Are these variables appropriate?
Forage species composition and biomass using remote sensing techniques.
Chemical composition (including lipids and tannins) of forages and supplements, forage: concentrate ratio, additives
Animal characteristics, including species, number, age, starting weight, weight gain, daily feed int
Excreted total nitrogen (NH4+, urine N, faecal N) and excreted volatile solids
Rumen pH and rumen microbes (quantity)
Environmental conditions, particularly, temperature and relative humidity
Methane and nitrous oxide fluxes from herds of ruminants using infra-red gas analysers
Climate change, water and food security / by
Hugh Turral
FAO consultant
Jacob Burke and Jean-Marc Faurès
FAO Land and Water Division, 2011
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Good Practice Guidance for Land Use, Land-Use Change and Forestry, 2003
Edited by
Jim Penman, Michael Gytarsky, Taka Hiraishi, Thelma Krug, Dina Kruger,
Riitta Pipatti, Leandro Buendia, Kyoko Miwa, Todd Ngara,
Kiyoto Tanabe and Fabian Wagner
Hi J.K.,
Types of input variables depend on the level of modeling you are planning to undertake. Is it ‘animal level’, ‘farm level’ or ‘regional level’ modeling you are aiming for?
Another important factor is what model do you plan to use (trying to adapt an existing model or to develop a new one)?
In general, you have listed some of the most important variables required for modeling greenhouse gas emissions from ruminants, but the level of details (input variables) required may depend on the factors I mentioned above.
-Susantha
Thanks for your valuable responses. In fact, I'm planning develop a farm level model.
Hello,
Refer to Ramin and Huhtanen (2013-J Dairy Sci), and Appuhamy et al. (2016-Global Change Biology) as the most related articles. Certainly, you can choze the potential regressors for your study.
Good luck!
Mina
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