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

Autor: Butler BM; The James Hutton Institute, Craigiebuckler, Aberdeen AB15 8QH, UK., Palarea-Albaladejo J; Biomathematics & Statistics Scotland, JCMB, The King's Buildings, Edinburgh EH9 3FD, UK., Shepherd KD; World Agroforestry Centre (ICRAF), P.O. Box 30677-00100 GPO, Nairobi, Kenya., Nyambura KM; International Fertiliser Development Centre, c/o icipe Campus, P.O. Box 30772-00100, Nairobi, Kenya., Towett EK; World Agroforestry Centre (ICRAF), P.O. Box 30677-00100 GPO, Nairobi, Kenya., Sila AM; World Agroforestry Centre (ICRAF), P.O. Box 30677-00100 GPO, Nairobi, Kenya., Hillier S; The James Hutton Institute, Craigiebuckler, Aberdeen AB15 8QH, UK.; Department of Soil and Environment, Swedish University of Agricultural Sciences (SLU), SE-75007 Uppsala, Sweden.
Jazyk: angličtina
Zdroj: Geoderma [Geoderma] 2020 Oct 01; Vol. 375, pp. 114474.
DOI: 10.1016/j.geoderma.2020.114474
Abstrakt: 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 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, K-feldspar, plagioclase, Fe/Al/Ti-(hydr)oxides, phyllosilicates (1:1 and 2:1), ferromagnesians, and calcite. 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) in combination with log-ratio compositional data analysis. Fe/Al/Ti/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 of nutrients within their chemical composition and their low cation exchange capacity. Results highlight how the mineral composition controls the total nutrient reserves and their phyto-availability in soils of sub-Saharan Africa. The typical characterisation of soils and their parent material based on the clay particle size fraction (i.e. texture) and/or the overall silica component (i.e. acid and basic rock types) alone may therefore mask the intricacies of mineral contributions to soil nutrient concentrations.
Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(© 2020 The Authors.)
Databáze: MEDLINE
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