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Dataset of chemical and near-infrared spectroscopy measurements of fresh and dried poultry and cattle manure

Combined with multivariate calibration methods, near-infrared (NIR) spectroscopy is a non-destructive, rapid, precise and inexpensive analytical method to predict chemical contents of organic products. Nevertheless, one practical limitation of this approach is that performance of the calibration mod...

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Autores principales: Gogé, Fabien, Thuriès, Laurent, Fouad, Youssef, Damay, Nathalie, Davrieux, Fabrice, Moussard, Géraud, Roux, Caroline Le, Trupin-Maudemain, Séverine, Valé, Matthieu, Morvan, Thierry
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7749372/
https://www.ncbi.nlm.nih.gov/pubmed/33365375
http://dx.doi.org/10.1016/j.dib.2020.106647
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author Gogé, Fabien
Thuriès, Laurent
Fouad, Youssef
Damay, Nathalie
Davrieux, Fabrice
Moussard, Géraud
Roux, Caroline Le
Trupin-Maudemain, Séverine
Valé, Matthieu
Morvan, Thierry
author_facet Gogé, Fabien
Thuriès, Laurent
Fouad, Youssef
Damay, Nathalie
Davrieux, Fabrice
Moussard, Géraud
Roux, Caroline Le
Trupin-Maudemain, Séverine
Valé, Matthieu
Morvan, Thierry
author_sort Gogé, Fabien
collection PubMed
description Combined with multivariate calibration methods, near-infrared (NIR) spectroscopy is a non-destructive, rapid, precise and inexpensive analytical method to predict chemical contents of organic products. Nevertheless, one practical limitation of this approach is that performance of the calibration model may decrease when the data are acquired with different spectrometers. To overcome this limitation, standardization methods exist, such as the piecewise direct standardization (PDS) algorithm. The dataset presented in this article consists of 332 manure samples from poultry and cattle, sampled from farms located in major regions of livestock production in mainland France and Reunion Island. The samples were analysed for seven chemical properties following conventional laboratory methods. NIR spectra were acquired with three spectrometers from fresh homogenized and dried ground samples and then standardized using the PDS algorithm. This important dataset can be used to train and test chemometric models and is of particular interest to NIR spectroscopists and agronomists who assess the agronomic value of animal waste.
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spelling pubmed-77493722020-12-22 Dataset of chemical and near-infrared spectroscopy measurements of fresh and dried poultry and cattle manure Gogé, Fabien Thuriès, Laurent Fouad, Youssef Damay, Nathalie Davrieux, Fabrice Moussard, Géraud Roux, Caroline Le Trupin-Maudemain, Séverine Valé, Matthieu Morvan, Thierry Data Brief Data Article Combined with multivariate calibration methods, near-infrared (NIR) spectroscopy is a non-destructive, rapid, precise and inexpensive analytical method to predict chemical contents of organic products. Nevertheless, one practical limitation of this approach is that performance of the calibration model may decrease when the data are acquired with different spectrometers. To overcome this limitation, standardization methods exist, such as the piecewise direct standardization (PDS) algorithm. The dataset presented in this article consists of 332 manure samples from poultry and cattle, sampled from farms located in major regions of livestock production in mainland France and Reunion Island. The samples were analysed for seven chemical properties following conventional laboratory methods. NIR spectra were acquired with three spectrometers from fresh homogenized and dried ground samples and then standardized using the PDS algorithm. This important dataset can be used to train and test chemometric models and is of particular interest to NIR spectroscopists and agronomists who assess the agronomic value of animal waste. Elsevier 2020-12-13 /pmc/articles/PMC7749372/ /pubmed/33365375 http://dx.doi.org/10.1016/j.dib.2020.106647 Text en © 2020 The Authors. Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Gogé, Fabien
Thuriès, Laurent
Fouad, Youssef
Damay, Nathalie
Davrieux, Fabrice
Moussard, Géraud
Roux, Caroline Le
Trupin-Maudemain, Séverine
Valé, Matthieu
Morvan, Thierry
Dataset of chemical and near-infrared spectroscopy measurements of fresh and dried poultry and cattle manure
title Dataset of chemical and near-infrared spectroscopy measurements of fresh and dried poultry and cattle manure
title_full Dataset of chemical and near-infrared spectroscopy measurements of fresh and dried poultry and cattle manure
title_fullStr Dataset of chemical and near-infrared spectroscopy measurements of fresh and dried poultry and cattle manure
title_full_unstemmed Dataset of chemical and near-infrared spectroscopy measurements of fresh and dried poultry and cattle manure
title_short Dataset of chemical and near-infrared spectroscopy measurements of fresh and dried poultry and cattle manure
title_sort dataset of chemical and near-infrared spectroscopy measurements of fresh and dried poultry and cattle manure
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7749372/
https://www.ncbi.nlm.nih.gov/pubmed/33365375
http://dx.doi.org/10.1016/j.dib.2020.106647
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