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Nutritional strategies, including feed management measures, are promising methods for CH4 and overall GHG reduction. Evidence from literature is reviewed in this article in relation to the effects of forage quality (digestible organic matter, DOM) and forage type (grasses vs. legumes, and maize). The major determinants of forage quality are botanical composition and phenological stage, i.e., at advanced growth stages of plants, the fibre content increases while DOM decreases. Methane yield (g/kg DMI) decreases with increased digestibility of forages in both dairy cattle and sheep, and also CH4 intensity (g/kg milk) decreases with increased digestibility of forages for dairy cattle. Using forage legumes in ruminant feeding systems can reduce overall GHG emissions due to decreased N fertilizer use and related emissions. Recommended dietary mitigation measures are often related to a reduction in N excretion such as better matching of dietary protein to animal needs, shifting N excretion from urine to faeces (by tannin inclusion at low levels) and reducing the amount of excreted fermentable organic matter. Methane decreases with increasing intake of forage legumes rich in tannins and there is a shift of N partition from urinary N towards faecal N. Reduced CH4 emissions from ruminants fed on forage‐based diets will decrease the carbon footprint of livestock and agriculture and improve the efficiency of productive ruminants in both developing and developed countries. Likewise, estimations of net CH4 output should account for enteric CH4 emissions and soil carbon (C) sequestration of land used for feed production (i.e., grasslands and croplands). [ABSTRACT FROM AUTHOR]

Growing demand for animal products has contributed to an increase in biogeochemical fluxes, leading particularly to gaseous ammonia, methane, and nitrous oxide emissions into the atmosphere. Developing accurate knowledge on the sources and magnitude of gas emissions from the livestock sector is essential to reducing emissions, while meeting other societal expectations, and to implementing effective regulations. To this end, a database called ELFE (ELevage et Facteurs d'Emission; i.e., Livestock and Emission Factors) was recently developed. It currently contains ∼5200 gas emission measurements extracted from 345 publications of the international literature published from 1964 to 2018 from 37 countries. One of its innovative aspects is the structured and comprehensive description of both the livestock system and the measurement method associated with emission data. Ammonia emitted by livestock systems represents 40 to 80% of emission values and 45 to 81% of the values concern production systems with slurry, depending on the animal produced. This database will contribute to improved emission factors for national inventories by more thoroughly considering factors influencing emission levels and data quality. It highlights the need for shared and standardized reporting protocols for both the livestock system itself and the measurement conditions, to allow for thorough comparisons and to reduce uncertainty in unit conversions. The database is available online on the Institut national de la recherche agronomique (INRA) platform (https://data.inra.fr/dataset.xhtml?persistentId=doi:10.15454/MHJPYT) and will be updated annually with new gas emissions. Core Ideas: A new database includes about 5200 emission values from 345 publications.Of these emission values, 62% were related to NH3, 41% to CH4, 29% to N2O, and 29% to CO2.The database includes a detailed description of production systems and measurement methods.Complete data for system description and unit conversion increase potential uses. [ABSTRACT FROM AUTHOR]

Abstract: Enteric methane (CH4) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH4 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 CH4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH4 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 CH4 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 CH4 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 CH4 emission conversion factors for specific regions are required to improve CH4 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 CH4 yield and intensity prediction, information on milk yield and composition is required for better estimation. [ABSTRACT FROM AUTHOR]