Mineral-nutrient relationships in African soils assessed using cluster analysis of X-ray powder diffraction patterns and compositional methods.

ABSTRACT: Soil mineral compositions are often complex and spatially diverse, with each mineral exhibiting characteristic chemical properties that determine the intrinsic total concentration of soil nutrients and their phyto-availability. Defining soil mineral-nutrient relationships is therefore important for understanding the inherent fertility of soils for sustainable nutrient management, and data-driven approaches such as cluster analysis allow for these relations to be assessed in new detail. Here the fuzzy-c-means clustering algorithm was applied to an X-ray powder diffraction (XRPD) dataset of 935 soils from sub-Saharan Africa, with each diffractogram representing a digital signature of a soil's mineralogy. Nine mineralogically distinct clusters were objectively selected from the soil mineralog

SUBMITTER: Butler BM 

PROVIDER: S-EPMC7386901 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature