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

Abstract

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.

Do we really need large spectral libraries for local scale SOC assessment with NIR spectroscopy?

“…The underrepresentation could be smaller if a stratified sampling is used to generate the library. However, it is almost unknown how to define or identify the strata to be sampled (Gogé et al, 2012;Grinand et al, 2012;Peng et al, 2013;Araújo et al, 2014;Shi et al, 2014). In general, these results were in agreement with those from Shepherd and Walsh (2002), who suggested the need of large spectral libraries for the construction of accurate models.…”

Estimating soil texture from vis–NIR spectra

“…For the PLSR models, our results confirm reports that spectral processing has little to no benefit for predictive modelling (Grinand et al ., ; Viscarra Rossel & Webster, ). In contrast, the models fitted with the RF algorithm were improved markedly after converting to z ‐scores.…”

Quantification of SOC and Clay Content Using Visible Near-Infrared Reflectance–Mid-Infrared Reflectance Spectroscopy With Jack-Knifing Partial Least Squares Regression

“…For SOC, information related to organic matter was found in the Vis-NIR region around 474; 556; 638; 832; 1,265; 1,720; and 2,165 to 2,443 nm. Absorption bands between 7,323 and 8,878 nm have been ascribed to C-O stretching and O-H bending in humic acid and aromatic amines (Stuart, 2004;Janik et al, 2007;Grinand et al, 2012). 5).…”

“…The MIR spectral features can be characterized by specific organic and inorganic spectral bands, whereas the NIR region gives much weaker and broader signals from vibration overtones and combination bands (McCarty et al, 2002;Stuart, 2004;Grinand et al, 2012). In the MIR spectral region, specific spectral features for aromatic (around 6,250 and 6,600 nm), carboxylic (around 3,425 and 5,780 nm), and carbohydrate groups (around 2,857 and 4,650 nm) can be found because of the stretching of the C-H, C=O, and C=C double bonds and carbohydrate C-OH deformation vibration, which are essential for identifying SOC (Ibrahim et al, 2008;Calderon et al, 2011;Grinand et al, 2012;Song et al, 2012). Rossel et al (2006) calibrated separately spectra from visible (400-700 nm), NIR (700-2,500 nm), MIR (2,500-25,000 nm), and the combination of all regions to predict soil properties (including, among others, SOC and soil texture).…”