Mineralogy of Africa’s Soils as a predictor of Soil Fertility

Soil mineralogy is essential to understanding many facets of land use and a key determinant of all soil functional properties that are expensive or time-consuming to measure, and can solve specific agricultural and environmental problems. They provide physical support for plants, contribute to soil structural formation, are sources of many soil nutrients, and can act as sorbents of several environmental pollutants. Soil mineralogy in Africa has not been adequately and appropriately researched upon. Poorly and fragmentally coordinated scientific investigations coupled with the limitations in the traditional analysis techniques are partly responsible for the limited studies so far executed. Land Degradation Surveillance Framework is a methodology designed for understanding ecological variables/metrics and their dynamics at different spatial scales. The aim of this study was to evaluate the ability of X-ray diffraction (XRD) techniques to rapidly predict soil functional properties and to develop pedotransfer functions for Africa’s soils. Geo-referenced samples associated with the Africa Soil Information Service (AfSIS), taken from a set of sentinel sites randomised over sub-Saharan Africa were used for characterisation. A total of 160 topsoil samples taken from 16 randomised points of ten 100-km2 sites: Tanzania (3 sites), Malawi (2 sites), Mali (1 site), Burkina Faso (1 site), Kenya (2 sites) and Ghana (1 site) were characterised for chemical properties, particle sizes distribution, engineering properties and bulk mineralogy. Variation of the mineralogy within and between sites was explored using multivariate analysis, including principal component analysis in R statistical software, as a precursor to exploring relationships with directly measured soil properties and soil fertility diagnostics. The clustering of individual minerals and the distributions of the soil fertility variables identified across the sites appeared to relate to differences in mineralogical functional groups, supporting the understanding of the pedologic environment differences and similarities. The findings therefore present opportunity to improve soil assessment using information on soil mineralogy. For instance XRD information on mineralogy can be combinedwith information from infrared spectroscopy, which characterises soil mineral and physio-chemical properties, to provide powerful diagnostic capabilities, and be used as a complementary input to pedo-transfer functions for low cost and rapid prediction of soil functional properties.