Innovative database and its potential to realise large scale study to quantify the impact of diet on CH4 emitted daily by dairy cows


  • Vanlierde, A. , Boulet, R. , Colinet, F. . , Gengler, N. , Soyeurt, H. , Dehareng, F. & Froidmont, E. (2017). Innovative database and its potential to realise large scale study to quantify the impact of diet on CH4 emitted daily by dairy cows. Proceedings in: EmiLi 2017 - Emissions of Gas and Dust from Livestock, Saint-Malo (France),
Type Conference Proceedings
Year of conference 2017
Title Innovative database and its potential to realise large scale study to quantify the impact of diet on CH4 emitted daily by dairy cows
Conference name EmiLi 2017 - Emissions of Gas and Dust from Livestock
Conference location Saint-Malo (France)
Abstract The main levers of action to reduce methane (CH4) emissions from cattle at the animal level are through breeding (1) and adaptation of the diet composition (DC) (2). Investigations on the impact of global DC on CH4 emission are always complicated because of the small number of animals used during those trials and because of their specificity on some feeding parameters without considering the global diet. Moreover detailed DC is rarely available in the classical performance recording databases, as are daily CH4 emission from dairy cows. Recent advances in the estimation of CH4 from milk mid infrared (MIR) spectra (3) make this data available in routine once a month through milk recording in Wallonia (South Belgium) allowing the organisation of large scale studies on dairy cows. In this context through collaboration with the feed company Dumoulin S.A. DC data was also available from 10 commercial farms from Wallonia, between January 2014 and June 2015 included. Indeed the composition of the diet given to the herd was recorded: components, proteins and energy levels, NDF, alpha-linolenic acid (ALA), fat, “sugar + starch”, etc. Moreover zootechnical data were also available (breed, days in milk (DIM), lactation number, milk yield, etc.). The DC of those farms differed in terms of main forages types (grass silage vs corn silage), F:C ratio and type of compound feed used (rich in “sugar + starch”, fat level, etc.). The objectives of this study was to use this novel and innovative database to evaluate the influence of some diet constituents on the level of CH4 emissions by considering the farm and the animal effect. Regarding conditions of use of the CH4 equation, only test-days from cows with a DIM between 5 and 365 (limits included) were included. Around 6800 records (predicted CH4 linked with diet and zootechnical data) from 1260 different cows were usable. In this specific case it was decided to focus on data from November to March included to remove the grazing data which are not easy to evaluate at nutritional level (quantity and quality). At the end 3456 records from 1040 different cows could be taken into account. First observations indicated the impact of three constituents on CH4 emission level seemed to be particularly interesting: global fat, ALA, and “sugar + starch” levels. The novel and innovative nature of the information included in this database allows several follow-up analyses that are currently ongoing with promising prospect.
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Authors Vanlierde, A., Boulet, R., Colinet, F. ., Gengler, N., Soyeurt, H., Dehareng, F., Froidmont, E.