Usefulness of near-infrared spectroscopy to determine biological and chemical soil properties: Importance of sample pre-treatment

Terhoeven‐Urselmans, Thomas; Schmidt, Harald; Joergensen, Rainer Georg; Ludwig, Bernard

doi:10.1016/j.soilbio.2007.12.011

Cited by 100 publications

(56 citation statements)

References 29 publications

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“…For instance, satisfactory, well, or excellent predictions of microbial biomass (C mic ) and basal respiration (coefficient of correlation [r 2 ] = 0.60-0.96, ratio of standard deviation in reference data to standard error of prediction [RPD] = 1.5-4.4) have been presented in several studies (Chang et al, 2001;Coûteaux et al, 2003;Terhoeven-Urselmans et al, 2008). However, inaccurate prediction indicated by the low RPD value (r 2 = 0.58, RPD = 1.1) has been reported as well (Terhoeven-Urselmans et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Near‐infrared spectroscopy for rapid estimation of microbial properties in reclaimed mine soils

Chodak

2011

Z. Pflanzenernähr. Bodenk.

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Several chemical and microbial properties of mine soils need to be measured for comprehensive assessment of the reclamation success. The objective of this study was to evaluate the ability of NIR spectroscopy to predict organic C (C org ), total N (N t ), and several microbial properties of mine soils reclaimed for forestry. Soils samples (n = 154) were collected at two reclaimed areas in central and S Poland, and their spectra in the NIR region (including the visible range, 400-2500 nm) were recorded. A half of the samples was used to develop calibration equations, and another half was used for validation. The modified partial least squares regression was applied to build calibration equations using the whole spectrum (0 to 2nd derivative). The best predictions were obtained for C org and N t (ratio of standard deviation to standard error of predic-

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Section: Introductionmentioning

confidence: 99%

Near‐infrared spectroscopy for rapid estimation of microbial properties in reclaimed mine soils

Chodak

2011

Z. Pflanzenernähr. Bodenk.

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“…Finally, it is essential to notice that the infrared data were validated using chemical analysis but not using biological activity factors, whereas the local variability observed using infrared spectroscopy could also be linked to the heterogeneous distribution of soil organisms (Ludwig et al 2015). Indeed, Terhoeven-Urselmans et al (2008) reported a high correlation between NIRS/MIRS and microbial properties, as ergosterol and microbial carbon measurements. Moreover, Morris (1999) found that considerable spatial variability in fungal and bacterial biomass exists at the 1-to 10-cm scale.…”

Section: Validation Of the Repeated Random Drawingmentioning

confidence: 99%

Improving the design of long-term monitoring experiments in forests: a new method for the assessment of local soil variability by combining infrared spectroscopy and dendrometric data

Akroume

Zeller

Buée

et al. 2016

Annals of Forest Science

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“…The glucose-responsive fraction of microbial biomass was assessed by the substrate induced respiration (SIR), according to Anderson & Domsch (1978). Fluorescein diacetate hydrolysis rate (hydrolase activity) was determined following the method of Schnürer & Rosswall (1982) using 3.6-diacetyl fluorescein as substrate and measuring the absorbance of the released fluorescein at 490 nm. β-glucosidase (EC 3.2.1.21) activity was assayed by the hydrolysis rate of p-nitrophenyl-β-D-glucopyranoside as substrate, detecting the absorbance of the released p-nitrophenol at 398 nm (Rodrí-guez-Loinaz et al 2008) with spectrophotometry (Lambda EZ201 ® , PerkinElmer Inc).…”

Section: Iforest -Biogeosciences and Forestrymentioning

confidence: 99%

Chemometric technique performances in predicting forest soil chemical and biological properties from UV-Vis-NIR reflectance spectra with small, high dimensional datasets

Bellino¹,

Colombo²,

Iovieno³

et al. 2016

iForest

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(1) Chemometric analysis applied to diffuse reflectance spectroscopy is increasingly proposed as an effective and accurate methodology to predict soil physical, chemical and biological properties. Its effectiveness, however, largely varies in relation to the calibration techniques and the specific soil properties. In addition, the calibration of UV-Vis-NIR spectra usually requires large datasets, and the identification of techniques suitable to deal with small sample sizes and high dimensionality problems is a primary challenge. In order to investigate the predictability of many soil chemical and biological properties from a small dataset and to identify the most suitable techniques to deal with this type of problems, we analysed 20 top soil samples of three different forests (Fagus sylvatica, Quercus cerris and Quercus ilex) in southern Apennines (Italy). Diffuse reflectance spectra were recorded in the UV-Vis-NIR range (200-2500 nm) and 22 chemical and biological properties were analysed. Three different calibration techniques were tested, namely the Partial Least Square Regression (PLSR), the combinations wavelet transformation/Elastic net and wavelet transformation/Supervised Principal Component (SPC) regression/ Least Absolute Shrinkage and Selection Operator (LASSO), a kind of preconditioned LASSO. Calibration techniques were applied to both raw spectra and spectra subjected to wavelet shrinkage filtering, in order to evaluate the influence on predictions of spectra denoising. Overall, SPC/LASSO outperformed the other techniques with both raw and denoised spectra. Elastic net produced heterogeneous results, but outperformed SPC/LASSO for total organic carbon, whereas PLSR produced the worst results. Spectra denoising improved the prediction accuracy of many parameters, but worsen the predictions in some cases. Our approach highlighted that: (i) SPC/LASSO (and Elastic net in the case of total organic carbon) is especially suitable to calibrate spectra in the case of small, high dimensional datasets; and (ii) spectra denoising could be an effective technique to improve calibration results.

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Usefulness of near-infrared spectroscopy to determine biological and chemical soil properties: Importance of sample pre-treatment

Cited by 100 publications

References 29 publications

Near‐infrared spectroscopy for rapid estimation of microbial properties in reclaimed mine soils

Near‐infrared spectroscopy for rapid estimation of microbial properties in reclaimed mine soils

Improving the design of long-term monitoring experiments in forests: a new method for the assessment of local soil variability by combining infrared spectroscopy and dendrometric data

Chemometric technique performances in predicting forest soil chemical and biological properties from UV-Vis-NIR reflectance spectra with small, high dimensional datasets

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