A global dataset of enteric methane mitigation experiments with beef cattle conducted from 1963 to 2023

Data and descriptive information were gathered from 226 peer-reviewed scientific publications from beef cattle experiments in which enteric methane and other animal response variables were measured. The dataset was based on the bibliography used by Arndt et al. (2022) but expanded to also include more recent studies published from 2019 to 2023. All articles were identified for inclusion in the dataset using the "Web of Science Core Collection", the "Commonwealth Agricultural Bureau International (CABI)", and the "EBSCO Discovery Service" databases with the search terms "methane" and "enteric" in combination with "beef", "cattle", "rumen", and "ruminant". Additionally, the search term "rumen" was used in combination with "energy balance", "energy metabolism", or "energy partitioning". For dataset inclusion, it was necessary for all studies to be written in English and at a minimum, quantify feed dry matter intake and enteric methane emissions as well as provide measures of variance for these estimates. Studies were primarily designed as completely randomized, randomized block, or crossover experiments. The dataset includes 895 records (rows) and 138 variables (columns). Reported variables include publication information, experimental design, animal description, methane measurement method, diet nutrient composition, and means and measures of variance for feed dry matter intake and enteric methane emissions. Additionally, depending on the study, data reported on rumen fermentation parameters, nutrient digestibility, nitrogen excretion, weight gain, and carbon dioxide and hydrogen emissions were included. This dataset can be used to explore the efficacy of enteric methane mitigation strategies and their impact on beef cattle nutrition and production. Furthermore, the dataset can potentially be used to investigate possible nutrient and feed additive interactions. (c) 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)