NIR hyperspectral imaging for predicting the composition of granular food commodities

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NIR hyperspectral imaging for predicting the composition of granular food commodities

Hyperspectral imaging (HSI) in the Near-Infrared (NIR) spectral range was applied for non- destructive characterisation of three staple food commodities: wheat, cocoa and coffee. Industrially-relevant properties such as moisture, fat and proteins were explored on a single seed basi...

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Bibliographic Details
Main Author:	Caporaso, Nicola
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2018
Subjects:	hyperspectral imaging food grains food quality NIR spectroscopy aroma prediction.
Online Access:	https://eprints.nottingham.ac.uk/52169/

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