Document details for 'Compositional mixed modelling of methane emissions and ruminal volatile fatty acids from individual cattle and multiple experiments'

Authors Palarea Albaladejo, J., Rooke, J.A., Nevison, I.M. and Dewhurst, R.J.
Publication details Journal of Animal Science 95, 2467-2480. American Society of Animal Science.
Publisher details American Society of Animal Science
Keywords methane production, volatile fatty acids, compositional data, mixed models
Abstract The aim of the study was establish if methane (CH4) yields (g/kg DM intake, DMI) could be predicted for individual cattle from rumen volatile fatty acid (VFA) molar proportions, and animal (DMI) and feed (forage:concentrate ratios and ME content) variables. The dataset available consisted of 284 measurements (from 6 experiments) for beef cattle of CH4 yields measured in indirect respiration chambers. A compositional modelling approach was employed where VFA measurements were considered as a whole, instead of in isolation, emphasizing their multivariate relative scale by means of a log-ratio coordinate representation. The analysis revealed expected close groupings of acetate and butyrate; propionate and valerate; iso-butyrate and iso-valerate. Linear mixed models were then fitted to investigate relationships between CH4 yield and VFA (represented by meaningful log-contrasts of its components called balances) while accounting for other animals and diet-related covariates. A model including a normalized balance representing (acetate + butyrate) / propionate best explained the contribution of VFA to CH4 yield variation. DMI, forage:concentrate proportion (expressed as a categorical variable diet-type: high concentrate, mixed forage:concentrate or high forage) and diet ME concentration were also statistically significant covariates. Our results provided new insights into the inter-relationships amongst VFA measurements and also between VFA and CH4 yield. In conclusion, it is possible to use VFA molar proportions to predict CH4 yields from individual cattle.
Last updated 2017-06-10
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  1. DOI
    doi:10.2527/jas.2016.1339

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