Soil carbon measurement in clods and sieved samples in a Mediterranean Vertisol by Visible and Near-Infrared Reflectance Spectroscopy

Fontán, José M.; Calvache, Sara; López‐Bellido, Rafael J.; López‐Bellido, Luis

doi:10.1016/j.geoderma.2010.02.001

Cited by 31 publications

(19 citation statements)

References 27 publications

(40 reference statements)

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“…In this case the effect of soil moisture appears to be more attenuating than soil structure or aggregation. A study by Fontan et al (2010) had similar findings when comparing results derived by scans of dried ground soil and dried soil clods. In contrasting results, the effect of soil smearing resulted in less accurate predictions of clay in Waiser et al (2007), yet had no effect when predicting soil carbon in Morgan et al (2009).…”

Section: Taking Ir and Pxrf To The Field And The Role Of Spectral Libsupporting

confidence: 52%

Potential of integrated field spectroscopy and spatial analysis for enhanced assessment of soil contamination: A prospective review

et al. 2015

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a b s t r a c tThere are tens of millions of contaminated soil sites in the world, and with an increasing population and associated risk there is a growing pressure to remediate them. A barrier to remediation is the lack of cost-effective approaches to assessment. Soil contaminants include a wide range of natural and synthetic metallic and organic compounds and minerals thus making analytical costs potentially very large. Further, soil contaminants show a large degree of spatial variation which increases the burden on sampling costs. This paper reviews potentially cost-effective methods for measurement, sampling design, and assessment. Current tiered investigation approaches and sampling strategies can be improved by using new technologies such as proximal sensing. Design of sampling can be aided by on-the-go proximal soil sensing; and expedited by subsequent adaptive spatially optimal sampling and prediction procedures enabled by field spectroscopic methods and advanced geostatistics. Field deployment of portable Visible & Near Infrared [wavelength 400-2500 nm] (Vis-NIR) and X-ray fluorescence (PXRF) spectroscopies will require special calibration approaches but show huge potential for synergistic use. The use of mid-infrared spectroscopy [wavelength 2500-25,000 nm, wavenumber 4000-400 cm −1 ] (MIR) for field implementation requires further adaptive research. We propose an integrated field-deployable methodology as a basis for further developments. Crown

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Section: Taking Ir and Pxrf To The Field And The Role Of Spectral Libsupporting

confidence: 52%

Potential of integrated field spectroscopy and spatial analysis for enhanced assessment of soil contamination: A prospective review

et al. 2015

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“…As described by Ludwig et al (2008), the mathematical treatment of spectra includes the following: no data treatment, subtraction of a constant offset (SCO), subtraction of a linear function (SLF), vector normalization (VN), minimum maximum scaling (MMS), multiplicative scatter correction (MSC), first derivative, second derivative, first derivative + SLF, first derivative + VN and first derivative + MSC. In all cases, model calibration is based on full‐cross‐validation (Bornemann et al , 2008; Ludwig et al , 2008; Fontán et al , 2010).…”

Section: Methodsmentioning

confidence: 99%

“…While several studies (Shenk et al , 1992; Reeves et al , 2002) reported positive effects on the NIRS model prediction by using a greater degree of grinding, Fystro (2002) suggested that sample grinding does not always improve the prediction. Fontán et al (2010) compared NIRS models for total organic carbon (TOC) prediction from intact soil crumbs and ground and sieved samples from a Mediterranean Vertisol. They concluded that estimating TOC with NIRS using soil crumbs may be a viable option with respect to the time and effort required to grind and sieve the samples.…”

Section: Introductionmentioning

confidence: 99%

Sample preparation and selection for qualitative and quantitative analyses of soil organic carbon with mid-infrared reflectance spectroscopy

Stumpe

Weihermüller

Marschner

2011

European Journal of Soil Science

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Mid-infrared spectroscopy (MIRS) is a well-established analytical tool for qualitative and quantitative analysis of soil samples. However, effects of soil sample grinding procedures on the prediction accuracy of MIR models and on qualitative spectral information have not been well investigated and, in consequence, not standardized up to now. Further, the effects of soil sample selection on the accuracy of MIR prediction models has not been quantified yet. This study investigated these effects by using 180 well-characterized soil samples that were ground for different times (0, 2 or 4 minutes) and then used for MIR measurements. To study the impact of sample preparation, soil spectra were subjected to principal component analyses (PCA), multiple regression and partial least square (PLS) analysis. The results indicate that the prediction accuracy of MIR models for soil organic carbon (SOC) and pH and the qualitative spectral information were better overall for lightly ground (2 minutes) soil samples compared with intensively (4 minutes) or unground soil samples. Whereas the grinding procedure did not show any effect on spectra of clay minerals, spectral information for quartz and for SOC was modified. Even though it is difficult to recommend a global standardized soil sample grinding procedure for MIR measurements because of different mill types available within laboratories, we highly recommend using an internally standardized grinding procedure. Moreover, we show that neither land use nor soil sampling depth influences the prediction of the SOC content. However, sand and clay content substantially affect the score vectors used by the PLS algorithm to predict the SOC content. Thus, we recommend using soil samples similar in texture for more precise SOC calibration models for MIR spectroscopy.

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“…In recent years, a comprehensive literature review found that partial least squares regression (PLSR) is the most common VNIR calibration method (Dunn et al, 2002;Morgan et al, 2009;Escribano et al, 2010;Fontan et al, 2010). Although PLSR has many advantages, such as its simplicity, robustness, predictability, precision, and clearly quantitative explanations, the principal disadvantage is that PLSR does not provide a quantitative explanation for the relationship between predictor variables and response variables, and it does not support re-use of model algorithms between variable instrumentations.…”

Section: Introductionmentioning

confidence: 99%

Prediction of soil organic matter content in a litchi orchard of South China using spectral indices

Chen

Peng

et al. 2012

Soil and Tillage Research

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Soil carbon measurement in clods and sieved samples in a Mediterranean Vertisol by Visible and Near-Infrared Reflectance Spectroscopy

Cited by 31 publications

References 27 publications

Potential of integrated field spectroscopy and spatial analysis for enhanced assessment of soil contamination: A prospective review

Potential of integrated field spectroscopy and spatial analysis for enhanced assessment of soil contamination: A prospective review

Sample preparation and selection for qualitative and quantitative analyses of soil organic carbon with mid-infrared reflectance spectroscopy

Prediction of soil organic matter content in a litchi orchard of South China using spectral indices

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