Quantitative pedology to evaluate a soil profile collection from the Brazilian semi-arid region
This work applies pedometric tools to analyse soil property information relevant to morphological characterisation and soil classification. The objective of this paper was further to identify similarities in soil properties among a soil profile collection. The harmonisation of soil data enables the...
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Published in | South African journal of plant and soil Vol. 35; no. 4; pp. 269 - 279 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Taylor & Francis
08.08.2018
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Subjects | |
Online Access | Get full text |
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Summary: | This work applies pedometric tools to analyse soil property information relevant to morphological characterisation and soil classification. The objective of this paper was further to identify similarities in soil properties among a soil profile collection. The harmonisation of soil data enables the comparison between soil profiles, transference of information and modelling of soil horizons distribution. The statistical procedures were implemented in R software, through the Algorithms for Quantitative Pedology (AQP package), which contains a collection of algorithms to model soil resources and aid soil classification, soil profile aggregation and visualisation. The procedures allowed definition of values for soil properties in every one-centimetre layer of the soil profile, by regrouping the data in a different layer thickness, and it was possible to analyse similarity between profiles using a dissimilarity matrix for each depth slice. The AQP allowed analysis of a large number of soil profiles, in terms of vertical variability of soil continuous properties (e.g. sand and clay content, and pH) and for categorical variables, such as diagnostic horizons. Soil depth functions were developed to represent soil properties and probability of occurrence to diagnostic horizons to a large data set, and the dissimilarity analysis allowed separation of a small group of similar soil profiles and further qualitative comparison among the select profiles. |
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ISSN: | 0257-1862 2167-034X |
DOI: | 10.1080/02571862.2017.1419385 |