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

2D imaging spectroscopy and 3D X-ray CT high spatial resolution analysis ─ method combination for investigating potential interplay of SOM and soil structure development in intact soil samples

Ms Evelin Pihlap1,2, Mr Maik Lucas3, Dr Markus Steffens4, Professor Doris  Vetterlein3,5, Professor Ingrid Kögel-Knabner1,6

1Chair of Soil Science, Technical University of Munich, Freising, Germany, 2Department of Geography, Institute of Ecology and Earth Sciences, University of Tartu, Tartu, Estonia, 3Soil System Science, Helmholtz Centre for Environmental Research UFZ, Halle/Saale, Germany, 4Department of Soil Sciences, Research Institute of Organic Agriculture (FiBL), Frick, Switzerland, 5Soil Science, Martin-Luther-University Halle-Wittenberg, Halle, Germany, 6Institute for Advanced Study, Technical University of Munich, Garching, Germany

Visible-near infrared (vis-NIR) spectroscopy is an acknowledged technique to simultaneously observe several soil parameters, such as soil organic matter, nutrient content, moisture, texture, and mineralogy. Imaging spectroscopy holds the potential to collect this information from intact soil samples with a high spatial resolution of 53×53 µm²/pixel. In this study, we mapped physico-chemical soil properties using a hyperspectral vis-NIR camera (spectral resolution 196 bands between 400-1000 nm and spatial resolution of 53×53 µm²/pixel) and combined them with information on soil structure as obtained using X-ray CT (spatial resolution of 19×19×19 µm³/voxel). We used undisturbed soil cylinders (diameter and height 3 cm) from agriculturally reclaimed soils in the open-cast mining area of Garzweiler near Cologne, Germany. First, we scanned the samples with a X-ray CT, and second embedded several slices from the cylinder in resin (polyester) and scanned them with a hyperspectral camera. For the first time image registration of 2D vis-NIR and 3D X-ray CT images was performed in elastix. This allowed us to correlate physico-chemical information on organic and mineral soil materials with structural data. We identified the impact of reclamation management and plant root on soil organic matter accumulation, and their interplay with biopores and soil structural development.


Biography:

I obtained BSc and MSc degree in Environmental Technology at the University of Tartu (Estonia). During master studies I spent one year at the Kiel University (Germany) as a Kiel City Scholarship holder, which gave me a possibility to expand my knowledge in soil science. During the studies in Kiel my interest in soil science increased and this encouraged me to continue my studies. Currently I am a PhD candicate at the Chair of Soil Science in Technical University of Munich (Germany). In the PhD project I focus on soil structural development after the reclamation of open-cast lignite mining area in West Germany.

SOIL ORGANIC MATTER

7th International Symposium
Soil Organic Matter

6 – 11 October 2019

Hilton Adelaide

Adelaide, South Australia

Australia

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