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Non-invasive individual methane measurement in dairy cows

Published online by Cambridge University Press:  23 December 2016

E. Negussie*
Affiliation:
Biometrical Genetics, Natural Resources Institute (Luke), Myllytie 1, 31600 Jokioinen, Finland
J. Lehtinen
Affiliation:
GASERA Ltd, 20520 Turku, Finland
P. Mäntysaari
Affiliation:
Livestock Technology, Natural Resources Institute (Luke), Myllytie 1, 31600 Jokioinen, Finland
A. R. Bayat
Affiliation:
Livestock Technology, Natural Resources Institute (Luke), Myllytie 1, 31600 Jokioinen, Finland
A.-E. Liinamo
Affiliation:
Biometrical Genetics, Natural Resources Institute (Luke), Myllytie 1, 31600 Jokioinen, Finland
E. A. Mäntysaari
Affiliation:
Biometrical Genetics, Natural Resources Institute (Luke), Myllytie 1, 31600 Jokioinen, Finland
M. H. Lidauer
Affiliation:
Biometrical Genetics, Natural Resources Institute (Luke), Myllytie 1, 31600 Jokioinen, Finland
*
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Abstract

Attempts to lower the environmental footprint of milk production needs a sound understanding of the genetic and nutritional basis of methane (CH4) emissions from the dairy production systems. This in turn requires accurate and reliable techniques for the measurement of CH4 output from individual cows. Many of the available measurement techniques so far are either slow, expensive, labor intensive and are unsuitable for large-scale individual animal measurements. The main objectives of this study were to examine and validate a non-invasive individual cow CH4 measurement system that is based on photoacoustic IR spectroscopy (PAS) technique implemented in a portable gas analysis equipment (F10), referred to as PAS-F10 method and to estimate the magnitude of between-animal variations in CH4 output traits. Data were collected from 115 Nordic Red cows of the Minkiö experimental dairy farm, at the Natural Resources Institute Finland (Luke). Records on continuous daily measurements of CH4, milk yield, feed intake and BW measurements over 2 years period were compiled for data analysis. The daily CH4 output was calculated using carbon dioxide as a tracer method. Estimates from the non-invasive PAS-F10 technique were then tested against open-circuit indirect respiration calorimetric chamber measurements and against estimates from other widely used prediction models. Concordance analysis was used to establish agreement between the chamber and PAS-F10 methods. A linear mixed model was used for the analysis of the large continuous data. The daily CH4 output of cows was 555 l/day and ranged from 330 to 800 l/day. Dry matter intake, level of milk production, lactation stage and diurnal variation had significant effects on daily CH4 output. Estimates of the daily CH4 output from PAS-F10 technique compared relatively well with the other techniques. The concordance correlation coefficient between combined weekly CH4 output estimates of PAS-F10 and chamber was 0.84 with lower and upper confidence limits of 0.65 and 0.93, respectively. Similarly, when chamber CH4 measurements were predicted from PAS-F10 measurements, the mean of two separate weekly PAS-F10 measurements gave the lowest prediction error variance than either of the separate weekly PAS-F10 measurements alone. This suggests that every other week PAS-F10 measurements when combined would improve the estimation of CH4 output with PAS-F10 technique. The repeatability of daily CH4 output from PAS-F10 technique ranged from 0.40 to 0.46 indicating that some between-animal variation exist in CH4 output traits.

Type
Research Article
Copyright
© The Animal Consortium 2016 

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References

Bell, MJ, Saunders, N, Wilcox, RH, Homer, EM, Goodman, JR, Craigon, J and Garnsworthy, PC 2014. Methane emissions among individual dairy cows during milking quantified by eructation peaks or ratio with carbon dioxide. Journal of Dairy Science 97, 65367889.Google Scholar
Boadi, DA and Wittenberg, KM 2002. Methane production from dairy and beef heifers fed forages differing in nutrient density using the sulfur hexafluoride (SF6) tracer gas technique. Canadian Journal of Animal Science 82, 201206.Google Scholar
Broucek, J 2014. Production of methane emissions from ruminant husbandry: a review. Journal of Environmental Protection 5, 14821493.Google Scholar
Brouwer, E 1965. Report of subcommittee on constants and factors. In Proceedings of the 3rd EAAP Symposium on Energy Metabolism, Troon, Publ. 11, Academic Press, London, pp. 441–443.Google Scholar
Chagunda, MGG, Römer, DAM and Roberts, DJ 2009. On the use of a laser methane detector in dairy cows. Computers and Electronics in Agriculture 96, 157160.Google Scholar
Chagunda, MGG and Yan, T 2011. Do methane measurements from a laser detector and an indirect open-circuit respiration calorimetric chamber agree sufficiently closely? Animal Feed Science and Technology 165, 814.Google Scholar
de Haas, Y, Windig, JJ, Calus, MPL, Dijkstra, J, de Haan, M, Bannink, A and Veerkamp, RF 2011. Genetic parameters for predicted methane production and potential for reducing enteric emissions through genomic selection. Journal of Dairy Science 94, 61226134.Google Scholar
Ellis, JL, Kebreab, E, Odondo, NE, McBride, BW, Okine, EK and France, J 2007. Prediction of methane production from dairy and beef cattle. Journal of Dairy Science 90, 34563467.Google Scholar
Garnsworthy, PC, Craigon, J, Hernandez-Medrano, H and Saunders, N 2012a. On-farm methane measurements during milking correlate with total methane production by individual dairy cows. Journal of Dairy Science 95, 31663180.Google Scholar
Garnsworthy, PC, Craigon, J, Hernandez-Medrano, H and Saunders, N 2012b. Variation among individual dairy cows in methane measurements made on farm during milking. Journal of Dairy Science 95, 31813189.Google Scholar
Grainger, C, Clarke, T, McGinn, SM, Auldist, MJ, Beauchemin, KA, Hannah, MC, Waghorn, GC, Clark, H and Eckard, RJ 2007. CH4 emissions from dairy cows measured using the sulfur hexafluoride (SF6) tracer and chamber techniques. Journal of Dairy Science 90, 27552766.Google Scholar
Haisch, C 2012. Photoacoustic spectroscopy for analytical measurements. Measurement Science and Technology 23, 012001.Google Scholar
Hammond, KJ, Burke, JL, Koolaard, JP, Muetzel, S, Pinares-Patiño, CS and Waghorn, GC 2013. Effects of feed intake on enteric methane emissions from sheep fed fresh white clover (Trifolium repens) and perennial ryegrass (Lolium perenne) forages. Animal Feed Science Technology 197, 121132.Google Scholar
Hellwing, ALF, Lund, P, Madsen, J and Weisbjerg, MR 2013. Comparison of enteric methane production predicted from the CH4/CO2 ration and measured in respiration chambers. Advances in Animal Biosciences 4, 557.Google Scholar
Hindrichsen, IK, Wettstein, H-R, Machmuller, A and Kreuzer, M 2006. CH4 emission, nutrient degradation and nitrogen turnover in dairy cows and their slurry at different milk production scenarios with and without concentrate supplementation. Agriculture, Ecosystems and Environment 113, 150161.Google Scholar
Intergovernmental Panel on Climate Change (IPCC) 1997. Revised 1996 IPCC guidelines for national greenhouse gas inventories. Intergovernmental Panel on Climate Change, Bracknell, UK.Google Scholar
Johnson, KA and Johnson, DE 1995. Methane emissions from cattle. Journal of Animal Science 73, 24832492.Google Scholar
Kebreab, E, Clark, K, Wagner-Riddle, C and France, J 2006. Methane and nitrous oxide emissions from Canadian animal agriculture: a review. Canadian Journal of Animal Science 86, 135158.Google Scholar
Kinsman, R, Sauer, FD, Jackson, HA and Wolynetz, MS 1995. Methane and carbon dioxide emissions from dairy cows in full lactation monitored over a six-month period. Journal of Dairy Science 78, 27602766.Google Scholar
Kirchgeβer, M, Windisch, W and Muller, HL 1995. Nutritional factors for the quantification of methane production. In: Ruminant physiology: digestion, metabolism, growth and reproduction: proceedings of the eighth international symposium on ruminant physiology (ed. W Von Engelhardt, S Leonhard-Marek, G Breves and D Giesecke), pp. 333348. Ferdinand Enke Verlag, Stuttgart, Germany.Google Scholar
Knapp, JR, Laur, GL, Vadas, PA, Weiss, WP and Tricarico, JM 2015. Invited review: enteric methane in dairy cattle production: quantifying the opportunities and impact of reducing emissions. Journal of Dairy Science 97, 32313261.Google Scholar
Kuusela, T and Kauppinen, J 2007. ‘Photoacoustic gas analysis using interferometric cantilever microphone’: invited review paper. Applied Spectroscopy Reviews 42, 443474.Google Scholar
Larsen, T and Nielsen, NI 2005. Fluorometric determination of b-hydroxybutyrate in milk and blood plasma. Journal of Dairy Science 88, 20042009.Google Scholar
Lassen, J, Løvendahl, P and Madsen, J 2012. Accuracy of noninvasive breath methane measurements using Fourier transform infrared methods on individual cows. Journal of Dairy Science 95, 890898.Google Scholar
Lin, L 1989. A concordance correlation coefficient to evaluate reproducibility. Biometrics 45, 255268.Google Scholar
Natural Resources Institute Finland (Luke) 2015. Feed tables and feeding recommendations. Retrieved on 14 June 2015 from https://portal.mtt.fi/portal/page/portal/Rehutaulukot/feed_tables_english/feed_tables/basis_of_calculations/energy_value_ruminants Google Scholar
Madsen, J, Bjerg, BS, Hvelplund, T, Weisbjerg, MR and Lund, P 2010. Methane and carbon dioxide ratio in excreted air for quantification of methane production in ruminants. Livestock Science 129, 223227.Google Scholar
Mäntysaari, P and Mäntysaari, EA 2015. Modeling of daily body weights and body weight changes of Nordic Red cows. Journal of Dairy Science 98, 69927002.Google Scholar
McBride, J, Morrison, SJ and Yan, T 2013. Review of enteric methane emission of cattle and sheep fed diets relevant to UK farming conditions. Advances in Animal Biosciences 4, 299.Google Scholar
McCourt, A, Yan, T, Mayne, CS and Porter, MG 2005. Prediction of CH4 output in beef cattle from indirect respiration calorimetry data. In Proceedings of the 2nd International Conference on Greenhouse Gases and Animal Agriculture, Publ. Series, Institute of Animal Science 27 (ed. CR Soliva, J Takahashi and M Kreuzer), pp. 405–408. ETH-Centre, Zurich, Switzerland.Google Scholar
Murray, RM, Bryant, AM and Leng, RA 1976. Rates of production of methane in the rumen and large intestine of sheep. British Journal of Nutrition 36, 114.Google Scholar
Negussie, E, Mäntysaari, P, Mäntysaari, EA and Lidauer, M 2014. Animal wise variation in enteric methane output traits and its relationships with feed efficiency in dairy cattle: a longitudinal model analysis. In Proceedings of the 10th World Congress of Genetics Applied to Livestock Production, 3pp.Google Scholar
Pedersen, S, Blanes-Vidal, V, Jørgensen, H, Chwalibog, A, Haeussermann, A, Heetkamp, MJW and Aarnink, AJA 2008. Carbon dioxide production in animal houses: a literature review. Agricultural Engineering International CIGR E-Journal X, BC 08 008, 19pp.Google Scholar
Pinares-Patiño, CS, Hickey, SM, Young, EA, Dodds, KG, MacLean, S, Molano, G, Sandoval, E, Kjestrup, H, Harland, R, Hunt, C, Pickering, NK and McEwan, JC. 2013. Heritability estimates of methane emissions from sheep. Animal 7, 316321.Google Scholar
Pinares-Patiño, CS, Waghorn, GC, Machmüller, A, Vlaming, B, Molano, G, Cavanagh, A and Clark, H 2007. Methane emissions and digestive physiology of non-lactating dairy cows fed pasture forage. Canadian Journal of Animal Science 87, 601613.Google Scholar
Reynolds, CK, Crompton, LA and Millis, JAN 2011. Improving the efficiency of energy utilization in cattle. Animal Production Science 51, 612.Google Scholar
Storlien, TM, Adler, S, Thuen, E and Harstad, OM 2013. Effect of silage botanical composition on greenhouse gas emissions from dairy cows. Advances in Animal Biosciences 4, 360.Google Scholar
Storm, IMLD, Hellwing, ALF, Nielsen, NI and Madsen, J 2012. Methods for measuring and estimating CH4 emission from ruminants. Animals 2, 160183.Google Scholar
Wilkerson, VA, Casper, DP and Mertens, DR 1995. The prediction of methane production of Holstein cows by several equations. Journal of Dairy Science 78, 24022414.Google Scholar
Yan, T, Mayne, CS and 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, Zurich, Switzerland, pp. 131–134.Google Scholar
Yan, T, Mayne, CS, Gordon, FG, Porter, MG, Agnew, RE, Patterson, DC, Ferris, CP and Kilpatrick, DJ 2010. Mitigation of enteric methane emissions through improving efficiency of energy utilization and productivity in lactating dairy cows. Journal of Dairy Science 93, 26302638.Google Scholar