Brazilian Canephora coffee evaluation using NIR spectroscopy and discriminant chemometric techniques.
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1151891 |
Resumo: | High-quality Brazilian Canephora coffees are rising to the level of specialty coffees in the face of a new industry perception. In this framework, spectra from 527 coffees were analyzed in the near-infrared (NIR) region. Prin- cipal component analysis distinguished Brazilian Canephora producing states, botanical varieties, low and high- quality Canephora, Canephora and Arabica, and Canephora with geographical indication (GI) from those without GI. Also, Canephora coffee cultivars from Western Brazilian Amazon were distinguished. Three multi-class PLS- DA (traditional, hard, and soft versions) were compared to discriminate 5 classes: Robusta Amaz?onico from traditional (1) and indigenous (2) producers of Rond?onia, Conilon from Espírito Santo (3), Conilon from Bahia (4), and specialty Arabica (5). Binary PLS-DA discriminated GI Canephora and non-GI Canephora with 100% sensitivity and specificity. Carbohydrates, chlorogenic acids, lipids, caffeine, and proteins were dominant ab- sorption bands in coffee classifications. The proposed method is objective, simple, fast, and could be used in the routine analysis of coffee to verify claims of identity, variety, and origin. |
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Brazilian Canephora coffee evaluation using NIR spectroscopy and discriminant chemometric techniques.Amazonian robustaConilonGeographical originMultivariate classificationNIR spectroscopyPLS-DAHigh-quality Brazilian Canephora coffees are rising to the level of specialty coffees in the face of a new industry perception. In this framework, spectra from 527 coffees were analyzed in the near-infrared (NIR) region. Prin- cipal component analysis distinguished Brazilian Canephora producing states, botanical varieties, low and high- quality Canephora, Canephora and Arabica, and Canephora with geographical indication (GI) from those without GI. Also, Canephora coffee cultivars from Western Brazilian Amazon were distinguished. Three multi-class PLS- DA (traditional, hard, and soft versions) were compared to discriminate 5 classes: Robusta Amaz?onico from traditional (1) and indigenous (2) producers of Rond?onia, Conilon from Espírito Santo (3), Conilon from Bahia (4), and specialty Arabica (5). Binary PLS-DA discriminated GI Canephora and non-GI Canephora with 100% sensitivity and specificity. Carbohydrates, chlorogenic acids, lipids, caffeine, and proteins were dominant ab- sorption bands in coffee classifications. The proposed method is objective, simple, fast, and could be used in the routine analysis of coffee to verify claims of identity, variety, and origin.MICHEL ROCHA BAQUETA, UNICAMP; ENRIQUE ANASTACIO ALVES, CPAF-RO; PATRÍCIA VALDERRAMA, UTFPR; JULIANA AZEVEDO LIMA PALLONE, UNICAMP.BAQUETA, M. R.ALVES, E. A.VALDERRAMA, P.PALLONE, J. A. L.2023-02-23T15:57:19Z2023-02-23T15:57:19Z2023-02-232023info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleJournal of Food Composition and Analysis, v. 116, 2023.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1151891porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2023-02-23T15:57:19Zoai:www.alice.cnptia.embrapa.br:doc/1151891Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542023-02-23T15:57:19falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542023-02-23T15:57:19Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Brazilian Canephora coffee evaluation using NIR spectroscopy and discriminant chemometric techniques. |
title |
Brazilian Canephora coffee evaluation using NIR spectroscopy and discriminant chemometric techniques. |
spellingShingle |
Brazilian Canephora coffee evaluation using NIR spectroscopy and discriminant chemometric techniques. BAQUETA, M. R. Amazonian robusta Conilon Geographical origin Multivariate classification NIR spectroscopy PLS-DA |
title_short |
Brazilian Canephora coffee evaluation using NIR spectroscopy and discriminant chemometric techniques. |
title_full |
Brazilian Canephora coffee evaluation using NIR spectroscopy and discriminant chemometric techniques. |
title_fullStr |
Brazilian Canephora coffee evaluation using NIR spectroscopy and discriminant chemometric techniques. |
title_full_unstemmed |
Brazilian Canephora coffee evaluation using NIR spectroscopy and discriminant chemometric techniques. |
title_sort |
Brazilian Canephora coffee evaluation using NIR spectroscopy and discriminant chemometric techniques. |
author |
BAQUETA, M. R. |
author_facet |
BAQUETA, M. R. ALVES, E. A. VALDERRAMA, P. PALLONE, J. A. L. |
author_role |
author |
author2 |
ALVES, E. A. VALDERRAMA, P. PALLONE, J. A. L. |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
MICHEL ROCHA BAQUETA, UNICAMP; ENRIQUE ANASTACIO ALVES, CPAF-RO; PATRÍCIA VALDERRAMA, UTFPR; JULIANA AZEVEDO LIMA PALLONE, UNICAMP. |
dc.contributor.author.fl_str_mv |
BAQUETA, M. R. ALVES, E. A. VALDERRAMA, P. PALLONE, J. A. L. |
dc.subject.por.fl_str_mv |
Amazonian robusta Conilon Geographical origin Multivariate classification NIR spectroscopy PLS-DA |
topic |
Amazonian robusta Conilon Geographical origin Multivariate classification NIR spectroscopy PLS-DA |
description |
High-quality Brazilian Canephora coffees are rising to the level of specialty coffees in the face of a new industry perception. In this framework, spectra from 527 coffees were analyzed in the near-infrared (NIR) region. Prin- cipal component analysis distinguished Brazilian Canephora producing states, botanical varieties, low and high- quality Canephora, Canephora and Arabica, and Canephora with geographical indication (GI) from those without GI. Also, Canephora coffee cultivars from Western Brazilian Amazon were distinguished. Three multi-class PLS- DA (traditional, hard, and soft versions) were compared to discriminate 5 classes: Robusta Amaz?onico from traditional (1) and indigenous (2) producers of Rond?onia, Conilon from Espírito Santo (3), Conilon from Bahia (4), and specialty Arabica (5). Binary PLS-DA discriminated GI Canephora and non-GI Canephora with 100% sensitivity and specificity. Carbohydrates, chlorogenic acids, lipids, caffeine, and proteins were dominant ab- sorption bands in coffee classifications. The proposed method is objective, simple, fast, and could be used in the routine analysis of coffee to verify claims of identity, variety, and origin. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-02-23T15:57:19Z 2023-02-23T15:57:19Z 2023-02-23 2023 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Journal of Food Composition and Analysis, v. 116, 2023. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1151891 |
identifier_str_mv |
Journal of Food Composition and Analysis, v. 116, 2023. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1151891 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
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1794503540105805824 |