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Updated: Jun 30, 2026

Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions
Published on: January 10, 2019
[Study on the soil mid-infrared photoacoustic spectroscopy]
Chang-wen Du1, Jian-min Zhou, Huo-yan Wang
1The National Key Lab of Soil Agricultural Sustainability, Institute of Soil Science Chinese Academy of Sciences, Nanjing, China. chwdu@issas.ac.cn
Abstract:
Infrared photoacoustic spectroscopy (PAS) is a new style to obtain data based on photoacoustic theory. Photoacoustic thoeory is based on the absorption of electromagnetic radiation by analyte molecules, and the absorbed energy is measured by detecting pressure fluctuations in the form of sound waves or shock pulses. In contrast to conventional absorption spectroscopy, PAS allows the determination of absorption coefficients over several orders of magnitude, even in very black and strongly scattering soil samples. Red soil, fulvic soil and paddy soil were collected from Fengqiu National Ecological Experimental Station, Yingtan Red Soil Experimental Station, and Changshu Ecological Experimental Station, respectively. These soil samples were used as experimental materials to characterize the Fourier transform mid-infrared photoacoustic spectra (FTIR-PAS). Compared with infrared transmittance spectra and reflectance spectra, the testing of FTIR-PAS spectra was very fast and convenient without any pr-treatment, and there were more abundant absorptions as well as appropriate absorption values in the spectra; The main soil components (kaolin, bentonite, sand and CaCO3) also showed several strong absorptions with specific characteristics in the spectra; Further more, the interference of water with the PAS spectra was significantly smaller than that with reflectance spectra. Therefore, the soil properties could be better characterized by FTIR-PAS. The principal components analysis based on the FTIR-PAS spectra indicated that there were two main principal components (PCA1, PCA2) which contained 98.17% variance of the spectra, and the two-dimensionol distribution was made by plotting these two principal components to classify the soil type, and the results indicated that this distribution could be applied to distinguish soil type, which provided new technique for soil identification as well as further quantitative analysis in soil science.
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