Caffeine Content Prediction in Coffee Beans Using Hyperspectral Reflectance and Machine Learning

Caffeine Content Prediction in Coffee Beans Using Hyperspectral Reflectance and Machine Learning

The application of hyperspectral data in machine learning models can contribute to the rapid and accurate determination of caffeine content in coffee beans. This study aimed to identify the machine learning algorithm with the best performance for predicting caffeine content and to find input data fo...

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Bibliographic Details
Main Authors: Dthenifer Cordeiro Santana, Rafael Felipe Ratke, Fabio Luiz Zanatta, Cid Naudi Silva Campos, Ana Carina da Silva Cândido Seron, Larissa Pereira Ribeiro Teodoro, Natielly Pereira da Silva, Gabriela Souza Oliveira, Regimar Garcia dos Santos, Rita de Cássia Félix Alvarez, Carlos Antonio da Silva Junior, Matildes Blanco, Paulo Eduardo Teodoro
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:AgriEngineering
Subjects:
support vector machine
spectroscopy
secondary metabolites
Online Access:https://www.mdpi.com/2624-7402/6/4/255
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