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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Vasát, Radim Kodesová, Radka Boruvka, Lubos Jaksík, Ondrej Klement, Ales Drábek, Ondrej |
| Description | Country affiliation: Czech Republic Author Affiliation: Vasát R ( Czech University of Life Sciences Prague, Faculty of Agrobiology, Food and Natural Resources, Department of Soil Science and Soil Protection, Kamýcká 129, 165 21 Prague 6-Suchdol, Czech Republic.) |
| Abstract | From a wide range of techniques appropriate to relate spectra measurements with soil properties, partial least squares (PLS) regression and support vector machines (SVM) are most commonly used. This is due to their predictive power and the availability of software tools. Both represent exclusively statistically based approaches and, as such, benefit from multiple responses of soil material in the spectrum. However, physical-based approaches that focus only on a single spectral feature, such as simple linear regression using selected continuum-removed spectra values as a predictor variable, often provide accurate estimates. Furthermore, if this approach extends to multiple cases by taking into account three basic absorption feature parameters (area, width, and depth) of all occurring features as predictors and subjecting them to best subset selection, one can achieve even higher prediction accuracy compared with PLS regression. Here, we attempt to further extend this approach by adding two additional absorption feature parameters (left and right side area), as they can be important diagnostic markers, too. As a result, we achieved higher prediction accuracy compared with PLS regression and SVM for exchangeable soil pH, slightly higher or comparable for dithionite-citrate and ammonium oxalate extractable Fe and Mn forms, but slightly worse for oxidizable carbon content. Therefore, we suggest incorporating the multiple linear regression approach based on absorption feature parameters into existing working practices. |
| File Format | HTM / HTML |
| ISSN | 00037028 |
| Issue Number | 12 |
| Volume Number | 69 |
| e-ISSN | 19433530 |
| Journal | Applied Spectroscopy |
| Language | English |
| Publisher | Sage Publication |
| Publisher Date | 2015-12-01 |
| Publisher Place | United States |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Discipline Imaging Discipline Analytical Chemistry Discipline Radiology Soil Chemistry Spectroscopy, Near-infrared Methods Absorption, Physicochemical Calibration Least-squares Analysis Linear Models Support Vector Machines Journal Article Research Support, Non-u.s. Gov't |
| Content Type | Text |
| Resource Type | Article |
| Subject | Spectroscopy Instrumentation |
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