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DIVISION S-5-PEDOLOGY

Quantifying Soil Morphology in Tropical Environments

Methods and Application in Soil Classification

Institute for Land and Water Management, Katholieke Universiteit Leuven, Vital Decosterstraat 102, 3000 Leuven, Belgium

anne.gobin{at}agr.kuleuven.ac.be

We tested the hypothesis that readily observed and easily measured morphological variables can be used to characterize the soils sampled and described in southeastern Nigeria for purposes of land use and management. Field tests were developed for estimating soil texture and amount of ironstone nodules. Two new soil color indices provided an immediate means of diagnosing the soil drainage regime in case of the color index (CI) and soil forming processes in tropical soils in case of the redness index (RI). The indices correlated negatively with organic C content and positively with dithionite-extracted Fe₂O₃ (0.44) and Al₂O₃ (0.51). Inexpensive field tests for color, texture, and ironstone can be quantified using color indices and laboratory measurements. The local soil classification was quantified by means of color indices (RI, CI) and percentages of ironstone, sand, silt, and clay measured in the A horizon. A classification based on soil texture, ironstone, and color was used to define classes for the B horizon. The two first principal components (PC) extracted from soil morphological variables measured on the upper three horizons of 72 pedons explained 64.7% of the total variance. Nonhierarchical clustering performed on the two PCs produced seven clusters that compare well with the great groups of U.S. soil taxonomy. Principal component analysis on 20 soil chemical and morphological variables confirmed that soil texture, ironstone, and soil color account for most of the variation of the soils and provide an efficient means of characterizing tropical soils derived from sedimentary parent material.

Abbreviations: BS, base saturation • CEC, cation-exchange capacity • CI, color index • CV, coefficient of variation • EA, exchangeable acidity • PC, principal component • RI, redness index • RR, redness rating • SD, standard deviation

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