Detection of Chocolate Properties Using Near-Infrared Spectrophotometry †
Title
Detection of Chocolate Properties Using Near-Infrared Spectrophotometry †Date
2021Citation
Galdo, B.; Fernandez-Blanco, E.; Rivero, D. Detection of Chocolate Properties Using Near-Infrared Spectrophotometry. Eng. Proc. 2021, 7, 37. https://doi.org/10.3390/engproc2021007037
Abstract
[Abstract] Knowing the chemical composition of a substance provides valuable information about it. That is why numerous techniques have been developed to try to obtain it. One of them is the Near Infrared Spectrometry technique, a non-destructive technique that analyzes the electromagnetic spectrum in search of waves of a certain length. The aim of this project is to combine this technology with machine learning techniques to try to detect the presence of milk, as well as the level of cocoa present in an ounce of chocolate. This has given satisfactory results in both cases, so it is considered that the combination of these techniques offers great possibilities.
Keywords
Near infrared spectroscopy
Machine learning
Artificial neural networks
Intensity
Absorbance
Reflectance
Chocolate
Milk
Cocoa
Machine learning
Artificial neural networks
Intensity
Absorbance
Reflectance
Chocolate
Milk
Cocoa
Description
Presented at the 4th XoveTIC Conference, A Coruña, Spain, 7–8 October 2021.
Editor version
Rights
Atribución 3.0 España