Identification of milk fatty acids as proxies of the enteric methane emissions in dairy cows

Abstract : Methane (CH4) is a potent greenhouse gas coming from the anaerobic microbial fermentation of the diet in the rumen. One of the main current challenge for the dairy sector is to find CH4 mitigation strategies (diets or genetics) without altering animal performance. Enteric methane measurement methods are costly and very difficult to apply on a large scale on field. Thus, there is a need to develop alternative measurement methods, such as equations based on proxies to predict CH4 emissions. Milk fatty acids (FA) have been identified as potential predictors of the methanogenesis in dairy cattle, but the prediction ability of extant published CH4 equations must be improved, and their domain of applicability must be enlarged to a wide range of diets. The objective of this PhD thesis was to confirm the potential of milk FA as proxies to predict enteric CH4 emissions in dairy cows fed a wide range of diets. Two databases (based on individual and mean data, respectively) were built thanks to an international collaboration, and gathered data on CH4, milk FA composition, dairy performances, diet and animal characteristics. Two in vivo experiments were conducted with the aim to study the effect of dietary strategies poorly documented, on methanogenesis and milk FA. The data from these experiments were included in the created database. Firstly, simple CH4 prediction equations were developed [g/d, g/kg of DMI (DMI), and g/kg of milk] based only on milk FA, and secondly other variables related to cow intake or characteristics, and dairy performance were added and constituted complex equations. Relationships between CH4 and several milk FA (C10:0, iso C17:0 + trans-9 C16:1, iso C16:0, cis-11 C18:1, cis-15 C18:1, cis-9,cis-12 C18:2, and trans-11,cis-15 C18 :2) were found, confirming common rumen metabolic pathways between methanogenesis and lipid metabolism. Equations were also closely related to the diets included in the database used for their development. Simple equations were less accurate than complex ones (prediction error of 58.6 g/d, 2.8 g/kg DMI and 3.7 g/kg milk vs 42.8 g/d, 2.5 g/kg DMI and 3.3 g/kg milk, respectively). A minimum difference of 16% in CH4 emissions between mitigating strategies can be evidenced with the best prediction equation developed in this PhD. Methane prediction equations based on milk FA well determined by infrared spectrometry methods need to be developed in order to be used on a routine basis and on a large scale. These prediction equations would allow studying the effect of novel mitigation strategies of enteric CH4 emissions in dairy cows.
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Adeline Bougouin. Identification of milk fatty acids as proxies of the enteric methane emissions in dairy cows. Agronomy. Université Clermont Auvergne, 2018. English. ⟨NNT : 2018CLFAC036⟩. ⟨tel-02426188v2⟩

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