Chocolate Quality Assessment Based on Chemical Fingerprinting Using Near Infra-red and Machine Learning Modeling

Chocolate Quality Assessment Based on Chemical Fingerprinting Using Near Infra-red and Machine Learning Modeling

Chocolates are the most common confectionery and most popular dessert and snack across the globe. The quality of chocolate plays a major role in sensory evaluation. In this study, a rapid and non-destructive method was developed to predict the quality of chocolate based on physicochemical data, and...

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Bibliographic Details
Main Authors: Thejani M. Gunaratne, Claudia Gonzalez Viejo, Nadeesha M. Gunaratne, Damir D. Torrico, Frank R. Dunshea, Sigfredo Fuentes
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Foods
Subjects:
sensory
physicochemical measurements
artificial neural networks
near infra-red spectroscopy
Online Access:https://www.mdpi.com/2304-8158/8/10/426

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https://www.mdpi.com/2304-8158/8/10/426

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