Prediction of soil organic and inorganic carbon contents at a national scale (France) using mid‐infrared reflectance spectroscopy (MIRS)

European Journal of Soil Science - Tập 63 Số 2 - Trang 141-151 - 2012
Clovis Grinand1, Bernard Barthès1, Didier Brunet1, Ernest Kouakoua1, Dominique Arrouays2, Claudy Jolivet2, Giovanni Caria3, Martial Bernoux1
1Institut de Recherche pour le Développement (IRD), UMR Eco&Sols (Montpellier SupAgro-CIRAD-INRA-IRD), 2 place Viala, bât. 12, 34060 Montpellier Cedex 2, France
2Institut National de La Recherche Agronomique (INRA), US 1106 INFOSOL, 2163 avenue de la Pomme de Pin, CS 40001 Ardon, 45075 Orléans Cedex 2, France
3INRA, US 010, Laboratoire d’analyses des sols, 273 rue de Cambrai, 62000 Arras, France

Tóm tắt

This work aimed to evaluate the potential of mid‐infrared reflectance spectroscopy (MIRS) to predict soil organic and inorganic carbon contents with a 2086‐sample set representative of French topsoils (0–30 cm). Ground air‐dried samples collected regularly using a 16 × 16‐km grid were analysed for total (dry combustion) and inorganic (calcimeter) carbon; organic carbon was calculated by difference. Calibrations of MIR spectra with partial least square regressions were developed with 10–80% of the set and five random selections of samples. Comparisons between samples with contrasting organic or inorganic carbon content and regression coefficients of calibration equations both showed that organic carbon was firstly associated with a wide spectral region around 2500–3500 cm−1 (which was a reflection of its complex nature), and inorganic carbon with narrow spectral bands, especially around 2520 cm−1. Optimal calibrations for both organic and inorganic carbon were achieved by using 20% of the total set: predictions were not improved much by including more of the set and were less stable, probably because of atypical samples. At the 20% rate, organic carbon predictions over the validation set (80% of the total) yielded mean R2, standard error of prediction (SEP) and RPD (ratio of standard deviation to SEP) of 0.89, 6.7 g kg−1 and 3.0, respectively; inorganic carbon predictions yielded 0.97, 2.8 g kg−1 and 5.6, respectively. This seemed appropriate for large‐scale soil inventories and mapping studies but not for accurate carbon monitoring, possibly because carbonate soils were included. More work is needed on organic carbon calibrations for large‐scale soil libraries.

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