Dataset of visible-near infrared handheld and micro-spectrometers – comparison of the prediction accuracy of sugarcane properties

Dataset of visible-near infrared handheld and micro-spectrometers – comparison of the prediction accuracy of sugarcane properties

In the dataset presented in this article, sixty sugarcane samples were analyzed by eight visible / near infrared spectrometers including seven micro-spectrometers. There is one file per spectrometer with sample name, wavelength, absorbance data [calculated as log10 (1/Reflectance)], and another file...

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Main Authors: Abdallah Zgouz, Daphné Héran, Bernard Barthès, Denis Bastianelli, Laurent Bonnal, Vincent Baeten, Sebastien Lurol, Michael Bonin, Jean-Michel Roger, Ryad Bendoula, Gilles Chaix
Format: Article
Language:English
Published: Elsevier 2020-08-01
Series:Data in Brief
Subjects:
Micro-spectrometers
Handheld devices
Visible-near infrared spectroscopy
chemometrics, sugarcane
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340920309070
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spelling doaj-22391ab5aaa541118b3f84d547e1393a2020-11-25T02:54:22ZengElsevierData in Brief2352-34092020-08-0131106013Dataset of visible-near infrared handheld and micro-spectrometers – comparison of the prediction accuracy of sugarcane propertiesAbdallah Zgouz0Daphné Héran1Bernard Barthès2Denis Bastianelli3Laurent Bonnal4Vincent Baeten5Sebastien Lurol6Michael Bonin7Jean-Michel Roger8Ryad Bendoula9Gilles Chaix10HélioSPIR, 361 Rue Jean François Breton, 34196 Montpellier, FranceUMR ITAP, Inrae, Institut Agro, University of Montpellier, Montpellier, FranceEco&Sols, University of Montpellier, CIRAD, INRAE, IRD, Institut Agro, 34070 Montpellier, FranceHélioSPIR, 361 Rue Jean François Breton, 34196 Montpellier, France; CIRAD, UMR SELMET, F-34398 Montpellier, France; SELMET, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, FranceCIRAD, UMR SELMET, F-34398 Montpellier, France; SELMET, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, FranceQuality and Authentication of Products Unit, Walloon Agricultural Research Centre (CRA-W), Gembloux, BelgiumCTIFL, F-13210 Saint-Rémy-de-Provence, FranceFondis Electronic, 26 avenue René Duguay-Trouin 78960 Voisins-Le-Bretonneux, FranceHélioSPIR, 361 Rue Jean François Breton, 34196 Montpellier, France; UMR ITAP, Inrae, Institut Agro, University of Montpellier, Montpellier, France; ChemHouse Research Group, Montpellier, FranceHélioSPIR, 361 Rue Jean François Breton, 34196 Montpellier, France; UMR ITAP, Inrae, Institut Agro, University of Montpellier, Montpellier, FranceHélioSPIR, 361 Rue Jean François Breton, 34196 Montpellier, France; Cirad, UMR Agap, F-34398 Montpellier, France; Agap, Univ Montpellier, Cirad, Iinrae, Institut Agro, Montpellier, France; ChemHouse Research Group, Montpellier, France; Corresponding author.In the dataset presented in this article, sixty sugarcane samples were analyzed by eight visible / near infrared spectrometers including seven micro-spectrometers. There is one file per spectrometer with sample name, wavelength, absorbance data [calculated as log10 (1/Reflectance)], and another file for reference data, in order to assess the potential of the micro-spectrometers to predict chemical properties of sugarcane samples and to compare their performance with a LabSpec spectrometer. The Partial Least Square Regression (PLS-R) algorithm was used to build calibration models. This open access dataset could also be used to test new chemometric methods, for training, etc.http://www.sciencedirect.com/science/article/pii/S2352340920309070Micro-spectrometersHandheld devicesVisible-near infrared spectroscopychemometrics, sugarcane
collection DOAJ
language English
format Article
sources DOAJ
author Abdallah Zgouz
Daphné Héran
Bernard Barthès
Denis Bastianelli
Laurent Bonnal
Vincent Baeten
Sebastien Lurol
Michael Bonin
Jean-Michel Roger
Ryad Bendoula
Gilles Chaix
spellingShingle Abdallah Zgouz
Daphné Héran
Bernard Barthès
Denis Bastianelli
Laurent Bonnal
Vincent Baeten
Sebastien Lurol
Michael Bonin
Jean-Michel Roger
Ryad Bendoula
Gilles Chaix
Dataset of visible-near infrared handheld and micro-spectrometers – comparison of the prediction accuracy of sugarcane properties
Data in Brief
Micro-spectrometers
Handheld devices
Visible-near infrared spectroscopy
chemometrics, sugarcane
author_facet Abdallah Zgouz
Daphné Héran
Bernard Barthès
Denis Bastianelli
Laurent Bonnal
Vincent Baeten
Sebastien Lurol
Michael Bonin
Jean-Michel Roger
Ryad Bendoula
Gilles Chaix
author_sort Abdallah Zgouz
title Dataset of visible-near infrared handheld and micro-spectrometers – comparison of the prediction accuracy of sugarcane properties
title_short Dataset of visible-near infrared handheld and micro-spectrometers – comparison of the prediction accuracy of sugarcane properties
title_full Dataset of visible-near infrared handheld and micro-spectrometers – comparison of the prediction accuracy of sugarcane properties
title_fullStr Dataset of visible-near infrared handheld and micro-spectrometers – comparison of the prediction accuracy of sugarcane properties
title_full_unstemmed Dataset of visible-near infrared handheld and micro-spectrometers – comparison of the prediction accuracy of sugarcane properties
title_sort dataset of visible-near infrared handheld and micro-spectrometers – comparison of the prediction accuracy of sugarcane properties
publisher Elsevier
series Data in Brief
issn 2352-3409
publishDate 2020-08-01
description In the dataset presented in this article, sixty sugarcane samples were analyzed by eight visible / near infrared spectrometers including seven micro-spectrometers. There is one file per spectrometer with sample name, wavelength, absorbance data [calculated as log10 (1/Reflectance)], and another file for reference data, in order to assess the potential of the micro-spectrometers to predict chemical properties of sugarcane samples and to compare their performance with a LabSpec spectrometer. The Partial Least Square Regression (PLS-R) algorithm was used to build calibration models. This open access dataset could also be used to test new chemometric methods, for training, etc.
topic Micro-spectrometers
Handheld devices
Visible-near infrared spectroscopy
chemometrics, sugarcane
url http://www.sciencedirect.com/science/article/pii/S2352340920309070
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