Accuracy of enteric methane emission models for cattle in sub-Saharan Africa: status quo and the way forward

Abstract Cattle emit over 65% of enteric methane (CH4) in sub-Saharan Africa (SSA), making them the focus of many mitigation strategies targeting livestock emissions. Since measured feed intake data are sparse, emission factors for enteric CH4 (EFCH4) are mainly estimated indirectly from gross energy intake (GEI) using the net energy (NE) requirements for different metabolic processes in cattle. However, all NE requirement systems commonly used for cattle in SSA were developed for cattle in temperate regions. Therefore, we assessed the suitability of different enteric CH4 models for estimating the GEI of cattle in SSA. The Intergovernmental Panel on Climate Change (IPCC) and South African models were identified as the main tier 2-based methods used to estimate enteric CH4 emissions from cattle in SSA. In the IPCC model, EFCH4 was estimated as (GEI * [Ym/100])/55.65, where Ym is the conversion factor (%) of gross energy in feed to CH4 and 55.65 the energy content of CH4 (MJ/kg). The GEI was estimated based on NE requirements for different metabolic processes in cattle as per the American National Research Council. In the South African model, EFCH4 was estimated as (Y/100 * GEI/55.22), where Y is the CH4 yield and 55.22 is the energy content of CH4; Y was calculated from the dry matter (DM) digestibility while GEI was calculated by predicting DM intake and multiplying it by 18.4 MJ (gross energy per kilogram DM). Also, the suitability of the British and German NE requirement systems was assessed as alternatives used for cattle nutrition in SSA. These NE systems were implemented in the IPCC model to yield the “AFRC” and “GfE” models, respectively. The four models were then evaluated using an evaluation dataset summarizing feed quality and DM intake results from 21 studies conducted in SSA, with 125 dietary treatments, and 822 cattle observations. The relative prediction error (RPE) and concordance correlation coefficient (CCC) were used to evaluate the models’ accuracy. Only the South African model estimated the GEI in dairy cattle with an acceptable RPE (18.9%) and highest CCC (0.87), while the other three models yielded estimates with RPE > 20%. None of the four models we assessed estimated GEI for other cattle (i.e., nondairy) with an RPE < 20% or CCC > 0.30. The inaccuracy in GEI estimates suggests an error of the same magnitude in EFCH4 estimates. Therefore, a concerted effort is needed to improve the accuracy of enteric CH4 estimation models for cattle in SSA.