Prediction accuracy of near infrared spectroscopy coupled with adaptive machine learning methods for simultaneous determination of chlorogenic acid and caffeine on intact coffee beans

Prediction accuracy of near infrared spectroscopy coupled with adaptive machine learning methods for simultaneous determination of chlorogenic acid and caffeine on intact coffee beans

Due to the inherent complexity and high dimensionality of near infrared spectroscopy (NIRS) data, it is critical to employ robust methods that can accurately interpret the spectroscopic signals to determine the concentration of chlorogenic acid (CGA) and caffeine on intact coffee beans. Therefore, t...

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Bibliographic Details
Main Authors: Agus Arip Munawar, Zulfahrizal, Daniel Mörlein
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Case Studies in Chemical and Environmental Engineering
Subjects:
NIRS
Machine learning
Prediction
Coffee beans
Calibration
Online Access:http://www.sciencedirect.com/science/article/pii/S2666016424003074

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http://www.sciencedirect.com/science/article/pii/S2666016424003074

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