Abstract

Soil texture is an independent and innate soil property and other dynamic soil properties such as electrical conductivity (EC), organic carbon (OC) content and cation exchange capacity (CEC) are mostly dependent on it. An attempt was made to develop a model for numerically simulating soil texture and also to construct relationships of the developed model with other soil properties. Hypothetical data of particle size distribution and our data were used to justify and validate the newly defined indices. Scatter diagrams showed good association between the indices and hypothetical data of soil separates. Moreover, similar trends were observed between the line charts of USDA soil textural class codes and the indices. Strong correlations (r = 0.78–0.96) were found between the indices and soil separates (sand, silt and clay) for our data. However, the indices demonstrated moderate correlations (r = –0.34 to –0.55) with EC and OC of the soils. Strong nonlinear relationships were found between CEC and the three indices (R2 = 0.699, R2 = 0.732 and R2 = 0.672 (all P < 0.001). Furthermore, the variability of EC, OC and CEC within a single USDA textural class and customised textural index groups were described using the developed model. The developed indices showed excellent fitness for simulation of soil texture and demonstrated an extended applicability in terms of their relationships with soil properties related to soil texture, which will help in constructing digital soil maps.

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