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A dataset of descriptive information was compiled from 213 peer-reviewed scientific publications that focused on dairy cow experiments and measured enteric methane emissions. This dataset was primarily based on the bibliography used by Arndt et al. (2022), with the addition of studies conducted from 2019 to 2022. The articles were identified for inclusion in the dataset using the “Web of Science Core Collection” database, using various combinations of search terms related to methane, dairy, cattle, rumen, ruminant, energy balance, energy metabolism, energy partitioning, and enteric emissions. For inclusion in the dataset, studies had to be written in English and provide information on enteric methane emission, as well as report feed dry matter intake along with measures of variance. Both continuous and crossover design studies were included, resulting in a comprehensive dataset with 797 records (rows) and 162 variables (columns). The variables cover various aspects such as publication information, experimental design, animal description, methane measurement method, and diet nutrient composition. Additionally, when available, the dataset includes treatment means and measures of variance for feed dry matter intake, rumen fermentation parameters, nutrient digestibility, nitrogen excretion, milk yield, milk components, as well as enteric methane, carbon dioxide, and hydrogen emissions. Researchers can use this dataset to assess the effectiveness of different enteric methane mitigation strategies and their impact on milk yield and other essential dairy cow nutrition and performance variables. Furthermore, it offers the opportunity to explore potential interactions between nutrients and feed additives. |
