Table 2: Detailed partial least squares regression model results for soil total carbon ( ) prediction from the subsets of visible/near-infrared diffuse reflectance spectra based on content. The range of values reflects the results of 10 random iterations of the models, and the number in parentheses is the mean. Detailed results are also given for full sample set models with no subsetting for comparison.

CalibrationValidation
RMSE (%)c RMSE (%)RPDdRPIQe

< 10%133–1470.43–0.80 1.08–1.78 56–700.47–0.76 1.27–1.97 1.37–2.03 1.77–2.88
(0.64)(1.46)(0.61)(1.59)(1.63)(2.12)

> 10%68–820.77–0.93 3.86–7.00 22–360.77–0.91 3.96–7.65 2.05–3.21 2.38–5.16
(0.86)(5.33)(0.84)(5.87)(2.55)(4.02)

Full sample set2150.81–0.96 2.88–5.87 920.81–0.95 2.82–7.18 2.27–4.47 2.08–4.35
(0.91)(4.06)(0.91)(4.24)(3.46)(3.19)

aNumber of samples.
bCoefficient of determination.
cRoot mean squared error.
dResidual prediction deviation.
eRatio of performance to interquartile distance.