirements of ruminants. CAB International, Wallingford, Oxon, UK.Google Scholar
Axelsson, J 1949. The amount of produced methane energy in the European metabolic experiments with adult cattle. Annals of the Royal Agricultural College of Sweden 16, 404–419.Google Scholar
Blaxter, KL, Clapperton, JL 1965. Prediction of the amount of methane produced by ruminants. British Journal of Nutrition 19, 511–522.CrossRefGoogle ScholarPubMed
Ellis, JL, Kebreab, E, Odongo, NE, McBride, BW, Okine, EK, France, J 2007. Prediction of methane production from dairy and beef cattle. Journal of Dairy Science 90, 3456–3467.CrossRefGoogle ScholarPubMed
Gordon, FJ, Dawson, LER, Ferris, CP, Steen, RWJ, Kilpatrick, DJ 1999. The influence of wilting and forage additive type on the energy utilisation of grass silage by growing cattle. Animal Feed Science and Technology 79, 15–27.CrossRefGoogle Scholar
Gordon, FJ, Porter, MG, Mayne, CS, Unsworth, EF, Kilpatrick, DJ 1995. The effect of forage digestibility and type of concentrate on nutrient utilisation for lactating dairy cattle. Journal of Dairy Research 62, 15–27.CrossRefGoogle ScholarPubMed
Holter, JB, Young, AJ 1992. Methane production in dry and lactating Holstein cows. Journal of Dairy Science 75, 2165–2175.CrossRefGoogle ScholarPubMed
Houghton, JT, Meira Filho, LG, Callendar, BA, Harris, N, Kattenbureg, A, Maskell, K ed. 1996. Climate Change 1995; the science of climate change. Contribution of Working Group 1 to the second assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK.Google Scholar
Kirkpatrick, DE 1995. The effects of diet on metabolisable energy utilisation and carcass composition in beef cattle and sheep. PhD thesis, The Queen’s University of Belfast, Belfast, UK.Google Scholar
Kirkpatrick, DE, Steen, RWJ, Unsworth, EF 1997. The effect of differing forage: concentrate ratio and restricting feed intake on the energy and nitrogen utilisation by beef cattle. Livestock Production Science 51, 151–164.CrossRefGoogle Scholar
Kriss, M 1930. Quantitative relations of the dry matter of the food consumed, the heat production, the gaseous outgo, and the insensible loss in body weight of cattle. Journal of Agricultural Research 40, 283–295.Google Scholar
Lavery, NP 1998. A comparison of grazed and conserved grass and concentrate diets in terms of the performance and carcass composition of beef cattle and lambs. PhD thesis, The Queen’s University of Belfast, Belfast, UK.CrossRefGoogle Scholar
Mc Court, A, Yan, T, Mayne, CS, Porter, MG 2005. Prediction of methane output for beef cattle from indirect respiration calorimetry data. In Proceedings of the 2nd Greenhouse Gases and Animal Agriculture Conference, 20–24 September 2005, Zurich, Switzerland, pp. 405–408.Google Scholar
McIlmoyle, DG, Patterson, DC, Kilpatrick, DJ 2000. The effect of fodder beet inclusion on nitrogen and energy utilisation of grass silage based diet by beef steers. In Proceedings of the British Society of Animal Science, March 2000, Scarborough, UK, p. 73.CrossRefGoogle Scholar
Mills, JAN, Kebreab, E, Yates, CW, Crompton, LA, Cammell, SB, Dhanoa, MS, Agnew, RE, France, J 2003. Alternative approaches to predicting methane emissions from dairy cows. Journal of Animal Science 81, 3143–3150.CrossRefGoogle ScholarPubMed
Moe, PW, Tyrrell, HF 1979. Methane production in dairy cows. Journal of Dairy Science 62, 1583–1586.CrossRefGoogle Scholar
Moss, AR, Jouany, JP, Newbold, J 2000. Methane production by ruminants: its contribution to global warming. Annales de Zootechnie 49, 231–253.CrossRefGoogle Scholar
Steinfeld, H, Gerber, P, Wassenaar, T, Castel, V, Rosales, M, de Haan, C 2006. Livestock’s long shadow – environmental issues and options. Food and Agriculture Organisation of the United Nations, Rome, Italy.Google Scholar
Yan, T, Agnew, RE, Gordon, FJ, Porter, MG 2000. Prediction of methane energy output in dairy and beef cattle offered grass silage-based diets. Livestock Production Science 64, 253–263.CrossRefGoogle Scholar
Yan, T, Mayne, CS 2007. Mitigation strategies to reduce methane emission from dairy cows. In Proceedings of the BGS/BES/BSAS Conference: High Value Grassland: Providing Biodiversity, a Clean Environment and Premium Products, 17–19 April 2007, University of Keele, Staffordshire, UK, pp. 345–348.Google Scholar
Yan, T, Mayne, CS, Porter, MG 2005. Effects of dietary and animal factors on methane production in dairy cows offered grass silage-based diets. In Proceedings of the 2nd Greenhouse Gases and Animal Agriculture Conference, 20–24 September 2005, Zurich, Switzerland, pp. 131–134.Google Scholar