Mid-infrared attenuated total reflectance spectroscopy for soil carbon and particle size determination

Yufeng Ge, J. Alex Thomasson, Cristine L.S. Morgan

Research output: Contribution to journalArticlepeer-review

46 Scopus citations

Abstract

In soil analysis mid-infrared spectroscopy (MIR) is not as widely used as visible and near infrared spectroscopy (VisNIR), mainly due to (1) the need for sample preparation and (2) strong absorption leading to spectral distortion and total absorption. In this study we used attenuated total reflectance (ATR) as a sample presentation technique to obtain MIR spectra of neat soil samples to overcome the two aforementioned drawbacks. A set of diverse soil samples (N=270) were scanned with a Fourier Transform IR spectrometer (4000 to 400cm-1) on its diamond ATR crystal. The objective was to investigate the usefulness of ATR spectra in determining clay, sand, organic and inorganic C using partial least squares regression. Results showed that inorganic C and clay can be predicted very well with ATR, with validation R2 around 0.94 and Ratio of Performance to Deviation (RPD) around 4.0. Sand can be predicted satisfactorily also, with R2=0.88 and RPD slightly lower than 3.0. Organic C is predicted with R2=0.77 and RPD>2.1. Compared to the results of VisNIR models, significantly higher accuracy was obtained for clay, sand, and inorganic C, and a slight improvement was obtained for organic C. In our opinion, MIR-ATR can be a promising and powerful tool for soil characterization. It combines the advantages of both VisNIR (minimum sample preparation and high analysis throughput) and diffuse reflectance MIR (better model performance). Finally, as evidenced in our "leave-whole-field-out" experiment, the models developed with ATR spectra performed better on dissimilar samples and might have a larger scope of application than VisNIR.

Original languageEnglish (US)
Pages (from-to)57-63
Number of pages7
JournalGeoderma
Volume213
DOIs
StatePublished - Jan 2014
Externally publishedYes

Keywords

  • Clay
  • Evanescent field
  • Partial least squares regression
  • Soil carbon

ASJC Scopus subject areas

  • Soil Science

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