Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-22T17:06:11.843Z Has data issue: false hasContentIssue false

Relationships between methane emission of Holstein Friesian dairy cows and fatty acids, volatile metabolites and non-volatile metabolites in milk

Published online by Cambridge University Press:  21 February 2017

S. van Gastelen*
Affiliation:
Top Institute Food and Nutrition, PO Box 557, 6700 AN Wageningen, The Netherlands Animal Nutrition Group, Wageningen University & Research, PO Box 338, 6700 AH Wageningen, The Netherlands
E. C. Antunes-Fernandes
Affiliation:
Top Institute Food and Nutrition, PO Box 557, 6700 AN Wageningen, The Netherlands Food Quality and Design Group, Wageningen University & Research, PO Box 17, 6700 AH Wageningen, The Netherlands
K. A. Hettinga
Affiliation:
Food Quality and Design Group, Wageningen University & Research, PO Box 17, 6700 AH Wageningen, The Netherlands
J. Dijkstra
Affiliation:
Animal Nutrition Group, Wageningen University & Research, PO Box 338, 6700 AH Wageningen, The Netherlands
*
Get access

Abstract

This study investigated the relationships between methane (CH4) emission and fatty acids, volatile metabolites (V) and non-volatile metabolites (NV) in milk of dairy cows. Data from an experiment with 32 multiparous dairy cows and four diets were used. All diets had a roughage : concentrate ratio of 80 : 20 based on dry matter (DM). Roughage consisted of either 1000 g/kg DM grass silage (GS), 1000 g/kg DM maize silage (MS), or a mixture of both silages (667 g/kg DM GS and 333 g/kg DM MS; 333 g/kg DM GS and 677 g/kg DM MS). Methane emission was measured in climate respiration chambers and expressed as production (g/day), yield (g/kg dry matter intake; DMI) and intensity (g/kg fat- and protein-corrected milk; FPCM). Milk was sampled during the same days and analysed for fatty acids by gas chromatography, for V by gas chromatography–mass spectrometry, and for NV by nuclear magnetic resonance. Several models were obtained using a stepwise selection of (1) milk fatty acids (MFA), V or NV alone, and (2) the combination of MFA, V and NV, based on the minimum Akaike’s information criterion statistic. Dry matter intake was 16.8±1.23 kg/day, FPCM yield was 25.0±3.14 kg/day, CH4 production was 406±37.0 g/day, CH4 yield was 24.1±1.87 g/kg DMI and CH4 intensity was 16.4±1.91 g/kg FPCM. The observed CH4 emissions were compared with the CH4 emissions predicted by the obtained models, based on concordance correlation coefficient (CCC) analysis. The best models with MFA alone predicted CH4 production, yield and intensity with a CCC of 0.80, 0.71 and 0.69, respectively. The best models combining the three types of metabolites included MFA and NV for CH4 production and CH4 yield, whereas for CH4 intensity MFA, NV and V were all included. These models predicted CH4 production, yield and intensity better with a higher CCC of 0.92, 0.78 and 0.93, respectively, and with increased accuracy (Cb) and precision (r). The results indicate that MFA alone have moderate to good potential to estimate CH4 emission, and furthermore that including V (CH4 intensity only) and NV increases the CH4 emission prediction potential. This holds particularly for the prediction model for CH4 intensity.

Type
Research Article
Copyright
© The Animal Consortium 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Antunes-Fernandes, EC, van Gastelen, S, Dijkstra, J, Hettinga, KA and Vervoort, J 2016. Milk metabolome relates enteric methane emission to milk synthesis and energy metabolism pathways. Journal of Dairy Science 99, 62516262.Google Scholar
Bauman, DE and Griinari, JM 2003. Nutritional regulation of milk fat synthesis. Annual Review of Nutrition 23, 203227.Google Scholar
Buchin, S, Martin, B, Dupont, D, Bornard, A and Achilleos, C 1999. Influence of the composition of Alpine highland pasture on the chemical, rheological and sensory properties of cheese. Journal of Dairy Research 66, 579588.Google Scholar
Castro-Montoya, J, Bhagwat, AM, Peiren, N, De Campeneere, S, De Baets, B and Fievez, V 2011. Relationships between odd- and branched-chain fatty acid profiles in milk and calculated enteric methane proportion for lactating dairy cattle. Animal Feed Science and Technology 166–167, 596602.Google Scholar
Centraal Veevoederbureau (CVB) 2012. Chemische samenstellingen en nutritionele waarden van voedermiddelen (in Dutch). CVB, The Hague, Netherlands.Google Scholar
Chilliard, Y, Martin, C, Roual, J and Doreau, M 2009. Milk fatty acids in dairy cows fed whole crude linseed, extruded linseed, or linseed oil, and their relationship with methane output. Journal of Dairy Science 92, 51995211.Google Scholar
Dijkstra, J, van Gastelen, S, Antunes-Fernandes, EC, Warner, D, Hatew, B, Klop, G, Podesta, SC, Van Lingen, HJ, Hettinga, KA and Bannink, A 2016. Relationships between milk fatty acid profiles and enteric methane production in dairy cattle fed grass- or grass silage-based diets. Animal Production Science 56, 541548.CrossRefGoogle Scholar
Dijkstra, J, van Zijderveld, SM, Apajalahti, JA, Bannink, A, Gerrits, WJJ, Newbold, JR, Perdok, HB and Berends, H. 2011. Relationships between methane production and milk fatty acid profiles in dairy cattle. Animal Feed Science and Technology 166–167, 590595.Google Scholar
Enjalbert, F, Nicot, MC, Bayourthe, C and Moncoulon, R 2001. Ketone bodies in milk and blood of dairy cows: relationship between concentrations and utilization for detection of subclinical ketosis. Journal of Dairy Science 84, 583589.Google Scholar
Fievez, V, Colman, E, Castro-Montoya, JM, Stefanov, I and Vlaeminck, B 2012. Milk odd- and branched-chain fatty acids as biomarkers of rumen function – an update. Animal Feed Science and Technology 172, 5165.Google Scholar
Hammond, KJ, Crompton, LA, Bannink, A, Dijkstra, J, Yáñez-Ruiz, DR, O’Kiely, P, Kebreab, E, Eugène, MA, Yu, Z, Shingfield, KJ, Schwarm, A, Hristov, AN and Reynolds, CK 2016. Review of current in vivo measurement techniques for quantifying enteric methane emission from ruminants. Animal Feed Science and Technology 219, 1330.Google Scholar
Kliem, KE, Morgan, R, Humphries, DJ, Shingfield, KJ and Givens, DI 2008. Effect of replacing grass silage with maize silage in the diet on bovine milk fatty acid composition. Animal 2, 18501858.CrossRefGoogle ScholarPubMed
Lin, LIK 1989. A concordance correlation coefficient to evaluate reproducibility. Biometrics 45, 255268.CrossRefGoogle ScholarPubMed
Mohammed, R, McGinn, SM and Beauchemin, KA 2011. Prediction of enteric methane output from milk fatty acid concentrations and rumen fermentation parameters in dairy cows fed sunflower, flax, or canola seeds. Journal of Dairy Science 94, 60576068.Google Scholar
Rico, DE, Chouinard, PY, Hassanat, F, Benchaar, C and Gervais, R 2016. Prediction of enteric methane emissions from Holstein dairy cows fed various forage sources. Animal 10, 203211.CrossRefGoogle ScholarPubMed
Sundekilde, UK, Poulsen, NA, Larsen, LB and Bertram, HC 2013. Nuclear magnetic resonance metabonomics reveals strong association between milk metabolites and somatic cell count in bovine milk. Journal of Dairy Science 96, 290299.Google Scholar
Urbach, G 1990. Effect of feed on flavor in dairy foods. Journal of Dairy Science 73, 36393650.Google Scholar
Van Gastelen, S, Antunes-Fernandes, EC, Hettinga, KA, Klop, G, Alferink, SJJ, Hendriks, WH and Dijkstra, J 2015. Enteric methane production, rumen volatile fatty acid concentrations, and milk fatty acid composition in lactating Holstein-Friesian cows fed grass silage- or corn silage-based diets. Journal of Dairy Science 98, 19151927.Google Scholar
Van Gastelen, S and Dijkstra, J 2016. Prediction of methane emission from lactating dairy cows using milk fatty acids and mid-infrared spectroscopy. Journal of the Science of Food and Agriculture 96, 39633968.CrossRefGoogle ScholarPubMed
Van Lingen, HJ, Crompton, LA, Hendriks, WH, Reynolds, CK and Dijkstra, J 2014. Meta-analysis of relationships between enteric methane yield and milk fatty acid profile in dairy cattle. Journal of Dairy Science 97, 71157132.Google Scholar
Villeneuve, MP, Lebeuf, Y, Gervais, R, Tremblay, GF, Vuillemard, JC, Fortin, J and Chouinard, PY 2013. Milk volatile organic compounds and fatty acid profile in cows fed timothy as hay, pasture, or silage. Journal of Dairy Science 96, 71817194.Google Scholar
Vlaeminck, B and Fievez, V 2005. Milk odd- and branched-chain fatty acids to predict ruminal methanogenesis in dairy cows. Communications in Agricultural and Applied Biological Sciences 70, 4347.Google Scholar
Vlaeminck, B, Fievez, V, Cabrita, ARJ, Fonseca, AJM and Dewhurst, RJ 2006. Factors affecting odd- and branched-chain fatty acids in milk: a review. Animal Feed Science and Technology 131, 389417.Google Scholar
Williams, SRO, Moate, PJ, Deighton, MH, Hannah, MC and Wales, WJ 2014. Methane emissions of dairy cows cannot be predicted by the concentrations of C8:0 and total C18 fatty acids in milk. Animal Production Science 54, 17571761.Google Scholar
Supplementary material: File

van Gastelen supplementary material

Tables S1-S3

Download van Gastelen supplementary material(File)
File 36.9 KB