ReviewAnimals : an open access journal from MDPI2024
Advances in Methane Emission Estimation in Livestock: A Review of Data Collection Methods, Model Development and the Role of AI Technologies.
Review in Animals : an open access journal from MDPI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 53 citations in OpenAlex.
- Optimisation of selection for methane mitigation by integrating production traits with ruminal microbiome-driven breeding in beef cattle.Genetics, selection, evolution : GSE · 2026Article
- - Invited Review - Advancing precision livestock farming: integrating artificial intelligence and emerging technologies for sustainable livestock management.Animal bioscience · 2026Article
- Data-Driven Prediction of Ammonia and Methane Concentrations and Emissions in Dairy Barns Using Artificial Neural Networks.Animals : an open access journal from MDPI · 2026Article
- Gated recurrent unit model for forecasting greenhouse gas concentrations with uncertainty quantification.Frontiers in artificial intelligence · 2026Article
- Estimation of the sample size to determine gas flux in finishing steers under confined conditions using alternative statistical approaches.Translational animal science · 2026Article
- Artificial Neural Networks for Predicting Emissions from the Livestock Sector: A Review.Animals : an open access journal from MDPI · 2025Review
- Dairy Barn Methane Levels and Feasibility of Thermal Catalytic Oxidation for Net Climate Benefit.Environmental science & technology · 2025Article
- Genomics and phenomics: Who will be the dairy cows of the future?JDS communications · 2025Review
- Spatiotemporal evolution regional differences and decoupling effects of greenhouse gas emissions from animal husbandry in Henan Province.Scientific reports · 2025Article
- Sugarcane Extract (Polygain™) Supplementation Reduces Enteric Methane Emission in Dairy Calves.Animals : an open access journal from MDPI · 2025Article
- Bridging research and practice using digital twin modeling to mitigate methane emissions across dairy production stages.Journal of animal science · 2025Article
- Innovative lipid delivery systems in ruminant diets: the role of spray drying.Frontiers in veterinary science · 2025Review
- Predicting Enteric Methane Emissions from Dairy and Beef Cattle Using Nutrient Composition and Intake Variables.Animals : an open access journal from MDPI · 2024Article
- Enteric Methane Emission in Livestock Sector: Bibliometric Research from 1986 to 2024 with Text Mining and Topic Analysis Approach by Machine Learning Algorithms.Animals : an open access journal from MDPI · 2024Review
- In-Depth Development of a Versatile Rumen Bolus Sensor for Dairy Cattle.Sensors (Basel, Switzerland) · 2024Review
- Relationship between Dairy Cow Health and Intensity of Greenhouse Gas Emissions.Animals : an open access journal from MDPI · 2024Review
- Examining hydrogen peroxide-containing organelles in seaweeds.microPublication biology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 2 countries.
Funding
Abstract
This review examines the significant role of methane emissions in the livestock industry, with a focus on cattle and their substantial impact on climate change. It highlights the importance of accurate measurement and management techniques for methane, a potent greenhouse gas accounting for 14-16% of global emissions. The study evaluates both conventional and AI-driven methods for detecting methane emissions from livestock, particularly emphasizing cattle contributions, and the need for region-specific formulas. Sections cover livestock methane emissions, the potential of AI technology, data collection issues, methane's significance in carbon credit schemes, and current research and innovation. The review emphasizes the critical role of accurate measurement and estimation methods for effective climate change mitigation and reducing methane emissions from livestock operations. Overall, it provides a comprehensive overview of methane emissions in the livestock industry by synthesizing existing research and literature, aiming to improve knowledge and methods for mitigating climate change. Livestock-generated methane, especially from cattle, is highlighted as a crucial factor in climate change, and the review underscores the importance of integrating precise measurement and estimation techniques for effective mitigation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.