Your search found 1 records
1 Berazneva, J.; McBride, L.; Sheahan, M.; Guerena, D. 2018. Empirical assessment of subjective and objective soil fertility metrics in East Africa: implications for researchers and policy makers. World Development, 105:367-382. [doi: https://doi.org/10.1016/j.worlddev.2017.12.009]
Soil fertility ; Agricultural productivity ; Soil analysis ; Soil pH ; Soil types ; Soil quality ; Cation exchange capacity ; Natural resources management ; Researchers ; Policy making ; Farmers attitudes ; Crop yield ; Maize / East Africa / Kenya / Tanzania
(Location: IWMI HQ Call no: e-copy only Record No: H048769)
(1.09 MB)
Bringing together emerging lessons from biophysical and social sciences as well as newly available data, we take stock of what can be learned about the relationship among subjective (reported) and objective (measured) soil fertility and farmer input use in east Africa. We identify the correlates of Kenyan and Tanzanian maize farmers’ reported perceptions of soil fertility and assess the extent to which these subjective assessments reflect measured soil chemistry. Our results offer evidence that farmers base their perceptions of soil quality and soil type on crop yields. We also find that, in Kenya, farmers’ reported soil type is a reasonable predictor of several objective soil fertility indicators while farmer-reported soil quality is not. In addition, in exploring the extent to which publicly available soil data are adequate to capture local soil chemistry realities, we find that the time-consuming exercise of collecting detailed objective measures of soil content is justified when biophysical analysis is warranted, because farmers’ perceptions are not sufficiently strong proxies of these measures to be a reliable substitute and because currently available high-resolution geo-spatial data do not sufficiently capture local variation. In the estimation of agricultural production or profit functions, where the focus is on averages and in areas with low variability in soil properties, the addition of soil information does not considerably change the estimation results. However, having objective (measured) plot-level soil information improves the overall fit of the model and the estimation of marginal physical products of inputs. Our findings are of interest to researchers who design, field, or use data from agricultural surveys, as well as policy makers who design and implement agricultural interventions and policies.
Powered by DB/Text WebPublisher, from
