An overview of current Dutch enteric methane research
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1 An overview of current Dutch enteric methane research Jan Dijkstra and André Bannink Wageningen UR, the Netherlands Research topics Netherlands: dairy cattle Covenant Clean and Efficient : 30% reduction 2020 compared with 1990 Mitigating CH 4 practical diets quality grass herbage and grass silage starch: concentrate / maize silage In vitro techniques Developments in modelling Indicator in milk 1
2 Starch content and fermentation rate Native vs gelatinized maize grain at high or low inclusion level in concentrate; grass silage/concentrate 60/40% Treatment P-value slow rapid rate level low high low high Starch (g/kg DM) Fract degr (%/h) < CH 4 (g/kg RFOM) <0.01 <0.01 CH 4 (g/kg DM) CH 4 (g/kg FPCM) Hatew et al. (2015) J Dairy Sci Maize silage: effect maturity at harvest Methane (g/kg DM or g/kg FPCM) per kg DM per kg FPCM maize silage (preliminary data) Van Gastelen et al. (2015) Benchaar et al. (2014) Hassanat et al. (2013) Diet starch content (g/kg DM) 2
3 Maize silage: effect maturity at harvest Methane (g/kg DM or g/kg FPCM) per kg DM per kg FPCM maize silage (preliminary data) Van Gastelen et al. (2015) Benchaar et al. (2014) Hassanat et al. (2013) Diet starch content (g/kg DM) Research topics Netherlands: dairy cattle Covenant Clean and Efficient : 30% reduction 2020 compared with 1990 Mitigating CH 4 practical diets quality grass herbage and grass silage starch: concentrate / maize silage In vitro techniques Developments in modelling Indicator in milk 3
4 In vitro techniques Methane production during in vitro gas production APES: automated pressure evaluation system gas samples at ~12 incubation time points for methane analysis Pellikaan et al. (2011) In vitro techniques Screening substrates / additives (e.g. tannins) Hydrogen dynamics 4
5 In vitro techniques Screening substrates / additives (e.g. tannins) Hydrogen dynamics Relationship with in vivo methane production? inoculum of adapted animal; substrate / additive dose In vitro (ml/g OM) and in vivo (ml/g OM) R 2 = 0.04; P=0.88 In vitro (ml/g OM) and in vivo (ml/g RFOM) R 2 = 0.54; P=0.040 Hatew et al. (2015) Anim Feed Sci Technol Research topics Netherlands: dairy cattle Covenant Clean and Efficient : 30% reduction 2020 compared with 1990 Mitigating CH 4 practical diets quality grass herbage and grass silage starch: concentrate / maize silage In vitro techniques Developments in modelling Indicator in milk 5
6 Mechanistic modelling Feed input Rumen Model Fermentation Small intestinal digestion Large Intestinal Model Fermentation Methane module Methane module H 2 source Acetate Butyrate Propionate Valerate Microbial growth with amino acids Microbial growth with ammonia Lipid hydrogenation CO 2 + 4H 2 Methane CH 4 +2H 2 O EXCESS H 2 sink H 2 (Dijkstra et al. 1992; Mills et al. 2001; Bannink et al. 2011) Application of mechanistic model Methane emission per kg milk Methane emission per unit GE Methane production (g/kg milk) IPCC Tier 2 (6.5% GE) - - mechanistic model Year MCF (% GE) Tier 2: 11% reduction Tier 3: 15% reduction Mechanistic model (Tier 3) IPCC Tier 2 (1997) IPCC Tier 2 (2006) Year (Dijkstra et al. 1992; Mills et al. 2001; Bannink et al. 2011) 6
7 Future developments modelling Develop user-friendly interface to Tier 3 model Future developments modelling 7
8 Future developments modelling Future developments modelling 8
9 Future developments modelling Develop user-friendly interface to Tier 3 model Integrate in ANCA (Annual Nutrient Cycling Assessment) farm specific production and excretion characteristics compulsory from 2016 onwards to demonstrate (legislation) and stimulate efficient, sustainable milk production ANCA: quantification of C, N, P cycles Develop user-friendly interface to Tier 3 model Integrate in ANCA (Annual Nutrient Cycling Assessment) farm specific production and excretion characteristics compulsory from 2016 onwards to demonstrate (legislation) and stimulate efficient, sustainable milk production 9
10 Future developments modelling Develop user-friendly interface to Tier 3 model Integrate in ANCA (Annual Nutrient Cycling Assessment) farm specific production and excretion characteristics compulsory from 2016 onwards to demonstrate (legislation) and stimulate efficient, sustainable milk production Improve mechanistic models hydrogen dynamics additives (e.g., nitrate) Research topics Netherlands: dairy cattle Covenant Clean and Efficient : 30% reduction 2020 compared with 1990 Mitigating CH 4 practical diets quality grass herbage and grass silage starch: concentrate / maize silage In vitro techniques Developments in modelling Indicator in milk 10
11 Indicator in milk Analysis of milk samples fatty acid profile (GC) polar metabolites ( 1 H-NMR metabolomics) volatile metabolites (GC-MS metabolomics) Indicator in milk Preliminary results first experiment grass silage vs. maize silage (n=32) Van Gastelen et al. (2015) methane g/kg DM and g/kg FPCM milk fatty acids only: R 2 = 0.53 and 0.51 all metabolites: R 2 = 0.69 and 0.68 g/kg DM: 1 fatty acid, 2 non-volatile metabolites g/kg FPCM: 1 fatty acid, 2 non-volatile, 1 volatile metabolite Further develop prediction equations using ~200 individual cows with chamber CH 4 data (with Food Quality & Design) 11
12 Exciting opportunities to mitigate CH 4 emissions jan.dijkstra@wur.nl andre.bannink@wur.nl 12
This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and
This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution
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