Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractVariability of single bean coffee volatile compounds of Arabica and robusta roasted coffees analysed by SPME-GC-MS    Next AbstractPTR-MS Characterization of VOCs Associated with Commercial Aromatic Bakery Yeasts of Wine and Beer Origin »

Food Chem


Title:Prediction of coffee aroma from single roasted coffee beans by hyperspectral imaging
Author(s):Caporaso N; Whitworth MB; Fisk ID;
Address:"Division of Food Sciences, University of Nottingham, Sutton Bonington Campus, LE12 5RD, UK. Campden BRI, Chipping Campden, Gloucestershire GL55 6LD, UK. Division of Food Sciences, University of Nottingham, Sutton Bonington Campus, LE12 5RD, UK; The University of Adelaide, North Terrace, Adelaide, South Australia, Australia. Electronic address: Ian.Fisk@nottingham.ac.uk"
Journal Title:Food Chem
Year:2022
Volume:20210917
Issue:
Page Number:131159 -
DOI: 10.1016/j.foodchem.2021.131159
ISSN/ISBN:1873-7072 (Electronic) 0308-8146 (Print) 0308-8146 (Linking)
Abstract:"Coffee aroma is critical for consumer liking and enables price differentiation of coffee. This study applied hyperspectral imaging (1000-2500 nm) to predict volatile compounds in single roasted coffee beans, as measured by Solid Phase Micro Extraction-Gas Chromatography-Mass Spectrometry and Gas Chromatography-Olfactometry. Partial least square (PLS) regression models were built for individual volatile compounds and chemical classes. Selected key aroma compounds were predicted well enough to allow rapid screening (R(2) greater than 0.7, Ratio to Performance Deviation (RPD) greater than 1.5), and improved predictions were achieved for classes of compounds - e.g. aldehydes and pyrazines (R(2) approximately 0.8, RPD approximately 1.9). To demonstrate the approach, beans were successfully segregated by HSI into prototype batches with different levels of pyrazines (smoky) or aldehydes (sweet). This is industrially relevant as it will provide new rapid tools for quality evaluation, opportunities to understand and minimise heterogeneity during production and roasting and ultimately provide the tools to define and achieve new coffee flavour profiles"
Keywords:*Coffee Gas Chromatography-Mass Spectrometry Hyperspectral Imaging Odorants/analysis Seeds/chemistry *Volatile Organic Compounds/analysis Coffee aroma Coffee roasting Flavour development Hyperspectral chemical imaging Nirs Non-destructive assessment Quali;
Notes:"MedlineCaporaso, Nicola Whitworth, Martin B Fisk, Ian D eng England 2021/10/02 Food Chem. 2022 Mar 1; 371:131159. doi: 10.1016/j.foodchem.2021.131159. Epub 2021 Sep 17"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 27-12-2024