Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-26T19:35:03.188Z Has data issue: false hasContentIssue false
  • English
  • Français

Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows

Published online by Cambridge University Press:  28 February 2012

F. Dehareng ,
C. Delfosse ,
E. Froidmont ,
H. Soyeurt ,
C. Martin ,
N. Gengler ,
A. Vanlierde  and
P. Dardenne
F. Dehareng*
Affiliation:
Valorisation of Agricultural Products Department, Walloon Agricultural Research Centre, B-5030 Gembloux, Belgium
C. Delfosse
Affiliation:
Valorisation of Agricultural Products Department, Walloon Agricultural Research Centre, B-5030 Gembloux, Belgium
E. Froidmont
Affiliation:
Department of Production and Sectors, Walloon Agricultural Research Centre, B-5030 Gembloux, Belgium
H. Soyeurt
Affiliation:
Animal Science Unit, Gembloux Agro Bio-Tech, University of Liège, B-5030 Gembloux, Belgium National Fund for Scientific Research, B-1000 Brussels, Belgium
C. Martin
Affiliation:
UR1213 Herbivores, INRAClermont-Theix Research Centre, F-63122 Saint Genès Champanelle, France
N. Gengler
Affiliation:
Animal Science Unit, Gembloux Agro Bio-Tech, University of Liège, B-5030 Gembloux, Belgium National Fund for Scientific Research, B-1000 Brussels, Belgium
A. Vanlierde
Affiliation:
Valorisation of Agricultural Products Department, Walloon Agricultural Research Centre, B-5030 Gembloux, Belgium
P. Dardenne
Affiliation:
Valorisation of Agricultural Products Department, Walloon Agricultural Research Centre, B-5030 Gembloux, Belgium
*
†E-mail: dehareng@cra.wallonie.be
Get access

Abstract

This study investigates the feasibility to predict individual methane (CH4) emissions from dairy cows using milk mid-infrared (MIR) spectra. To have a large variability of milk composition, two experiments were conducted on 11 lactating Holstein cows (two primiparous and nine multiparous). The first experiment aimed to induce a large variation in CH4 emission by feeding two different diets: the first one was mainly composed of fresh grass and sugar beet pulp and the second one of maize silage and hay. The second experiment consisted of grass and corn silage with cracked corn, soybean meal and dried pulp. For each milking period, the milk yields were recorded twice daily and a milk sample of 50 ml was collected from each cow and analyzed by MIR spectrometry. Individual CH4 emissions were measured daily using the sulfur hexafluoride method during a 7-day period. CH4 daily emissions ranged from 10.2 to 47.1 g CH4/kg of milk. The spectral data were transformed to represent an average daily milk spectrum (AMS), which was related to the recorded daily CH4 data. By assuming a delay before the production of fermentation products in the rumen and their use to produce milk components, five different calculations were used: AMS at days 0, 0.5, 1, 1.5 and 2 compared with the CH4 measurement. The equations were built using Partial Least Squares regression. From the calculated R2cv, it appears that the accuracy of CH4 prediction by MIR changed in function of the milking days. In our experimental conditions, the AMS at day 1.5 compared with the measure of CH4 emissions gave the best results. The R2 and s.e. of the cross-validation were equal to 0.79 and 5.14 g of CH4/kg of milk. The multiple correlation analysis performed in this study showed the existence of a close relationship between milk fatty acid (FA) profile and CH4 emission at day 1.5. The lower R2 (R2 = 0.76) obtained between FA profile and CH4 emission compared with the one corresponding to the obtained calibration (R2c = 0.87) shows the interest to apply directly the developed CH4 equation instead of the use of correlations between FA and CH4. In conclusion, our preliminary results suggest the feasibility of direct CH4 prediction from milk MIR spectra. Additional research has the potential to improve the calibrations even further. This alternative method could be useful to predict the individual CH4 emissions at farm level or at the regional scale and it also could be used to identify low-CH4-emitting cows.

Keywords

methanemid-infraredmilkspectracows
Type
Full Paper
Information
animal , Volume 6 , Issue 10 , October 2012 , pp. 1694 - 1701
Copyright
Copyright © The Animal Consortium 2012

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.)

Footnotes

*

These authors contributed equally to the study.

References

Beauchemin, KA, McAllister, TA, McGinn, SM 2009. Dietary mitigation of enteric methane from cattle. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources 4, 1–18.CrossRefGoogle Scholar
Bauman, DE, Griinari, JM 2003. Nutritional regulation of milk fat synthesis. Annual Review of Nutrition 23, 203–227.CrossRefGoogle ScholarPubMed
Bell, MJ, Wall, E, Russell, G, Morgan, C, Simm, G 2010. Effect of breeding for milk yield, diet and management on enteric methane emissions from dairy cows. Animal Production Science 50, 817–826.CrossRefGoogle Scholar
Chilliard, Y, Martin, C, Rouel, J, Doreau, M 2009. Milk fatty acids in dairy cows fed whole crude linseed, extruded linseed, or linseed oil, and their relationship with CH4 output. Journal of Dairy Science 92, 5199–5211.CrossRefGoogle ScholarPubMed
Clark, H 2010. Animal vs. measurement technique variability in enteric methane production – is the measurement resolution sufficient? In Proceedings of the 4th International Conference on Greenhouse Gases and Animal Agriculture Banff, CA (ed. EJ Mc Geough and SM McGinn), 48pp.Google Scholar
Collomb, M, Bütikofer, U, Sieber, R, Jeangros, B, Bosset, J-O 2002. Correlation between fatty acids in cows’ milk fat produced in the Lowlands, Mountains and Highlands of Switzerland and botanical composition of the fodder. International Dairy Journal 12, 661–666.CrossRefGoogle Scholar
Delfosse, C, Froidmont, E, Fernandez Pierna, JA, Martin, C, Dehareng, F 2010. Estimation of methane emission by dairy cows on the basis of milk composition. In Proceedings of the 4th International Conference on Greenhouse Gases and Animal Agriculture Banff, CA (ed. EJ Mc Geough and SM McGinn), 168pp.Google Scholar
Demeyer, D, Fievez, V 2000. Ruminants et environnement: la méthanogenèse. Annales de Zootechie 49, 95–112.CrossRefGoogle Scholar
Dijkstra, J, Apajalahti, JA, Bannink, A, Gerrits, WJJ, Newbold, JR, Perdok, HB, van Zijderveld, SM, Berends, H 2010. Relationship of milk fatty acid profile with methane production in dairy cattle. In Proceedings of the 4th International Conference on Greenhouse Gases and Animal Agriculture Banff, CA (ed. EJ Mc Geough and SM McGinn), 169pp.Google Scholar
Food and Agriculture Organization (FAO) 2010. New FAO report assesses dairy greenhouse gas emissions. Retrieved November, 2011, from http://www.fao.org/news/story/en/item/41348/icode/ Google Scholar
Fuglestvedt, J 2009. Impacts of metric choice on analyzing the climate effects of emissions. IPCC Expert Meeting on the Science of Alternative Metrics, Oslo, Norway, pp. 40–47.Google Scholar
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.CrossRefGoogle ScholarPubMed
Johnson, KA, Johnson, DE 1995. Methane emissions from cattle. Journal of Animal Science 73, 2483–2492.CrossRefGoogle ScholarPubMed
Johnson, KA, Huyler, M, Westberg, H, Lamb, B, Zimmerman, P 1994. Measurement of CH4 emissions from ruminant livestock using a sulphur hexafluoride tracer technique. Environmental Science & Technology 28, 359–362.CrossRefGoogle Scholar
Jouany, JP 2008. Enteric CH4 production by ruminants and its control. In Gut efficiency: the key ingredient in ruminant production. Elevating animal performance and health (ed. S Andrieu and D Wilde), pp. 35–59. Wageningen Academic Publishers, Waginingen, the Netherlands.Google Scholar
Lassey, KR, Uylatt, MJ, Martin, RJ, Walker, CF, Shelton, ID 1997. Methane emissions measured directly from grazing livestock in New Zealand. Atmospheric Environment 31, 2905–2914.CrossRefGoogle Scholar
Martin, C, Doreau, M, Morgavi, DP 2010. Methane mitigation in ruminants: from microbe to the farm scale. Animal 4, 351–365.CrossRefGoogle Scholar
Martin, C, Rouel, J, Jouany, JP, Doreau, M, Chilliard, Y 2008. Methane output and diet digestibility in response to feeding dairy cows crude linseed, extruded linseed, or linseed oil. Journal of Animal Science 86, 2642–2650.CrossRefGoogle ScholarPubMed
Miettinen, H, Huhtanen, P 1996. Effects of the ration of ruminal propionate to butyrate on milk yield and blood metabolites in dairy cows. Journal of Dairy Science 79, 851–861.CrossRefGoogle Scholar
Ørskov, ER, Fraser, C, Kay, RNB 1969. Dietary factors influencing the digestion of starch in the rumen and small and large intestine of early weaned lambs. British Journal of Nutrition 23, 217–226.CrossRefGoogle ScholarPubMed
Soyeurt, H, Dardenne, P, Dehareng, F, Bastin, C, Gengler, N 2009. Genetic parameters of saturated and monounsaturated fatty acid content and the ratio of saturated to unsaturated fatty acids in bovine milk. Journal of Dairy Science 91, 3611–3626.CrossRefGoogle Scholar
Soyeurt, H, Dehareng, F, Gengler, N, McParland, S, Wall, E, Berry, DP, Coffey, M, Dardenne, P 2011. Mid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems and countries. Journal of Dairy Science 94, 1657–1667.CrossRefGoogle ScholarPubMed
Soyeurt, H, Dardenne, P, Dehareng, F, Lognay, G, Veselko, D, Marlier, M, Bertozzi, C, Mayeres, P, Gengler, N 2006. Estimating fatty acid content in cow milk using mid-infrared spectrometry. Journal of Dairy Science 89, 3690–3695.CrossRefGoogle ScholarPubMed
Vermorel, M 1995. Emissions annuelles de méthane d'origine digestive par les bovins en France: variation selon le type d'animal et le niveau de production. INRA Productions Animales 8, 265–272.CrossRefGoogle Scholar
Vlaeminck, B, 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, 43–47.Google ScholarPubMed
Weill, W, Chesneau, G, Chilliard, Y, Doreau, M, Martin, C 2009. June 24, Method for evaluating the amount of CH4 produced by a dairy ruminant and method for decreasing and controlling this amount. World Patent WO/2009/156453.Google Scholar
Weill, P, Kerhoas, N, Chesneau, G, Schmitt, B, Legrand, P, Rennaud, JP 2008. Existe t-il un lien entre production de méthane par les vaches laitières et profil en acides gras des laits? Nutrition clinique et métabolisme 22, 71–72.Google Scholar
Williams, PC, Sobering, DC 1993. Comparison of commercial near infrared transmittance and reflectance instruments for the analysis of whole grains and seeds. Journal of Near Infrared Spectroscopy 1, 25–33.CrossRefGoogle Scholar