Soil mineral compositions are often complex and spatially diverse, with each min- eral 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 diffrac- togram representing a digital signature of a soil's mineralogy. Nine mineralogically distinct clusters were objectively selected from the soil mineralogy continuum by retaining samples exceeding the 75 % quantile of the membership coefficients in each cluster, yielding a dataset of 239 soils. As such, samples within each cluster represented mineralogically similar soils from different agro-ecological environments of sub-Saharan Africa. Mineral quantification based on the mean diffractogram of each cluster illustrated substantial mineralogical diversity between the nine groups with respect to quartz, feldspars, Fe/Ti/Al-(hydr)oxides and phyllosilicates. Mineral-nutrient relationships were defined using the clustered XRPD patterns and corresponding measurements of total and/or extractable (Mehlich-3) nutrient concentrations (B, Mg, K, Ca, Mn, Fe, Ni, Cu and Zn). The compositional data analysis methods used for defining these relationships respected the relative nature and the inherent interplay between nutrient concentration quantities as fraction of the sample material. Fe/Ti/Al/Mn-(hydr)oxides and feldspars were found to be the primary control of total nutrient concentrations, whereas 2:1 phyllosilicates were the main source of all extractable nutrients except for Fe and Zn. Kaolin minerals were the most abundant phyllosilicate group within the dataset but did not represent a nutrient source, which reflects the lack on nutrients within their chemical composition and their low cation exchange capacity. Results highlight how it is the precise mineralogy of a soil that controls the total nutrient reserves and their phyto-availability. The typical classification of soils and their parent material based on clay size fractions (i.e. texture) and/or silica components (i.e. acid and basic rock types) alone may therefore mask the intricacies of mineral contributions to soil nutrients.