Data/hora: 10/06/2024 09:19:29

Biblioteca(s): | Embrapa Florestas.
Data corrente: | 19/07/2019
Data da última atualização: | 10/03/2021
Autoria: | LIMA, G. G. de; RUIZ, H. Z.; MATOS, M.; HELM, C. V.; LIZ, M. V. de; MAGALHAES, W. L. E.
Afiliação: | GABRIEL GOETTEN DE LIMA, Pós doutorando da UFPR; HENRIQUE ZAVATTIERI RUIZ, UTFPR; MAILSON MATOS, Doutorando da UFPR; CRISTIANE VIEIRA HELM, CNPF; MARCUS VINICIUS DE LIZ, UTFPR; WASHINGTON LUIZ ESTEVES MAGALHAES, CNPF.
Título: | Prediction of yerba mate caffeine content using near infrared spectroscopy.
Ano de publicação: | 2019
Fonte/Imprenta: | Spectroscopy Letters, v. 52, n. 5, p. 282-287, 2019.
DOI: | 10.1080/00387010.2019.1622567
Idioma: | Inglês
Conteúdo: | There is a commercial and beneficial interest of producing yerba mate leaves into different grades of caffeine. This work uses a handheld and bench near-infrared (NIR) spectroscopy to compare and predict, using partial least squares (PLS) regression, the amount of caffeine in yerba mate leaves. Standards of pure caffeine were compared, using high-performance liquid chromatography (HPLC), with extracts of yerba mate. The bench spectroscopy gave a strong confidence model of caffeine prediction, whereas the handheld related to a fair model. For first detection and initial separation of yerba mate in the field, the modeling proposed can be used to predict caffeine intensity.
Palavras-Chave: | x.
Categoria do assunto: | --
Registro original: | Embrapa Florestas (CNPF)
Exemplares: | CNPF - (56873-1) - UPC - AP - DD -  -  -  - DIS