Data/hora: 02/06/2024 12:07:50

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