Soil variability description using Fourier transform mid-infrared photoacoustic spectroscopy coupling with RGB method

• Published in: Catena (Giessen) Vol. 152; pp. 190 - 197
• Main Authors: Ma, Fei, Zeng, Yin, Du, Changwen, Shen, Yazhen, Ma, Hongwei, Xu, Sheng, Zhou, Jianming
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2017
• Subjects: absorbance; amides; carbonates; carboxylic acids; China; clay minerals; Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS); iron oxides; kriging; photoacoustic spectroscopy; principal component analysis; quartz; Red-green-blue multicolor method (RGB); soil heterogeneity; soil management; soil organic matter; soil sampling; soil surveys; Soil variability; spectrometers; China; SOM; Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS); PCs; Soil variability; FTIR-PAS; SOC; MD; Red-green-blue multicolor method (RGB); RGB; PCA
• ISSN: 0341-8162; 1872-6887
• DOI: 10.1016/j.catena.2017.01.005

Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS) has been successfully applied in recent years to predict soil properties due to its advantages as a rapid, non-destructive, and well-rounded characterization method. In this study, we investigated the potential of FTIR-PAS to characterize soil heterogeneity in an agricultural field in Lishui (China). On the basis that each FTIR-PAS spectrum represents a well-rounded soil characteristic from each sample, we aimed to explore a method to convert the spectral lines (multidimensional matrix) into data that can be used in soil mapping while retaining maximum soil information to display soil heterogeneity maps according to kriging interpolations. The Mahalanobis distance (MD) and red-green-blue tricolor (RGB) methods were employed to convert the soil information. A set of diverse soil samples (n=597) was scanned with a FTIR-PAS spectrometer in the mid-infrared range (4000–400cm−1). The peaks showing soil organic matter content (CO from carboxylic acids at 1755cm−1; COO, NH, and CN from carboxylates and amides at 1540cm−1), clay minerals (quartz overtones at 1953cm−1: carbonates, quartz, and iron oxides lower than 800cm−1), and water (O–H: 3700–3000cm−1 and 1700–1600cm−1, respectively). The first three PCs (85.05%) were extracted using principal component analysis (PCA). The results showed that both methods could convert the multidimensional matrix based primarily on absorbance bands associated with characteristic soil attributes. However, comparison of the maps suggested that the RGB method could translate information on spectral heterogeneity with higher accuracy than MD method which lost the direction of soil attributions. Therefore, FTIR-PAS spectra data combined RGB method might provide a supplemental method for use in agricultural modelling and soil management. [Display omitted] •FTIR-PAS was firstly employed to capture the variability of paddy soils.•Spectral information was extracted and expressed by the first three PCs.•Mahalanobis distance and RGB method were used for descripting soil variability.