Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Microbes and Methanogenesis01:26

Microbes and Methanogenesis

91
Methanogenesis is a critical microbial process in anaerobic ecosystems responsible for the biological production of methane, a potent greenhouse gas and valuable biofuel. This metabolic pathway is primarily facilitated by methanogenic archaea, which thrive in anoxic environments such as wetlands, sediments, and animal gastrointestinal tracts. The absence of oxygen in these habitats prevents aerobic respiration, thereby favoring alternative biochemical pathways for organic matter degradation.In...
91

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Herd-Level Prevalence of High Fat-to-Protein Ratio and Associated Factors During Early Lactation in Irish Spring-Calving Dairy Herds.

Animals : an open access journal from MDPI·2025
Same author

Between-country differences in the psychosocial profiles of British cattle farmers.

The Veterinary record·2025
Same author

Herd-Level Risk Factors Associated with <i>Mycoplasma bovis</i> Serostatus in Youngstock on Irish Dairy Farms.

Animals : an open access journal from MDPI·2024
Same author

Identification of Predictive Biomarkers of Lameness in Transition Dairy Cows.

Animals : an open access journal from MDPI·2024
Same author

Footbathing and Foot Trimming, and No Quarantine: Risks for High Prevalence of Lameness in a Random Sample of 269 Sheep Flocks in England, 2022.

Animals : an open access journal from MDPI·2024
Same author

Using Object-Oriented Simulation to Assess the Impact of the Frequency and Accuracy of Mobility Scoring on the Estimation of Epidemiological Parameters for Lameness in Dairy Herds.

Animals : an open access journal from MDPI·2024

Related Experiment Video

Updated: May 5, 2026

The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals
11:02

The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals

Published on: September 7, 2015

22.2K

Evaluating Equations for Predicting Enteric Methane Emissions in Dairy Cattle.

Fern T Baker1,2, Luke O'Grady1,3, Martin J Green1

  • 1School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire LE12 5RD, UK.

Animals : an Open Access Journal From MDPI
|May 4, 2026
PubMed
Summary
This summary is machine-generated.

Dairy cattle enteric methane emissions (EMEs) vary widely due to inconsistent prediction equations. A new combined equation using metabolised energy and neutral detergent fibre offers a more reliable average prediction for EMEs.

Keywords:
enteric fermentationenteric methane prediction equationsneutral detergent fibre (NDF) and metabolised energy (ME)

More Related Videos

Measuring Liver Mitochondrial Oxygen Consumption and Proton Leak Kinetics to Estimate Mitochondrial Respiration in Holstein Dairy Cattle
08:29

Measuring Liver Mitochondrial Oxygen Consumption and Proton Leak Kinetics to Estimate Mitochondrial Respiration in Holstein Dairy Cattle

Published on: November 30, 2018

10.6K
Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions
08:18

Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions

Published on: June 12, 2016

17.4K

Related Experiment Videos

Last Updated: May 5, 2026

The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals
11:02

The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals

Published on: September 7, 2015

22.2K
Measuring Liver Mitochondrial Oxygen Consumption and Proton Leak Kinetics to Estimate Mitochondrial Respiration in Holstein Dairy Cattle
08:29

Measuring Liver Mitochondrial Oxygen Consumption and Proton Leak Kinetics to Estimate Mitochondrial Respiration in Holstein Dairy Cattle

Published on: November 30, 2018

10.6K
Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions
08:18

Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions

Published on: June 12, 2016

17.4K

Area of Science:

  • Animal Science
  • Environmental Science
  • Agricultural Science

Background:

  • Dairy cattle enteric methane emissions (EMEs) are a significant environmental concern.
  • Existing prediction equations for EMEs show considerable variability, hindering comparisons and emission reduction efforts.
  • Inconsistencies in EME measurements complicate farm-to-farm comparisons and progress towards Net Zero goals.

Purpose of the Study:

  • To evaluate the variability of existing dairy cattle enteric methane emission (EME) prediction equations.
  • To develop a unified EME prediction equation by averaging existing models.
  • To create a more accurate and consistent method for predicting EMEs based on key dietary components.

Main Methods:

  • Gathered and analyzed 32 existing EME prediction equations.
  • Evaluated twelve dietary variable combinations using a mixed-effects model.
  • Selected an equation based on metabolised energy (ME) and neutral detergent fibre (NDF) for its predictive accuracy and significance.

Main Results:

  • Existing equations yielded a wide range of EME predictions (12.49 to 34.27 g CH4/kg DM) for example diets.
  • The developed combined equation (CH4 = 0.33 × ME + 0.31 × NDF + 3.47) demonstrated a low prediction error (RMSE = 1.47 g CH4/kg DM).
  • The chosen equation accounted for significant predictor variables and residual variation.

Conclusions:

  • A combined EME prediction equation using ME and NDF provides a more consistent and reliable estimate.
  • This new equation can serve as a valuable tool for comparing EMEs across different studies and farms.
  • The findings contribute to more accurate EME assessments, supporting efforts to reduce greenhouse gas emissions in dairy farming.