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A simplified approach for producing Tier 2 enteric-methane emission factors based on East African smallholder farm data

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Title A simplified approach for producing Tier 2 enteric-methane emission factors based on East African smallholder farm data
 
Creator Ndung'u, Phyllis W.
Toit, C.J.L. du
Takahashi, T.
Robertson-Dean, M.
Butterbach-Bahl, Klaus
Merbold, Lutz
Goopy, John P.
 
Subject cattle
mitigation
milk production
greenhouse gas emissions
smallholders
food science
 
Description Context.
Accurate reporting of livestock greenhouse gas (GHG) emissions is important in developing effective mitigation strategies, but the cost and labour requirements associated with on-farm data collection often prevent this effort in low- and middle-income countries.

Aim.
The aim of this study was to investigate the precision and accuracy of simplified activity data collection protocols in African smallholder livestock farms for country-specific enteric-methane emission factors.

Method.
Activity data such as live weight (LW), feed quality, milk yield, and milk composition were collected from 257 smallholder farms, with a total herd of 1035 heads of cattle in Nandi and Bomet counties in western Kenya. The data collection protocol was then altered by substituting the actual LW measurements with algorithm LW (ALG), feed quality (FQ) data being sourced from the Feedipedia database, reducing the need for daily milk yield records to a single seasonal milk measurement (MiY), and by using a default energy content of milk (MiE). Daily methane production (DMP) was calculated using these simplified protocols and the estimates under individual and combined protocols were compared with values derived from the published (PUBL) estimation protocol.

Key results.
Employing the algorithm LW showed good agreement in DMP, with only a small negative bias (7%) and almost no change in variance. Calculating DMP on the basis of Feedipedia FQ, by contrast, resulted in a 27% increase in variation and a 27% positive bias for DMP compared with PUBL. The substitutions of milk (MiY and MiE) showed a modest change in variance and almost no bias in DMP.

Conclusion.
It is feasible to use a simplified data collection protocol by using algorithm LW, the default energy content of milk value, and seasonal single milk yield data, but full sampling and analysis of feed resources are required to produce reliable Tier 2 enteric-methane emission factors.

Implications.
Reducing enteric methane emissions from livestock is a promising pathway to reduce the effects of climate change, and, hence, the need to produce accurate emission estimates as a benchmark to measure the effectiveness of mitigation options. However, it is expensive to produce accurate emission estimates, especially in developing countries; hence, it is important and feasible to simplify on-farm data collection.
 
Date 2022
2022-12-27T08:59:51Z
2022-12-27T08:59:51Z
 
Type Journal Article
 
Identifier Ndung’u, P.W., du Toit, C.J.L., Takahashi, T., Robertson-Dean, M., Butterbach-Bahl, K., Merbold, L. and Goopy, J.P. 2022. A simplified approach for producing Tier 2 enteric-methane emission factors based on East African smallholder farm data. Animal Production Science
1836-5787
https://hdl.handle.net/10568/126321
https://www.publish.csiro.au/an/acc/AN17809/AN17809_AC.pdf
https://doi.org/10.1071/AN22082
https://doi.org/10.17632/j5b9d7dd2b.2
 
Language en
 
Rights CC-BY-NC-ND-4.0
Open Access
 
Publisher CSIRO Publishing
 
Source Animal Production Science