A novel method to characterize soil organic carbon pools using thermal oxidation combined with multivariate analysis

Dr Manoharan Veeragathipillai1, Dr Les Janik2, Dr Jeff Baldock3, Mr Bruce Hinton4

1Office Of Environment And Heritage, Yanco, Australia, 2CSIRO Land and Water, Urrbrae, Australia, 3CSIRO Agriculture and Food, Urrbrae, Australia, 4Leco Australia, Castle Hill, Australia

Soil organic carbon (SOC) pools range from rapidly decomposable particulate organic carbon (POC), slowly decomposable humic fraction (HUM) and resistant organic carbon (ROC). The ROC pool contributes strongly to the long-term sequestration of SOC. Several analytical methods have been proposed, to measure carbon pools including ¹³C-NMR (expensive) and mid infrared (MIR) spectroscopy (soil composition dependent). This study examines whether thermal oxidation of soil samples at temperature intervals between 110°C and 1000°C, and subsequent evolved gas (%CO₂) measurement combined with chemometric analysis, is capable of quantifying SOC pools in different soil types. For this purpose, thermal oxidation profiles of 179 samples collected across Australia were recorded using a Leco® RC-612 and compared with reference SOC pool data obtained by fractionation followed by the ¹³C-NMR method. The mid infrared (MIR) analysis confirmed a well distributed and wide range of soil composition. Sample set was randomly divided into calibration (120) and validation (59) data set to build a partial least square regression (PLSR) model. PLSR analysis indicated that it was not possible to assign a single temperature range to a specific SOC pool. The thermal oxidation patterns revealed that preferential oxidation of POC not only released at lower temperature but continued to release at higher temperatures, possibly due the conversion to more resistant carbon form during the thermal oxidation process. The PLSR calibration model validation using 59 independent samples showed that TOC POC, HUM and ROC fractions were predicted accurately with the R²= 0.99, 0.85, 0.96, 0.90 and Root Mean Square Error of Prediction (RMSEP) of 0.15, 0.18, 0.15, and 0.10 respectively. It is concluded that combined thermal and multivariate analysis provides a robust, rapid and accurate prediction of  soil carbon pools in typical soil types and can be adopted easily for routine carbon pool analysis.


Biography:

Mano is  a Senior Scientist at the office of Environment and Heritage. He has over 20 years of experience in Environmental Soil science and Soil Analytical Chemistry and worked at number of universities and research institutions in Australia and overseas

SOIL ORGANIC MATTER

7th International Symposium
Soil Organic Matter

6 – 11 October 2019

Hilton Adelaide

Adelaide, South Australia

Australia

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