Carbon quantification in soils with different textures using laser-induced breakdown spectroscopy: spectral interference correctionand use of a 3D plane model

Author(s)

Stenio, Kleydson ; Pereira Xavier, Alfredo Augusto ; De Morais, Carla Pereira ; Pereira Milori, Debora Marcondes Bastos

• Document type: Journal article
• Source: ANALYTICAL METHODS; v. 14, n. 42, p. 11-pg., 2022-09-19.

Abstract

Soil carbon (C) determinations have been widely studied due to soil C sequestration that contributes to the mitigation of greenhouse gas emissions and improves soil quality. However, traditional chemical processes for large-scale analysis generate waste, are time-consuming, and have a high cost per measurement. Laser-induced breakdown spectroscopy (LIBS) is a multi-element spectroanalytical technique that allows fast and low-cost analysis, almost no sample preparation is required, and does not generate hazardous chemical waste. Two emission lines are commonly used for LIBS C determination, 193.03 and 247.85 nm. However, Brazilian soils have a high concentration of aluminum (Al) and iron (Fe), directly interfering in those C emission lines. Furthermore, multiple soil textures increase the difficulty of building calibration models due to matrix effects. In the present work, a mathematical model is proposed to quantify the total C in soil samples having different textures bypassing spectral interferences. A LIBS-specific method for removing outliers has been developed with 6% spectrum removal. From the univariate analysis, it was noticed that some results were projections of a 3D surface in a 2D space, so a 3D plane model was obtained with good fits for the evaluated C emission lines, R-2 > 0.91, with limits of detection of 0.11% and 0.13% and limits of quantitation of 0.11% and 0.32% for lines 193.03 and 247.85 nm, respectively. Three repetitions were used to test the robustness of the methods and presented an R-2 of 0.95 and 0.93, a mean error of about 20.38% and 24.12% for lines 193.03 and 247.85 nm, respectively, and a root mean square error of prediction lower than 0.40% for both lines. (AU)

• FAPESP's process: 13/07276-1 - CEPOF - Optics and Photonic Research Center
• Grantee: Vanderlei Salvador Bagnato
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC