Literature DB >> 26245140

Methane production and diurnal variation measured in dairy cows and predicted from fermentation pattern and nutrient or carbon flow.

M Brask1, M R Weisbjerg1, A L F Hellwing1, A Bannink2, P Lund1.   

Abstract

Many feeding trials have been conducted to quantify enteric methane (CH(4)) production in ruminants. Although a relationship between diet composition, rumen fermentation and CH(4) production is generally accepted, the efforts to quantify this relationship within the same experiment remain scarce. In the present study, a data set was compiled from the results of three intensive respiration chamber trials with lactating rumen and intestinal fistulated Holstein cows, including measurements of rumen and intestinal digestion, rumen fermentation parameters and CH(4) production. Two approaches were used to calculate CH(4) from observations: (1) a rumen organic matter (OM) balance was derived from OM intake and duodenal organic matter flow (DOM) distinguishing various nutrients and (2) a rumen carbon balance was derived from carbon intake and duodenal carbon flow (DCARB). Duodenal flow was corrected for endogenous matter, and contribution of fermentation in the large intestine was accounted for. Hydrogen (H(2)) arising from fermentation was calculated using the fermentation pattern measured in rumen fluid. CH(4) was calculated from H(2) production corrected for H(2) use with biohydrogenation of fatty acids. The DOM model overestimated CH(4)/kg dry matter intake (DMI) by 6.1% (R(2)=0.36) and the DCARB model underestimated CH(4)/kg DMI by 0.4% (R(2)=0.43). A stepwise regression of the difference between measured and calculated daily CH(4) production was conducted to examine explanations for the deviance. Dietary carbohydrate composition and rumen carbohydrate digestion were the main sources of inaccuracies for both models. Furthermore, differences were related to rumen ammonia concentration with the DOM model and to rumen pH and dietary fat with the DCARB model. Adding these parameters to the models and performing a multiple regression against observed daily CH(4) production resulted in R 2 of 0.66 and 0.72 for DOM and DCARB models, respectively. The diurnal pattern of CH(4) production followed that of rumen volatile fatty acid (VFA) concentration and the CH(4) to CO(2) production ratio, but was inverse to rumen pH and the rumen hydrogen balance calculated from 4×(acetate+butyrate)/2×(propionate+valerate). In conclusion, the amount of feed fermented was the most important factor determining variations in CH(4) production between animals, diets and during the day. Interactions between feed components, VFA absorption rates and variation between animals seemed to be factors that were complicating the accurate prediction of CH(4). Using a ruminal carbon balance appeared to predict CH(4) production just as well as calculations based on rumen digestion of individual nutrients.

Entities:  

Keywords:  VFA; carbon; dairy cow; enteric fermentation; modelling methane

Mesh:

Substances:

Year:  2015        PMID: 26245140     DOI: 10.1017/S1751731115001184

Source DB:  PubMed          Journal:  Animal        ISSN: 1751-7311            Impact factor:   3.240


  3 in total

1.  Prediction of enteric methane emissions from lactating cows using methane to carbon dioxide ratio in the breath.

Authors:  Tomoyuki Suzuki; Yuko Kamiya; Kohei Oikawa; Itoko Nonaka; Takumi Shinkai; Fuminori Terada; Taketo Obitsu
Journal:  Anim Sci J       Date:  2021       Impact factor: 1.974

2.  Diurnal Dynamics of Gaseous and Dissolved Metabolites and Microbiota Composition in the Bovine Rumen.

Authors:  Henk J van Lingen; Joan E Edwards; Jueeli D Vaidya; Sanne van Gastelen; Edoardo Saccenti; Bartholomeus van den Bogert; André Bannink; Hauke Smidt; Caroline M Plugge; Jan Dijkstra
Journal:  Front Microbiol       Date:  2017-03-17       Impact factor: 5.640

3.  Genetic parameters of methane emissions determined using portable accumulation chambers in lambs and ewes grazing pasture and genetic correlations with emissions determined in respiration chambers.

Authors:  Arjan Jonker; Sharon M Hickey; Suzanne J Rowe; Peter H Janssen; Grant H Shackell; Sarah Elmes; Wendy E Bain; Janine Wing; Gordon J Greer; Brooke Bryson; Sarah MacLean; Ken G Dodds; Cesar S Pinares-Patiño; Emilly A Young; Kevin Knowler; Natalie K Pickering; John C McEwan
Journal:  J Anim Sci       Date:  2018-07-28       Impact factor: 3.159

  3 in total

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