Rapid Determination of Soil Organic Carbon and Permanganate Oxidizable Carbon: Comparison of Individual and Data Fusion Performance Using Fourier Transform Mid-Infrared Photoacoustic Spectroscopy (FTIR-PAS) and Laser-Induced Breakdown Spectroscopy (LIBS)

Abstract

Rapid and accurate prediction of soil organic carbon (SOC) and the carbon fractions that are sensitive to management are vital for evaluating soil fertility and SOC turnover from both long-term and short-term perspectives. This study used 396 soil samples to investigate the individual and combined use of FTIR-PAS and LIBS for both SOC and permanganate oxidizable carbon (POXC) prediction coupled with partial least squares regression (PLSR). The results showed that LIBS from 205 to 899 nm (LIBS-H) was suitable for predicting SOC and POXC, with a coefficient of determination in prediction ( R P 2 ) of 0.68 and 0.73, and a root mean square error in prediction (RMSEP) of 0.57% and 169 mg kg−1, respectively. FTIR-PAS also exhibited good potential for the prediction of SOC and POXC with a slightly poorer performance ( R P 2 of 0.66 and RMSEP of 0.59% for SOC; R P 2 of 0.72 and RMSEP of 171 mg kg−1 for POXC). The prediction ability of SOC was improved by low-level data fusion based on direct concatenation of FTIR-PAS spectra and LIBS spectra at the range of 184–205 nm (LIBS-L), resulting in an R P 2 of 0.72 and an RMSEP of 0.53%. In general, there is good potential for combining FTIR-PAS and LIBS-L to improve the SOC prediction. Both FTIR-PAS and LIBS-H can be applied for individual prediction of SOC and POXC. In addition, FTIR-PAS offers the advantages of reduced complexity in the modeling and easier sample preparation.