Prediction of yerba mate caffeine content using near infrared spectroscopy

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. Stan...

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Bibliographic Details
Published in:	Spectroscopy letters Vol. 52; no. 5; pp. 282 - 287
Main Authors:	de Lima, Gabriel Goetten, Ruiz, Henrique Zavattieri, Matos, Mailson, Helm, Cristiane Vieira, de Liz, Marcus Vinicius, Magalhães, Washington Luiz Esteves
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 28-05-2019 Taylor & Francis Ltd
Subjects:	Caffeine High performance liquid chromatography Infrared spectroscopy liquid chromatography Near infrared radiation near-infrared spectroscopy Spectrum analysis yerba-mate
Online Access:	Get full text
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Summary:	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.
ISSN:	0038-7010 1532-2289
DOI:	10.1080/00387010.2019.1622567