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

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...

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Main Authors: Bellino A, Colombo C, Iovieno P, Alfani A, Palumbo G, Baldantoni D
Format: Article
Language:English
Published: Italian Society of Silviculture and Forest Ecology (SISEF) 2016-02-01
Series:iForest - Biogeosciences and Forestry
Subjects:
Online Access:https://iforest.sisef.org/contents/?id=ifor1495-008
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spelling doaj-808a2fcbc65f4fadbcac151bd554faa22020-11-24T23:51:00ZengItalian Society of Silviculture and Forest Ecology (SISEF)iForest - Biogeosciences and Forestry1971-74581971-74582016-02-019110110810.3832/ifor1495-0081495Chemometric technique performances in predicting forest soil chemical and biological properties from UV-Vis-NIR reflectance spectra with small, high dimensional datasetsBellino A0Colombo C1Iovieno P2Alfani A3Palumbo G4Baldantoni D5Dipartimento di Chimica e Biologia, Università degli Studi di Salerno, v. Giovanni Paolo II 132, I-84084 Fisciano, Salerno (Italy)Dipartimento di Agricoltura Ambiente Alimenti, Università degli Studi del Molise, v. De Sanctis, I-86100 ampobasso (Italy)Consiglio per la Ricerca e la Sperimentazione in Agricoltura (CRA), Centro di ricerca per l’Orticoltura, v. Cavalleggeri 25, I-84098 Pontecagnano, Salerno (Italy)Dipartimento di Chimica e Biologia, Università degli Studi di Salerno, v. Giovanni Paolo II 132, I-84084 Fisciano, Salerno (Italy)Dipartimento di Agricoltura Ambiente Alimenti, Università degli Studi del Molise, v. De Sanctis, I-86100 ampobasso (Italy)Dipartimento di Chimica e Biologia, Università degli Studi di Salerno, v. Giovanni Paolo II 132, I-84084 Fisciano, Salerno (Italy)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.https://iforest.sisef.org/contents/?id=ifor1495-008Elastic NetPLSRSPC/LASSOWaveletsDiffuse Reflectance SpectroscopySample Size
collection DOAJ
language English
format Article
sources DOAJ
author Bellino A
Colombo C
Iovieno P
Alfani A
Palumbo G
Baldantoni D
spellingShingle Bellino A
Colombo C
Iovieno P
Alfani A
Palumbo G
Baldantoni D
Chemometric technique performances in predicting forest soil chemical and biological properties from UV-Vis-NIR reflectance spectra with small, high dimensional datasets
iForest - Biogeosciences and Forestry
Elastic Net
PLSR
SPC/LASSO
Wavelets
Diffuse Reflectance Spectroscopy
Sample Size
author_facet Bellino A
Colombo C
Iovieno P
Alfani A
Palumbo G
Baldantoni D
author_sort Bellino A
title Chemometric technique performances in predicting forest soil chemical and biological properties from UV-Vis-NIR reflectance spectra with small, high dimensional datasets
title_short Chemometric technique performances in predicting forest soil chemical and biological properties from UV-Vis-NIR reflectance spectra with small, high dimensional datasets
title_full Chemometric technique performances in predicting forest soil chemical and biological properties from UV-Vis-NIR reflectance spectra with small, high dimensional datasets
title_fullStr Chemometric technique performances in predicting forest soil chemical and biological properties from UV-Vis-NIR reflectance spectra with small, high dimensional datasets
title_full_unstemmed Chemometric technique performances in predicting forest soil chemical and biological properties from UV-Vis-NIR reflectance spectra with small, high dimensional datasets
title_sort chemometric technique performances in predicting forest soil chemical and biological properties from uv-vis-nir reflectance spectra with small, high dimensional datasets
publisher Italian Society of Silviculture and Forest Ecology (SISEF)
series iForest - Biogeosciences and Forestry
issn 1971-7458
1971-7458
publishDate 2016-02-01
description 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.
topic Elastic Net
PLSR
SPC/LASSO
Wavelets
Diffuse Reflectance Spectroscopy
Sample Size
url https://iforest.sisef.org/contents/?id=ifor1495-008
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