The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in Tea

[EN] The following study analyzed the potential of Near Infrared Spectroscopy (NIRS) to predict the metal composition (Al, Pb, As, Hg and Cu) of tea and for establishing discriminant models for pure teas (green, red, and black) and their different blends. A total of 322 samples of pure black, red, a...

Full description

Bibliographic Details
Authors: Valderrama, Patricia, Rodríguez-Fernández, Marta, Revilla Martín, Isabel, Hernández Jiménez, Miriam, Martínez Martín, Iván, Vivar Quintana, Ana María
Format: article
Status:Published version
Publication Date:2024
Country:España
Institution:Universidad de Salamanca (USAL)
Repository:GREDOS. Repositorio Institucional de la Universidad de Salamanca
OAI Identifier:oai:gredos.usal.es:10366/160573
Online Access:http://hdl.handle.net/10366/160573
Access Level:Open access
Keyword:NIRS (Near Infrared Spectroscopy)
Residual Mean Square residuals
Black tea
Green tea
Red tea
Espectroscopía del infrarrojo cercano
Suma residual de cuadrados
Té negro
Té verde
Té rojo
2209.21 Espectroscopia
id ES_9ac111cc1deeeffbb2503b52f9cee8d4
oai_identifier_str oai:gredos.usal.es:10366/160573
network_acronym_str ES
network_name_str España
repository_id_str
spelling The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in TeaValderrama, PatriciaRodríguez-Fernández, MartaRevilla Martín, IsabelHernández Jiménez, MiriamMartínez Martín, IvánVivar Quintana, Ana MaríaNIRS (Near Infrared Spectroscopy)Residual Mean Square residualsBlack teaGreen teaRed teaEspectroscopía del infrarrojo cercanoSuma residual de cuadradosTé negroTé verdeTé rojo2209.21 Espectroscopia[EN] The following study analyzed the potential of Near Infrared Spectroscopy (NIRS) to predict the metal composition (Al, Pb, As, Hg and Cu) of tea and for establishing discriminant models for pure teas (green, red, and black) and their different blends. A total of 322 samples of pure black, red, and green teas and binary blends were analyzed. The results showed that pure red teas had the highest content of As and Pb, green teas were the only ones containing Hg, and black teas showed higher levels of Cu. NIRS allowed to predict the content of Al, Pb, As, Hg, and Cu with ratio performance deviation values > 3 for all of them. Additionally, it was possible to discriminate pure samples from their respective blends with an accuracy of 98.3% in calibration and 92.3% in validation. However, when the samples were discriminated according to the percentage of blending (>95%, 95-85%, 85-75%, or 75-50% of pure tea) 100% of the samples of 10 out of 12 groups were correctly classified in calibration, but only the groups with a level of pure tea of >95% showed 100% of the samples as being correctly classified as to validation.MDPI202420242024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10366/160573reponame:GREDOS. Repositorio Institucional de la Universidad de Salamancainstname:Universidad de Salamanca (USAL)Inglésinfo:eu-repo/semantics/openAccessoai:gredos.usal.es:10366/1605732026-06-07T06:28:51Z
dc.title.none.fl_str_mv The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in Tea
title The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in Tea
spellingShingle The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in Tea
Valderrama, Patricia
NIRS (Near Infrared Spectroscopy)
Residual Mean Square residuals
Black tea
Green tea
Red tea
Espectroscopía del infrarrojo cercano
Suma residual de cuadrados
Té negro
Té verde
Té rojo
2209.21 Espectroscopia
title_short The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in Tea
title_full The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in Tea
title_fullStr The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in Tea
title_full_unstemmed The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in Tea
title_sort The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in Tea
dc.creator.none.fl_str_mv Valderrama, Patricia
Rodríguez-Fernández, Marta
Revilla Martín, Isabel
Hernández Jiménez, Miriam
Martínez Martín, Iván
Vivar Quintana, Ana María
author Valderrama, Patricia
author_facet Valderrama, Patricia
Rodríguez-Fernández, Marta
Revilla Martín, Isabel
Hernández Jiménez, Miriam
Martínez Martín, Iván
Vivar Quintana, Ana María
author_role author
author2 Rodríguez-Fernández, Marta
Revilla Martín, Isabel
Hernández Jiménez, Miriam
Martínez Martín, Iván
Vivar Quintana, Ana María
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv NIRS (Near Infrared Spectroscopy)
Residual Mean Square residuals
Black tea
Green tea
Red tea
Espectroscopía del infrarrojo cercano
Suma residual de cuadrados
Té negro
Té verde
Té rojo
2209.21 Espectroscopia
topic NIRS (Near Infrared Spectroscopy)
Residual Mean Square residuals
Black tea
Green tea
Red tea
Espectroscopía del infrarrojo cercano
Suma residual de cuadrados
Té negro
Té verde
Té rojo
2209.21 Espectroscopia
description [EN] The following study analyzed the potential of Near Infrared Spectroscopy (NIRS) to predict the metal composition (Al, Pb, As, Hg and Cu) of tea and for establishing discriminant models for pure teas (green, red, and black) and their different blends. A total of 322 samples of pure black, red, and green teas and binary blends were analyzed. The results showed that pure red teas had the highest content of As and Pb, green teas were the only ones containing Hg, and black teas showed higher levels of Cu. NIRS allowed to predict the content of Al, Pb, As, Hg, and Cu with ratio performance deviation values > 3 for all of them. Additionally, it was possible to discriminate pure samples from their respective blends with an accuracy of 98.3% in calibration and 92.3% in validation. However, when the samples were discriminated according to the percentage of blending (>95%, 95-85%, 85-75%, or 75-50% of pure tea) 100% of the samples of 10 out of 12 groups were correctly classified in calibration, but only the groups with a level of pure tea of >95% showed 100% of the samples as being correctly classified as to validation.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10366/160573
url http://hdl.handle.net/10366/160573
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:GREDOS. Repositorio Institucional de la Universidad de Salamanca
instname:Universidad de Salamanca (USAL)
instname_str Universidad de Salamanca (USAL)
reponame_str GREDOS. Repositorio Institucional de la Universidad de Salamanca
collection GREDOS. Repositorio Institucional de la Universidad de Salamanca
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869414430643585024
score 15.811543

Similar Items