1st International Congress on Environmental Modelling and Software - Lugano, Switzerland - June 2002
Keywords
methane, cow, computer model, molly
Start Date
1-7-2002 12:00 AM
Abstract
Because New Zealand is a signatory to the Kyoto Protocol Framework Convention on ClimateChange (1997), it is required to report national greenhouse gas emissions and maintain them at 1990 levelsby 2008-2012. New Zealand has one of the highest per capita levels of the greenhouse gas methane[Woodward et al., 2001] and most of this arises from gut fermentation from ruminants. Not only does thisruminant-produced methane contribute to greenhouse gas emissions, but it is also wasteful in terms ofenergy loss for the animal. This paper investigates the ability of four methane models within MOLLY[Baldwin, 1995] to model the methane production from a trial conducted at Dexcel, a dairy researchcompany based in Hamilton, New Zealand. In this trial, sixteen Friesian and Jersey dairy cows grazed oneither perennial ryegrass (Lolium perenne) or sulla - a condensed tannin containing forage legume(Hedysarum coronarium). MOLLY was run over 3 days, the period of methane production data collection,and each of the eight ryegrass-fed cows were modelled. (The sulla-fed cows were not modelled due to lackof information on the composition of sulla). MOLLY is one of the cow component models used in theWhole Farm Model (WFM) [Sherlock et al., 1997; Bright et al., 2000] which has been developed at Dexcel.The WFM simulates a pasture-based, rotationally grazed dairy farm and consists of a framework to whichare attached four different components – climate, management, pasture and cow. Three of the methanemodels were empirical – based on regression equations, the remaining model being a mechanistic one. Oneof the empirical models and the mechanistic model were found to be the best predictors of methaneproduction for the ryegrass-fed cows. The process of modelling methane production at the whole farm levelwill highlight areas where knowledge of methanogenesis is lacking, and direct research to the mostpromising feeding strategies to reduce methane emissions.
Using Models to Predict Methane Reduction in Pasture- Fed Dairy Cows
Because New Zealand is a signatory to the Kyoto Protocol Framework Convention on ClimateChange (1997), it is required to report national greenhouse gas emissions and maintain them at 1990 levelsby 2008-2012. New Zealand has one of the highest per capita levels of the greenhouse gas methane[Woodward et al., 2001] and most of this arises from gut fermentation from ruminants. Not only does thisruminant-produced methane contribute to greenhouse gas emissions, but it is also wasteful in terms ofenergy loss for the animal. This paper investigates the ability of four methane models within MOLLY[Baldwin, 1995] to model the methane production from a trial conducted at Dexcel, a dairy researchcompany based in Hamilton, New Zealand. In this trial, sixteen Friesian and Jersey dairy cows grazed oneither perennial ryegrass (Lolium perenne) or sulla - a condensed tannin containing forage legume(Hedysarum coronarium). MOLLY was run over 3 days, the period of methane production data collection,and each of the eight ryegrass-fed cows were modelled. (The sulla-fed cows were not modelled due to lackof information on the composition of sulla). MOLLY is one of the cow component models used in theWhole Farm Model (WFM) [Sherlock et al., 1997; Bright et al., 2000] which has been developed at Dexcel.The WFM simulates a pasture-based, rotationally grazed dairy farm and consists of a framework to whichare attached four different components – climate, management, pasture and cow. Three of the methanemodels were empirical – based on regression equations, the remaining model being a mechanistic one. Oneof the empirical models and the mechanistic model were found to be the best predictors of methaneproduction for the ryegrass-fed cows. The process of modelling methane production at the whole farm levelwill highlight areas where knowledge of methanogenesis is lacking, and direct research to the mostpromising feeding strategies to reduce methane emissions.
