TITLE:
Physical and Chemical Matrix Effects in Soil Carbon Quantification Using Laser-Induced Breakdown Spectroscopy
AUTHORS:
Aline Segnini, Alfredo Augusto Pereira Xavier, Pedro Luís Otaviani-Junior, Edilene Cristina Ferreira, Alex Marcel Watanabe, Marco Aurélio Sperança, Gustavo Nicolodelli, Paulino Ribeiro Villas-Boas, Patrícia Perondi Anchão Oliveira, Débora Marcondes Bastos Pereira Milori
KEYWORDS:
Soil C Content, Spectral Correction, Soil Textural Classes, Field-Based Method, Atomic Emission
JOURNAL NAME:
American Journal of Analytical Chemistry,
Vol.5 No.11,
August
8,
2014
ABSTRACT: Advanced field methods of carbon (C) analysis should now be capable of providing repetitive, sequential measurements for the evaluation of spatial and temporal variation at a scale that was previously unfeasible. Some spectroscopy techniques, such as laser-induced breakdown spectroscopy (LIBS), have portable features that may potentially lead to clean and rapid alternative approaches for this purpose. The goal of this study was to quantify the C content of soils with different textures and with high iron and aluminum concentrations using LIBS. LIBS emission spectra from soil pellets were captured, and the C content was estimated (emission line of C (I) at 193.03 nm) after spectral offset and aluminum spectral interference correction. This technique is highly portable and could be ideal for providing the soil C content in a heterogeneous experiment. Dry combustion was used as a reference method, and for calibration a conventional linear model was evaluated based on soil textural classes. The correlation between reference and LIBS values showed r = 0.86 for medium-textured soils and r = 0.93 for fine-textured soils. The data showed that better correlation and lower error (14%) values were found for the fine-textured LIBS model. The limit of detection (LOD) was found to be 0.32% for medium-textured soils and 0.13% for fine-textured soils. The results indicated that LIBS quantification can be affected by the texture and chemical composition of soil. Signal treatment was shown to be very important for mitigation of these interferences and to improve quantification.