EGU2020-13092
https://doi.org/10.5194/egusphere-egu2020-13092
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Prediction of soil organic and inorganic carbon concentrations in Tunisian samples by mid-infrared reflectance spectroscopy using a French national library

Tiphaine Chevallier1, Cécile Gomez2,3, Patricia Moulin4, Imane Bouferra1, Kaouther Hmaidi5, Dominique Arrouays6, Claudy Jolivet6, and Bernard Barthès1
Tiphaine Chevallier et al.
  • 1Eco&Sols, University of Montpellier, CIRAD, INRA, IRD, Montpellier SupAgro, 34060 Montpellier, France (tiphaine.chevallier@ird.fr)
  • 2LISAH, University of Montpellier, INRA, IRD, Montpellier SupAgro, 34060 Montpellier, France (cecile.gomez@ird.fr)
  • 3ndo-French Cell for Water Sciences, IRD, Indian Institute of Science, Bangalore 560012, India
  • 4US IMAGO, IRD, BP1386, Dakar, Senegal
  • 5UR Pédologie, Faculté des Sciences de Tunis, El Manar Tunis, Tunisia
  • 6INRA, US 1106 InfoSol, F45000, Orléans, France

Mid-Infrared Reflectance Spectroscopy (MIRS, 4000–400 cm-1) is being considered to provide accurate estimations of soil properties, including soil organic carbon (SOC) and soil inorganic carbon (SIC) contents. This has mainly been demonstrated when datasets used to build, validate and test the prediction model originate from the same area A, with similar geopedological conditions. The objective of this study was to analyze how MIRS performed when used to predict SOC and SIC contents, from a calibration database collected over a region A, to predict over a region B, where A and B have no common area and different soil and climate conditions. This study used a French MIRS soil dataset including 2178 soil samples to calibrate SIC and SOC prediction models with partial least squares regression (PLSR), and a Tunisian MIRS soil dataset including 96 soil samples to test them. Our results showed that using the French MIRS soil database i) SOC and SIC of French samples were successfully predicted, ii) SIC of Tunisian samples was also predicted successfully, iii) local calibration significantly improved SOC prediction of Tunisian samples and iv) prediction models seemed more robust for SIC than for SOC. So in future, MIRS might replace, or at least be considered as, a conventional physico-chemical analysis technique, especially when as exhaustive as possible calibration database will become available.

How to cite: Chevallier, T., Gomez, C., Moulin, P., Bouferra, I., Hmaidi, K., Arrouays, D., Jolivet, C., and Barthès, B.: Prediction of soil organic and inorganic carbon concentrations in Tunisian samples by mid-infrared reflectance spectroscopy using a French national library, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13092, https://doi.org/10.5194/egusphere-egu2020-13092, 2020

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