Daily methane emissions and emission intensity of grazing beef cattle genetically divergent for residual feed intakeJ. I. Velazco A B , R. M. Herd C , D. J. Cottle A and R. S. Hegarty A D
A University of New England, Armidale, NSW 2351, Australia.
B National Institute of Agricultural Research, Treinta y Tres 33000, Uruguay.
C Department of Primary Industries, Armidale, NSW 2351, Australia.
D Corresponding author. Email: email@example.com
Animal Production Science 57(4) 627-635 https://doi.org/10.1071/AN15111
Submitted: 27 February 2015 Accepted: 15 January 2016 Published: 27 May 2016
As daily methane production (DMP; g CH4/day) is strongly correlated with dry matter intake (DMI), the breeding of cattle that require less feed to achieve a desired rate of average daily gain (ADG) by selection for a low residual feed intake (RFI) can be expected to reduce DMP and also emission intensity (EI; g CH4/kg ADG). An experiment was conducted to compare DMP and EI of Angus cattle genetically divergent for RFI and 400-day weight (400dWT). In a 6-week grazing study, 64 yearling-age cattle (30 steers, 34 heifers) were grazed on temperate pastures, with heifers and steers grazing separate paddocks. Liveweight (LW) was monitored weekly and DMP of individual cattle was measured by a GreenFeed emission monitoring unit in each paddock. Thirty-nine of the possible 64 animals had emission data recorded for 15 or more days, and only data for these animals were analysed. For these cattle, regression against their mid-parent estimated breeding value (EBV) for post-weaning RFI (RFI-EBV) showed that a lower RFI-EBV was associated with higher LW at the start of experiment. Predicted dry matter intake (pDMI), predicted DMP (pDMP) and measured DMP (mDMP) were all negatively correlated with RFI-EBV (P < 0.05), whereas ADG, EI, predicted CH4 yield (pMY; g CH4/kg DMI) were not correlated with RFI-EBV (P > 0.1). Daily CH4 production was positively correlated with animal LW and ADG (P < 0.05). The associations between ADG and its dependent traits EI and pMY and predicted feed conversion ratio (kg pDMI/kg ADG) were strongly negative (r = –0.82, –0.57 and –0.85, P < 0.001) implying that faster daily growth by cattle was accompanied by lower EI, MY and feed conversion ratio. These results show that cattle genetically divergent for RFI do not necessarily differ in ADG, EI or pMY on pasture and that, if heavier, cattle with lower RFI-EBV can actually have higher DMP while grazing moderate quality pastures.
Additional keywords: CH4, feed conversion efficiency, grazing cattle, greenhouse gases, measurement, RFI.
ReferencesAFIA (2014) AFIA – Laboratory Methods Manual: a reference manual of standard methods for the analysis of fodder, version 8 [Online]. Australian Fodder Industry Association Publication No. 03/00. Available at http://www.afia.org.au/files/AFIALabManua_v8_rm.pdf [Verified 29 August 2015]
Alford AR, Hegarty RS, Parnell PF, Cacho OJ, Herd RM, Griffith GR (2006) The impact of breeding to reduce residual feed intake on enteric methane emissions from the Australian beef industry. Australian Journal of Experimental Agriculture 46, 813–820.
| The impact of breeding to reduce residual feed intake on enteric methane emissions from the Australian beef industry.CrossRef |
Allison CD (1985) Factors affecting forage intake by range ruminants: a review. Journal of Range Management 38, 305–311.
| Factors affecting forage intake by range ruminants: a review.CrossRef |
Arthur PF, Archer JA, Herd RM, Melville GJ (2001) Response to selection for net feed intake in beef cattle. Proceedings of the Association for the Advancement of Animal Breeding and Genetics 14, 135–138.
Arthur PF, Pryce JE, Herd RM (2014) Lessons learnt from 25 years of feed efficiency research in Australia. In ‘Proceedings of the 10th world congress of genetics applied to livestock production’. 18–22 August 2014, Vancouver, Canada. Available at https://asas.org/docs/default-source/wcgalp-proceedings-oral/110_paper_10178_manuscript_1215_0.pdf?sfvrsn=2 [Verified 13 May 2016]
Association of Official Analytical Chemists (1990) ‘Official methods of analysis.’ 15th edn. (Ed. K Helrich) Method 990.03. Association of Official Analytical Chemists, Arlington, VA, USA.
Barnett MC, Forster NA, Ray GA, Li L, Guppy CN, Hegarty RS (2016) Using portable X-ray fluorescence (pXRF) to determine fecal concentrations of non-absorbable digesta kinetic and digestibility markers in sheep and cattle. Animal Feed Science and Technology 212, 35–41.
| Using portable X-ray fluorescence (pXRF) to determine fecal concentrations of non-absorbable digesta kinetic and digestibility markers in sheep and cattle.CrossRef | 1:CAS:528:DC%2BC2MXitFSntLnF&md5=ae3dd0703797b9fef4794ee3e7cc5831CAS |
Basarab JA, Beauchemin KA, Baron VS, Ominiski KH, Guan LL, Miller SP, Crowley JJ (2013) Reducing GHG emissions through genetic improvement for feed efficiency: effects on economically important traits and enteric methane production. Animal 7, 303–315.
| Reducing GHG emissions through genetic improvement for feed efficiency: effects on economically important traits and enteric methane production.CrossRef | 23739472PubMed |
Benchaar C, Rivest J, Pomar C, Chiquette J (1998) Prediction of methane production from dairy cows using existing mechanistic models and regression equations. Journal of Animal Science 76, 617–627.
Blaxter KL, Clapperton JL (1965) Prediction of the amount of methane produced by ruminants. British Journal of Nutrition 19, 511–522.
| Prediction of the amount of methane produced by ruminants.CrossRef | 1:CAS:528:DyaF28XitFKktg%3D%3D&md5=6cde6902b771bbb1af70db2dca0760aaCAS | 5852118PubMed |
Charmley E, Williams SRO, Moate PJ, Hegarty RS, Herd RM, Oddy VH, Reyenga P, Staunton KM, Anderson A, Hannah MC (2016) A universal equation to predict methane production of forage-fed cattle in Australia. Animal Production Science 56, 169–180.
| A universal equation to predict methane production of forage-fed cattle in Australia.CrossRef | 1:CAS:528:DC%2BC28Xis1amu70%3D&md5=d1eb2b764dd6396af5b37141ae7a2b3dCAS |
Cottle DJ (2013) The trials and tribulations of estimating the pasture intake of grazing animals. Animal Production Science 53, 1209–1220.
| The trials and tribulations of estimating the pasture intake of grazing animals.CrossRef |
Cottle DJ, Nolan JV, Wiedemann SG (2011) Ruminant enteric methane mitigation: a review. Animal Production Science 51, 491–514.
| Ruminant enteric methane mitigation: a review.CrossRef | 1:CAS:528:DC%2BC3MXntVGisLY%3D&md5=ca8409519db155f19af58311f9f4e1d4CAS |
DoE (2013) ‘Australian national greenhouse accounts. Quarterly update of Australia’s national greenhouse gas inventory. June Quarter 2013.’ (Department of the Environment: Canberra) Available at http://www.environment.gov.au [Verified 22 January 2015]
Dong H, Mangino J, McAllister TA, Hatfield JL, Johnson DE, Lassey KR, de Lima MA, Romanovskaya A (2006) IPCC guidelines for national greenhouse gas inventories, vol. 4: agriculture, forestry, and other land use, chapter 10: emissions from livestock and manure management. pp. 10.1–10.87. (IPCC: Paris, France) Available at http://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/4_Volume4/V4_10_Ch10_Livestock. pdf [Verified 13 May 2016]
Grainger C, Clarke T, McGinn SM, Auldist MJ, Beauchemin KA, Hannah MC, Waghorn GC, Clark H, Eckard RJ (2007) Methane emissions from dairy cows measured using the sulfur hexafluoride (SF6) tracer and chamber techniques. Journal of Dairy Science 90, 2755–2766.
| Methane emissions from dairy cows measured using the sulfur hexafluoride (SF6) tracer and chamber techniques.CrossRef | 1:CAS:528:DC%2BD2sXlvFOitr0%3D&md5=9edcc5a363c2eba212f8765f0901b599CAS | 17517715PubMed |
Hegarty RS, Goopy JP, Herd RM, McCorkell B (2007) Cattle selected for lower residual feed intake have reduced daily methane production. Journal of Animal Science 85, 1479–1486.
| Cattle selected for lower residual feed intake have reduced daily methane production.CrossRef | 1:CAS:528:DC%2BD2sXls1ant7c%3D&md5=8004943b5c2eb95bd7a3c31248e24898CAS | 17296777PubMed |
Hegarty RS, Alcock D, Robinson DL, Goopy JP, Vercoe PE (2010) Nutritional and flock management options to reduce methane output and methane per unit product from sheep enterprises. Animal Production Science 50, 1026–1033.
| Nutritional and flock management options to reduce methane output and methane per unit product from sheep enterprises.CrossRef | 1:CAS:528:DC%2BC3cXhsVGrt7fJ&md5=6e2f7ec34211f3b03bfcda3aa3e1061fCAS |
Herd RM, Arthur PF (2009) Physiological basis for residual feed intake. Journal of Animal Science 87, E64–E71.
| Physiological basis for residual feed intake.CrossRef | 1:STN:280:DC%2BD1M3mtVWksA%3D%3D&md5=dbc3e7f231e26b74ef480ad84dbebce5CAS | 19028857PubMed |
Herd RM, Pitchford WS (2011) Residual feed intake selection makes cattle leaner and more efficient. In ‘Recent advances in animal nutrition – Australia. Vol. 18’. (Ed. P Cronje) pp. 45–58. (Department of Animal Science, University of New England: Armidale, NSW)
Herd RM, Hegarty RS, Dicker RW, Archer JA, Arthur PF (2002) Selection for residual feed intake improves feed conversion in steers on pasture. Animal Production in Australia 24, 85–88.
Herd RM, Archer JA, Arthur PF (2003) Reducing the cost of beef production through genetic improvement in residual feed intake: opportunity and challenges to application. Journal of Animal Science 81, E9–E17.
Herd RM, Oddy VH, Richardson EC (2004a) Biological basis for variation in residual feed intake in beef cattle. 1. Review of potential mechanisms. Australian Journal of Experimental Agriculture 44, 423–430.
| Biological basis for variation in residual feed intake in beef cattle. 1. Review of potential mechanisms.CrossRef |
Herd RM, Dicker RW, Lee GJ, Johnston DJ, Hammond AJ, Oddy VH (2004b) Steer growth and feed efficiency on pasture are favourable associated with genetic variation in sire net feed intake. Animal Production in Australia 25, 93–96.
Herd RM, Piper S, Thompson JM, Arthur PF, McCorkell B, Dibley KCP (2009) Benefits of genetic superiority in residual feed intake in a large feedlot. Proceedings of the Association for Advancement of Animal Breeding and Genetics 18, 476–479.
Herd RM, Arthur PF, Archer JA (2011) Associations between residual feed intake on ad-libitum, pasture and restricted feeding in Angus cows. Proceedings of the Association for Advancement of Animal Breeding and Genetics 19, 47–50.
Herd RM, Arthur PF, Donoghue KA, Bird SH, Bird-Gardiner T, Hegarty RS (2014) Measures of methane production and their phenotypic relationships with dry matter intake, growth, and body composition traits in beef cattle. Journal of Animal Science 92, 5267–5274.
| Measures of methane production and their phenotypic relationships with dry matter intake, growth, and body composition traits in beef cattle.CrossRef | 1:CAS:528:DC%2BC2MXitlartw%3D%3D&md5=c17a1cb11bffd89430e7403c5b06ec85CAS | 25349368PubMed |
Hristov AN, Oh J, Lee C, Meinen R, Montes F, Ott T, Firkins J, Rotz A, Dell C, Adesogan A, Yang W, Tricarico J, Kebreab E, Waghorn G, Dijkstra J, Oosting S (2013) ‘Mitigation of greenhouse gas emissions in livestock production – A review of technical options for non-CO2 emissions.’ FAO Animal Production and Health Paper No. 177. (Eds PJ Gerber, B Henderson, HPS Makkar) (FAO: Rome, Italy)
IPCC (2013) Intergovernmental Panel on Climate Change, Summary for Policymakers. In ‘Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change’. (Eds TF Stocker, D Qin, G.-K Plattner, M Tignor, SK Allen, J Boschung, A Nauels, Y Xia, V Bex, PM Midgley) (Cambridge University Press: Cambridge, UK and New York, NY)
Johnson K, Johnson DE (1995) Methane emissions from cattle. Journal of Animal Science 73, 2483–2492.
Jones RJ, Ludlow MM, Throughton JH, Blunt CG (1981) Changes in the natural carbon isotope ratios from steers fed diets of C3 and C4 species in sequence. Search 12, 85–87.
Jones FM, Phillips FA, Naylor T, Mercer NB (2011) Methane emissions from grazing Angus beef cows selected for divergent residual feed intake. Animal Feed Science and Technology 166–167, 302–307.
| Methane emissions from grazing Angus beef cows selected for divergent residual feed intake.CrossRef |
Kennedy PM, Charmley E (2012) Methane yields from Brahman cattle fed tropical grasses and legumes. Animal Production Science 52, 225–239.
| Methane yields from Brahman cattle fed tropical grasses and legumes.CrossRef | 1:CAS:528:DC%2BC38XktFWgsL0%3D&md5=0e18aa7dabcd5946d7575591a16a9980CAS |
Koch RM, Swiger L, Chambers D, Gregory KE (1963) Efficiency of feed use in beef cattle. Journal of Animal Science 22, 486–494.
Lana RP, Russell JB, Van Amburgh ME (1998) The role of pH in regulating ruminal methane and ammonia production. Journal of Animal Science 76, 2190–2196.
McLaren TI, Guppy CN, Tighe MK, Forster NA, Grave P, Lisle LM, Bennett JW (2012) Rapid, nondestructive total elemental analysis of Vertisol soils using portable X-ray fluorescence. Soil Science Society of America Journal 76, 1436–1445.
| Rapid, nondestructive total elemental analysis of Vertisol soils using portable X-ray fluorescence.CrossRef | 1:CAS:528:DC%2BC38XhtFarsbjJ&md5=766679401ff36d20675b4818b65e3fcbCAS |
Minson DJ, McDonald CK (1987) Estimating forage intake from the growth of beef cattle. Tropical Grasslands 21, 116–122.
Nkrumah JD, Okine EK, Mathison GW, Schmid K, Li C, Basarab JA, Moore SS (2006) Relationships of feedlot feed efficiency, performance, and feeding behavior with metabolic rate, methane production, and energy partitioning in beef cattle. Journal of Animal Science 84, 145–153.
Nolan JV, Hegarty RS, Hegarty J, Godwin IR, Woodgate R (2010) Effects of dietary nitrate on fermentation, methane production and digesta kinetics in sheep. Animal Production Science 50, 801–806.
| Effects of dietary nitrate on fermentation, methane production and digesta kinetics in sheep.CrossRef | 1:CAS:528:DC%2BC3cXhtVyrtbzP&md5=c4b3aedbbbfca9ab9c48f4b4570cd5d9CAS |
Pereira AB, Brito AF, Zimmerman S, Antaya N (2013) Evaluating carbon fluxes variability in late lactation organic Jersey cows using a portable automated gas quantification system during the grazing season. Journal of Dairy Science 96, 600
Phillipson J (1964) A miniature bomb calorimeter for small biological samples. Oikos 15, 130–139.
| A miniature bomb calorimeter for small biological samples.CrossRef |
Pickering NK, Oddy VH, Basarab J, Cammack K, Hayes B, Hegarty RS, Lassen J, McEwan JC, Miller S, Pinares-Patiño CS, de Haas Y (2015) Genetic possibilities to reduce greenhouse gas emissions in ruminants. Animal 9, 1431–1440.
| Genetic possibilities to reduce greenhouse gas emissions in ruminants.CrossRef | 1:CAS:528:DC%2BC2MXhtlOnurnN&md5=e528453b2c769598a2e2d1ca33f314efCAS | 26055577PubMed |
Pinares-Patiño CS, Ulyatt MJ, Holmes CW, Barry TN, Lassey KR (2003) Persistence of the between-sheep variation in methane emissions. The Journal of Agricultural Science 140, 227–233.
| Persistence of the between-sheep variation in methane emissions.CrossRef |
Pitchford WS, Accioly JA, Banks RG, Barnes LA, Barwick SA, Copping KJ, Deland MPB, Donoghue KA, Edwards N, Hebart ML, Herd RM, Jones FM, Lawrence M, Lee SJ, McKiernan WA, Parnell PF, Speijers J, Tudor GD, Graham JF (2014) Simultaneous genetic improvement of maternal productivity, feed efficiency and end-product traits in variable environments. Final Report for Project B.SBP.0050. Meat & Livestock Australia Limited, North Sydney, 56 pp.
Ramin M, Huhtanen P (2013) Development of equations for predicting methane emissions from ruminants. Journal of Dairy Science 96, 2476–2493.
| Development of equations for predicting methane emissions from ruminants.CrossRef | 1:CAS:528:DC%2BC3sXitlemt7s%3D&md5=80e2f676e1278d10e26ca08df4003d02CAS | 23403199PubMed |
Richardson EC, Herd RM (2004) Biological basis for variation in residual feed intake in beef cattle. 2. Synthesis of results following divergent selection. Australian Journal of Experimental Agriculture 44, 431–440.
| Biological basis for variation in residual feed intake in beef cattle. 2. Synthesis of results following divergent selection.CrossRef |
Rymer C (2000) Digestibility in vivo. Forage Evaluation in Ruminant Nutrition 113–134.
| Digestibility in vivo.CrossRef | 1:CAS:528:DC%2BD3MXitlKnsbg%3D&md5=7c09e38e74e9bd3d91423ec892417f10CAS |
SAS (1989) ‘SAS/STAT users guide. Version 6.’ 4th edn. (SAS Institute Inc.: Cary, NC)
Tighe MK, Forster NA (2014) Rapid, nondestructive elemental analysis of tree and shrub litter. Communications in Soil Science and Plant Analysis 45, 53–60.
| Rapid, nondestructive elemental analysis of tree and shrub litter.CrossRef | 1:CAS:528:DC%2BC3sXhsF2ks7jL&md5=0cdd5d24310b936f341374072701c3deCAS |
Tothill JC, Hargreaves JNG, Jones RM (1978) ‘Botanal – a comprehensive sampling and computing procedure for estimating pasture yield and composition. I Field sampling.’ CSIRO Australian Division of Tropical Crops and Pastures, Tropical Agronomy, St Lucia, Queensland, Australia. Memorandum No. 8.
Velazco JI, Mayer DG, Zimmerman S, Hegarty RS (2015) Use of short-term breath measures to estimate daily methane production by cattle. Animal
| Use of short-term breath measures to estimate daily methane production by cattle.CrossRef | 26303821PubMed |
Waghorn GC, Hegarty RS (2011) Lowering ruminant methane emissions through improved feed conversion efficiency. Animal Feed Science and Technology 166–167, 291–301.
| Lowering ruminant methane emissions through improved feed conversion efficiency.CrossRef |
Weston RH (1996) Some aspects of constraint to forage consumption by ruminants. Australian Journal of Agricultural Research 47, 175–197.
| Some aspects of constraint to forage consumption by ruminants.CrossRef |