Visible, near-infrared, and mid-infrared spectroscopy applications for soil assessment with emphasis on soil organic matter content and quality: state-of-the-art and key issues
Language English Country United States Media print
Document type Journal Article, Research Support, Non-U.S. Gov't, Review
PubMed
24359647
DOI
10.1366/13-07288
Knihovny.cz E-resources
- MeSH
- Spectroscopy, Near-Infrared methods standards MeSH
- Calibration MeSH
- Least-Squares Analysis MeSH
- Soil chemistry MeSH
- Spectrophotometry, Infrared methods standards MeSH
- Support Vector Machine MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
- Names of Substances
- Soil MeSH
Visible near-infrared (Vis-NIR) reflection spectroscopy and mid-infrared (mid-IR) reflection spectroscopy are cost- and time-effective and environmentally friendly techniques that could be alternatives to conventional soil analysis methods. Successful determination of spectrally active soil components, including soil organic matter (SOM), depends on the selection of suitable pretreatment and multivariate calibration techniques. The objective of the present review is to critically examine the suitability of Vis-NIR (350-2500 nm) and mid-IR (4000-400 cm(-1)) spectroscopy as a tool for SOM quantity and quality determination. Particular attention is paid to different pretreatment and calibration procedures and methods, and their ability to predict SOM content from Vis-NIR and mid-IR data is discussed. We then review the most recent research using spectroscopy in different calibration scales (local, regional, or global). Finally, accuracy and robustness, as well as uncertainty in Vis-NIR and mid-IR spectroscopy, are considered. We conclude that spectroscopy, especially the mid-IR technique in association with Savitzky-Golay smoothing and derivatization and the least squares support vector machine (LS-SVM) algorithm, can be useful in determining SOM quantity and quality. Future research conducted for the standardization of protocols and soil conditions will allow more accurate and reliable results on a global and international scale.
References provided by Crossref.org
vis-NIR and XRF Data Fusion and Feature Selection to Estimate Potentially Toxic Elements in Soil