Raman spectroscopy performed using optical fibers, with excitation at 1064 nm and a dispersive detection scheme, was utilized to measure a selection of unifloral honeys produced in the Italian region of Calabria. The honey samples had three different botanical origins: chestnut, citrus, and acacia. A multivariate processing of the spectroscopic data enabled us to distinguish their botanical origin, and to build predictive models for quantifying important nutraceutic indicators, such as the main sugars and potassium. Furthermore, the Raman spectra of chestnut honeys were compared with the taste profile measured by an electronic tongue: A good correlation to a bitter-savory taste was obtained. This experiment indicates the excellent potential of Raman spectroscopy as a modern analytical tool for the nondestructive and rapid multi-component analysis of food quality indicators.

Dispersive Raman Spectroscopy for the Nondestructive and Rapid Assessment of the Quality of Southern Italian Honey Types

Mignani Anna Grazia;Ciaccheri Leonardo;Mencaglia Andrea Azelio;
2016

Abstract

Raman spectroscopy performed using optical fibers, with excitation at 1064 nm and a dispersive detection scheme, was utilized to measure a selection of unifloral honeys produced in the Italian region of Calabria. The honey samples had three different botanical origins: chestnut, citrus, and acacia. A multivariate processing of the spectroscopic data enabled us to distinguish their botanical origin, and to build predictive models for quantifying important nutraceutic indicators, such as the main sugars and potassium. Furthermore, the Raman spectra of chestnut honeys were compared with the taste profile measured by an electronic tongue: A good correlation to a bitter-savory taste was obtained. This experiment indicates the excellent potential of Raman spectroscopy as a modern analytical tool for the nondestructive and rapid multi-component analysis of food quality indicators.
2016
Istituto di Fisica Applicata - IFAC
Food products
labeling
pattern analysis
predictive models
Raman scattering
sugar
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/322259
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