Enteric methane (CH 4) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH 4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH 4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH 4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH 4 production (g/day per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross‐validate their performance; and (4) assess the trade‐off between availability of on‐farm inputs and CH 4 prediction accuracy. The intercontinental database covered Europe (EU), the United States (US), and Australia (AU). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU, and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH 4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH 4 emission conversion factors for specific regions are required to improve CH 4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction. For enteric CH 4 yield and intensity prediction, information on milk yield and composition is required for better estimation.

No abstract

a b s t r a c tIn vitro fermentation techniques (IVFT) have been widely used to evaluate the nutritive value of feeds for ruminants and in the last decade to assess the effect of different nutritional strategies on methane (CH4) production. However, many technical factors may influence the results obtained. The present review has been prepared by the 'Global Network' FACCE-JPI international research consortium to provide a critical evaluation of the main factors that need to be considered when designing, conducting and interpreting IVFT experiments that investigate nutritional strategies to mitigate CH 4 emission from ruminants. Given the increasing and wide-scale use of IVFT, there is a need to critically review reports in the literature and establish what criteria are essential to the establishment and implementation of in vitro techniques. Key aspects considered include: i) donor animal species and number of animal used, ii) diet fed to donor animals, iii) collection and processing of rumen fluid as inoculum, iv) choice of substrate and incubation buffer, v) incubation procedures and CH 4 measurements, vi) headspace gas composition and vii) comparability of in vitro and in vivo measurements. Based on an evaluation of experimental evidence, a set of technical recommendations are presented to harmonize IVFT for feed evaluation, assessment of rumen function and CH 4 production.

Review of current in vivo measurement techniques for quantifying enteric methane emission from ruminants.Animal Feed Science and Technology http://dx.doi.org/10. 1016/j.anifeedsci.2016.05.018 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. techniques based on short-term measurements of gas concentrations in samples of exhaled air. This includes automated head chambers (e.g. the GreenFeed system), the use of carbon dioxide (CO 2 ) as a marker, and (handheld) laser CH 4 detection. Each of the techniques are compared and assessed on their capability and limitations, followed by methodology recommendations. It is concluded that there is no "one size fits all" method for measuring CH 4 emission by individual animals. Ultimately, the decision as to which method to use should be based on the experimental objectives and resources available. However, the need for high throughput methodology e.g. for screening large numbers of animals for genomic studies, does not justify the use of methods that are inaccurate. All CH 4 measurement techniques are subject to experimental variation and random errors. Many sources of variation must be considered when measuring CH 4 concentration in exhaled air samples without a quantitative or at least regular collection rate, or use of a marker to indicate (or adjust) for the proportion of exhaled CH 4 sampled. Consideration of the number and timing of measurements relative to diurnal patterns of CH 4 emission and respiratory exchange are important, as well as consideration of feeding patterns and associated patterns of rumen 4 fermentation rate and other aspects of animal behaviour. Regardless of the method chosen, appropriate calibrations and recovery tests are required for both method establishment and routine operation. Successful and correct use of methods requires careful attention to detail, rigour, and routine self-assessment of the quality of the data they provide.

No abstract