ABSTRACT: An array of quartz crystals coated with different room-temperature ionic liquids (RTILs) is proposed for the analysis of flavors by quartz crystal microbalance (QCM) measurements. Seven RTILs were adopted as sensing layers, all containing imidazolium or phosphonium cations, differing from one another in the length and branching of alkyl groups and neutralized by different anions. The array was at first applied to the analysis of 31 volatile organic compounds (VOCs), such as alcohols, phenols, aldehydes, esters, ketones, acids, amines, hydrocarbons and terpenes, chosen as representative components of a wide variety of food flavors. Multivariate data analysis by the principal component analysis (PCA) approach of the set of the corresponding responses led to separated clusters for these different chemical categories. To further prove the good performance of the RTIL-coated quartz crystal array as an “electronic nose”, it was applied to the analysis of headspaces from cinnamon samples belonging to different botanical varieties (Cinnamon zeylanicum and Cinnamon cassia). PCA applied to responses recorded on different stocks of samples of both varieties showed that they could be fully discriminated.

Room Temperature Ionic Liquids As Useful Overlayers for Estimating Food Quality from Their Odor Analysis by Quartz Crystal Microbalance Measurements

TONIOLO, Rosanna;DOSSI, Nicolo';BONTEMPELLI, Gino
2013-01-01

Abstract

ABSTRACT: An array of quartz crystals coated with different room-temperature ionic liquids (RTILs) is proposed for the analysis of flavors by quartz crystal microbalance (QCM) measurements. Seven RTILs were adopted as sensing layers, all containing imidazolium or phosphonium cations, differing from one another in the length and branching of alkyl groups and neutralized by different anions. The array was at first applied to the analysis of 31 volatile organic compounds (VOCs), such as alcohols, phenols, aldehydes, esters, ketones, acids, amines, hydrocarbons and terpenes, chosen as representative components of a wide variety of food flavors. Multivariate data analysis by the principal component analysis (PCA) approach of the set of the corresponding responses led to separated clusters for these different chemical categories. To further prove the good performance of the RTIL-coated quartz crystal array as an “electronic nose”, it was applied to the analysis of headspaces from cinnamon samples belonging to different botanical varieties (Cinnamon zeylanicum and Cinnamon cassia). PCA applied to responses recorded on different stocks of samples of both varieties showed that they could be fully discriminated.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/882513
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