Variability of Northwest Florida Soils by Principal Component Analysis
- M. E. Collins and
- F. A. Ovalles
Twenty soil properties from 151 pedons were evaluated (i) to select the statistically-important ones influencing soil variability and (ii) to test if these were actually differentiating properties. Approximately 83% of the pedons studied were Ultisols. Three sets of data were used for the statistical analysis of soil properties (i) weighted-averages in individual pedons, (ii) data from the first A (A, Ap or Al) horizon, and (iii) data from Albany, Dothan, and Orangeburg soil series. The latter data were tested by a nested analysis of variance to find out if the properties selected were actually differentiating properties. Principal component analysis (PCA) was used as an unbiased method to make the selection. The first five principal components (PCs) explained more than 73% of the total variance. Analyses of eigenvectors, collinearity, and correlation coefficients between soil properties and PCs were also employed. Total sand, fine sand, clay, and organic carbon contents were selected by the PCA as the important properties. These properties except fine sand were validated by a nested analysis of variance. The analysis of variance indicated these properties had a large variation among soil series and/or among horizons within the same soil series.
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