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GC-IMS data on the discrimination between geographic origins of olive oils

Gas chromatography hyphenated with ion mobility spectrometry (GC-IMS) is an emerging benchtop technique for sensitive and selective detection of volatile organic compounds. It is commonly used for non-target screening (NTS) of complex sample materials, such as food products. Resulting spectra are us...

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Detalles Bibliográficos
Autores principales: Christmann, Joscha, Rohn, Sascha, Weller, Philipp
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679686/
https://www.ncbi.nlm.nih.gov/pubmed/36426046
http://dx.doi.org/10.1016/j.dib.2022.108730
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author Christmann, Joscha
Rohn, Sascha
Weller, Philipp
author_facet Christmann, Joscha
Rohn, Sascha
Weller, Philipp
author_sort Christmann, Joscha
collection PubMed
description Gas chromatography hyphenated with ion mobility spectrometry (GC-IMS) is an emerging benchtop technique for sensitive and selective detection of volatile organic compounds. It is commonly used for non-target screening (NTS) of complex sample materials, such as food products. Resulting spectra are used as “fingerprints” for multivariate chemometric data analysis to extract information. This has been successfully applied in the field of food fraud detection in several published studies. The presented dataset contains GC-IMS measurements of extra virgin olive oil samples from Spain, Italy, and Greece. It allows classification and class modelling to differentiate geographic origins and was used in the associated publication gc-ims-tools, a new Python package for chemometric analysis of GC-IMS data (https://doi.org/10.1016/j.foodchem.2022.133476) as an example to demonstrate the functionality.
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spelling pubmed-96796862022-11-23 GC-IMS data on the discrimination between geographic origins of olive oils Christmann, Joscha Rohn, Sascha Weller, Philipp Data Brief Data Article Gas chromatography hyphenated with ion mobility spectrometry (GC-IMS) is an emerging benchtop technique for sensitive and selective detection of volatile organic compounds. It is commonly used for non-target screening (NTS) of complex sample materials, such as food products. Resulting spectra are used as “fingerprints” for multivariate chemometric data analysis to extract information. This has been successfully applied in the field of food fraud detection in several published studies. The presented dataset contains GC-IMS measurements of extra virgin olive oil samples from Spain, Italy, and Greece. It allows classification and class modelling to differentiate geographic origins and was used in the associated publication gc-ims-tools, a new Python package for chemometric analysis of GC-IMS data (https://doi.org/10.1016/j.foodchem.2022.133476) as an example to demonstrate the functionality. Elsevier 2022-11-08 /pmc/articles/PMC9679686/ /pubmed/36426046 http://dx.doi.org/10.1016/j.dib.2022.108730 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Christmann, Joscha
Rohn, Sascha
Weller, Philipp
GC-IMS data on the discrimination between geographic origins of olive oils
title GC-IMS data on the discrimination between geographic origins of olive oils
title_full GC-IMS data on the discrimination between geographic origins of olive oils
title_fullStr GC-IMS data on the discrimination between geographic origins of olive oils
title_full_unstemmed GC-IMS data on the discrimination between geographic origins of olive oils
title_short GC-IMS data on the discrimination between geographic origins of olive oils
title_sort gc-ims data on the discrimination between geographic origins of olive oils
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679686/
https://www.ncbi.nlm.nih.gov/pubmed/36426046
http://dx.doi.org/10.1016/j.dib.2022.108730
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