A simplified approach for producing Tier 2 enteric-methane emission factors based on East African smallholder farm data
P. W. Ndung’u
A B * , C. J. L. du Toit A , T. Takahashi C D , M. Robertson-Dean E , K. Butterbach-Bahl F , L. Merbold G and J. P. Goopy A B
A Department of Animal and Wildlife Sciences, University of Pretoria, Pretoria 0002, South Africa.
B Mazingira Centre, International Livestock Research Institute, PO Box 30709-00100, Nairobi, Kenya.
C Rothamsted Research, North Wyke, Okehampton, Devon EX20 2SB, UK.
D University of Bristol, Langford House, Langford, Somerset BS40 5DU, UK.
E School of Mathematics, University of New England, Armidale, NSW, Australia.
F Institute for Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, D-82467 Garmisch-Partenkirchen, Germany.
G Agroscope, Research Division Agroecology and Environment, Reckenholzstrasse 191, 8046 Zurich, Switzerland.
Animal Production Science 63(3) 227-236 https://doi.org/10.1071/AN22082
Submitted: 3 March 2022 Accepted: 28 September 2022 Published: 28 October 2022
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
Abstract
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, default energy content of milk value, seasonal single milk yield data, but full sampling and analysis of feed resources is required to produce reliable Tier 2 enteric-methane emission factors.
Implications: Reducing enteric methane emissions from the 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.
Keywords: activity data, cattle, dry-matter digestibility, GHG inventory, heart girth, milk yield, mitigation, protocol.
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