Accuracy of Estimating Soil Properties with Mid-Infrared Spectroscopy: Implications of Different Chemometric Approaches and Software Packages Related to Calibration Sample Size
Different algorithms exist in various software programs for the estimation of soil properties using mid-infrared (MIR) spectroscopy, with recommendations varying between different studies regarding which algorithm should be used. Objectives were to compare the performance of the commercial OPUS Quant 2 software, which uses partial least squares regression (PLSR) and a selection of spectral ranges, with the R software and to study the accuracy of different algorithms as a function of the information provided in the calibration. Contents of soil organic carbon (SOC), nitrogen, and texture for surface soils of an arable field were determined, and MIR were spectra recorded. Partial least squares regression used with either software was useful (ratio of performance to interquartile distance in the validation sample [RPIQ(V)] >1.89) for an estimation of SOC, clay, and N contents but not for sand and silt. The wavenumber region selection concept used in OPUS was also implemented in R, and it proved useful for SOC (all algorithms) and total nitrogen (artificial neural networks, support vector machine regression (SVMRJ) in the validation. Support vector machine regression generally slightly outperformed the other approaches and resulted in a successful estimation of sand content. The usefulness of SVMR over PLSR generally decreased with decreasing sample size used for the calibration (thus decreasing the information provided), and PLSR partly outperformed SVMR in the validation. Overall, this study indicates that there is no general superiority of a chemometric algorithm over PLSR independent of the information provided in the calibration sample.
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The James Hutton Institute, Craigiebuckler, Aberdeen,AB15 8QH, United KingdomThe James Hutton Institute, Craigiebuckler, Aberdeen,AB15 8QH, United Kingdom
Haghi, R.K.
Pérez-Fernández, E.
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BÜCHI Labortechnik AG, Flawil, SwitzerlandThe James Hutton Institute, Craigiebuckler, Aberdeen,AB15 8QH, United Kingdom
Pérez-Fernández, E.
Robertson, A.H.J.
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The James Hutton Institute, Craigiebuckler, Aberdeen,AB15 8QH, United KingdomThe James Hutton Institute, Craigiebuckler, Aberdeen,AB15 8QH, United Kingdom
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USDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USA
Univ Texas El Paso, Dept Chem, El Paso, TX 79968 USAUSDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USA
Padilla, Julio E.
Calderon, Francisco J.
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USDA ARS, Cent Great Plains Res Stn, Akron, CO 80720 USAUSDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USA
Calderon, Francisco J.
Acosta-Martinez, Veronica
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USDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USAUSDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USA
Acosta-Martinez, Veronica
Van Pelt, Scott
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USDA ARS, Wind Eros & Water Conservat Res Unit, Big Spring, TX USAUSDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USA
Van Pelt, Scott
Gardner, Terrence
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USDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USA
N Carolina State Univ, Dept Soil Sci, Raleigh, NC 27695 USAUSDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USA
Gardner, Terrence
Baddock, Matthew
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USDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USA
Griffith Univ, Griffith Sch Environm, Atmospher Environm Res Ctr, Brisbane, Qld 4111, AustraliaUSDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USA
Baddock, Matthew
Zobeck, Ted M.
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USDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USAUSDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USA
Zobeck, Ted M.
Noveron, Juan C.
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Univ Texas El Paso, Dept Chem, El Paso, TX 79968 USAUSDA ARS, Wind Eros & Water Conservat Res Unit, Lubbock, TX USA