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Tropentag, September 17 - 19, 2014 in Prague, Czech Republic

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Milk Fatty Acids Relationships with Methane Emissions from Dairy Cattle: A Step Beyond Predictions Models

JoaquĆ­n Castro-Montoya1, Veerle Fievez2, Nico Peiren3, Bernard De Baets4, Sam De Campeneere5

1University of Hohenheim, Animal Nutrition and Rangeland Management in the Tropics and Subtropics, Germany
2Gent University, Dept. of Animal Production (Lanupro), Belgium
3Institute for Agriculture and Fisheries Research, Belgium
4Gent University, Dept. of Applied Mathematics, Biometrics and Process Control, Belgium
5Institute for Agriculture and Fisheries Reserach, ILVO, Belgium


Around the world, growing demand for dairy products is changing milk production towards increased intensity and its concomitant changes in greenhouse gases emissions, which should be quantified and managed accordingly. Particularly for methane (CH4), several approaches have been used to quantify/estimate emissions from cattle. Milk fatty acids (MFA) have been previously used to develop predictive models for CH4 from dairy cows. However, small data sets and low variability prevent these models from accurately predicting CH4 under more general conditions. In this study, a data set containing 145 observations from 9 experiments with dairy cows was used to develop models to predict CH4 expressed in four functional units (g/d, g/kg DMI, g/kg milk and g/kg BW0.75/d) and to explore the ability of MFA to differentiate high from low CH4-emitter animals. A generalised linear mixed model was fitted to the data, and the variance explained by fixed (marginal R2(m)) and random (conditional R2(c)) effects were calculated for model evaluation. Variance explained by MFA (R2(m)) ranged from 0.19 (g CH4/kg BW0.75/d) to 0.55 (g CH4/kg DMI). Standardized coefficients showed that C17:0 and cis-9 C17:1 are highly relevant for CH4 prediction. Furthermore, the Gini coefficient and Lorenz curve, parameters normally applied in economics, were used to represent the distribution of MFA and its relationship with CH4. Gini coefficients for daily CH4 and CH4 relative to DMI were calculated for subsets of the data according to their cumulative abundance (below 0.625 g/100 g MFA (Group 0.625); between 0.625 and 2.5 g/100 g MFA (Group 2.5); between 2.5 and 10 g/100 g MFA (Group 10); above 10 g/100 g MFA (Group 100)). Methane measurements were divided into HIGH, MEDIUM and LOW. For daily CH4, Gini coefficients of MFA profiles in the category HIGH were different from the other categories for Group 10 and Group 0.625. For CH4 relative to DMI, category HIGH had a higher Gini coefficient for every group, with greater differences than those found for daily CH4. Milk FA hold a modest potential to predict amounts of CH4 emitted by dairy cows, but they might have potential to identify high from low emitter animals.

Keywords: Dairy, methane, milk fatty acids, prediction

Contact Address: Joaquín Castro-Montoya, University of Hohenheim, Animal Nutrition and Rangeland Management in the Tropics and Subtropics, Fruwirthstrasse 31, 70599 Stuttgart, Germany, e-mail: jcm@uni-hohenheim.de

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