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Investigation of soil properties using different techniques of mid‐infrared spectroscopy
Author(s) -
Ma F.,
Du C. W.,
Zhou J. M.,
Shen Y. Z.
Publication year - 2019
Publication title -
european journal of soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.244
H-Index - 111
eISSN - 1365-2389
pISSN - 1351-0754
DOI - 10.1111/ejss.12741
Subject(s) - attenuated total reflection , spectroscopy , diffuse reflectance infrared fourier transform , partial least squares regression , photoacoustic spectroscopy , infrared spectroscopy , analytical chemistry (journal) , infrared , chemistry , fourier transform infrared spectroscopy , materials science , optics , environmental chemistry , mathematics , physics , biochemistry , statistics , organic chemistry , quantum mechanics , photocatalysis , catalysis
Summary Diffuse reflectance spectroscopy (DRF), attenuated total reflectance spectroscopy (ATR) and Fourier transform infrared photoacoustic spectroscopy (PAS) are useful techniques that are commonly used to characterize soil properties. Here, these techniques were used to evaluate individual properties of 1456 paddy soil samples from Nanjing, China, to explore their features in the mid‐infrared range. The diffuse reflectance spectroscopy showed broad and shouldered peaks that ranged from 4000 to 500 cm −1 . Attenuated total reflectance spectroscopy produced main peaks around 1000 cm −1 . Fourier transform infrared photoacoustic spectroscopy spectra showed several moderate intensity peaks in the regions of 4000–2600 and 2500–500 cm −1 . The effective variables (wavenumbers) were selected using an uninformative variable elimination (UVE) algorithm to predict soil pH, and soil organic matter (SOM), total nitrogen (TN) and available phosphorus (AP) contents; it used a self‐adaptive partial least squares model (SAM–PLS). The results showed that selected wavenumbers improved the accuracy of prediction for pH, and SOM, TN and AP contents. For the prediction of pH, ATR spectra showed marginally better performance than the other spectra. The DRF spectroscopy was the optimal method for SOM and TN prediction. Available phosphorus contents were predicted poorly by all three spectra. Furthermore, mid‐infrared incident light paths, absorption modes, sensing styles, as well as peak interference and the prediction model, were the main factors that affected the assessment of soil properties in the three types of spectroscopy. Highlights Soil spectra data were measured with DRF, ATR and PAS spectrometers over the range 4000–500 cm −1 . A UVE algorithm was used to select effective wavenumbers from the full spectrum. The pH, SOM, TN and AP were estimated using three techniques based on a SAM–PLS model. Mid‐infrared incident light paths and absorption modes affected prediction performance of the three techniques.