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Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | BAQUETA, M. R. | |
dc.contributor.author | ALVES, E. A. | |
dc.contributor.author | VALDERRAMA, P. | |
dc.contributor.author | PALLONE, J. A. L. | |
dc.date.accessioned | 2023-02-23T15:57:19Z | - |
dc.date.available | 2023-02-23T15:57:19Z | - |
dc.date.created | 2023-02-23 | |
dc.date.issued | 2023 | |
dc.identifier.citation | Journal of Food Composition and Analysis, v. 116, 2023. | |
dc.identifier.uri | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1151891 | - |
dc.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. | |
dc.language.iso | por | |
dc.rights | openAccess | |
dc.subject | Amazonian robusta | |
dc.subject | Conilon | |
dc.subject | Geographical origin | |
dc.subject | Multivariate classification | |
dc.subject | NIR spectroscopy | |
dc.subject | PLS-DA | |
dc.title | Brazilian Canephora coffee evaluation using NIR spectroscopy and discriminant chemometric techniques. | |
dc.type | Artigo de periódico | |
riaa.ainfo.id | 1151891 | |
riaa.ainfo.lastupdate | 2023-02-23 | |
dc.contributor.institution | MICHEL ROCHA BAQUETA, UNICAMP; ENRIQUE ANASTACIO ALVES, CPAF-RO; PATRÍCIA VALDERRAMA, UTFPR; JULIANA AZEVEDO LIMA PALLONE, UNICAMP. | |
Aparece en las colecciones: | Artigo em periódico indexado (CPAF-RO)![]() ![]() |
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2023-01-Brazilian-Canephora-coffee-evaluation-using-NIR-spectroscopy-and-discriminant-chemometric-techniques-J.-Food-Composition-and-Analysis-116.pdf | 4.79 MB | Adobe PDF | ![]() Visualizar/Abrir |