Volume 5, Number 4
 
Archive
 
+ Volume 5, 2017
Issue 1
Issue 2
Issue 3
Issue 4
+ Volume 4, 2016
+ Volume 3, 2015
+ Volume 2, 2014
+ Volume 1, 2013
Science International Vol. 5 (4), 2017
Review Article
Mathematical Prediction Equations of Methane Emission from Dairy Cattle
Mostafa Sayed Abdellatif Khattab
 
Abstract: Several techniques were developed to estimate quantity of methane emissions, but these techniques are not practical at the farm conditions, so, attention were turned toward possible approaches to formulate a high accurate prediction model. Different studies were illustrated that amount digested feeds in the rumen, concentrate and roughage contents are the most important factors affecting methane production. The digestion feed in rumen and hydrogen produced could be estimated by VFA’s concentration, then it could help us to estimate. The dynamic and mechanistic models can be used to estimate methane emissions from ruminants. Their accuracy in prediction of methane production could be helpful to better estimate the contribution of ruminants to total global emission of methane. They also could be used to evaluate different strategies to reduce methane losses without affecting the metabolic efficiency of the whole rumen system. In conclusion, the developed equations could accurately and rapidly predict the CH4 production. Further in vitro and in vivo studies with a broader range of feedstuffs differing in constituents for each category are necessary to improve the accuracy and representation of the predictive equations before their practical application.
 
      Fulltext   HTML  /  PDF    |  
 
 
SIGN IN
  User ID
 
  Password
 
 
  Forgot Password?   |   Register Now
 
   Quick Links
  About the journal
  Current issue
   Archive
  Editorial board
  Submit manuscript
  Abstracting and indexing
  Article submission
  Guide to authors
  For subscribers
  Publication Ethics
 
 
Science International © 2017                                                                                                                                          Maintained and Developed by ansinet