Flavoromics is an “-omic” and “-holistic” approach focused on low molecular mass compounds (volatile and non-volatile) and linking them to a defined sensorial perception, thanks to advanced chemometric techniques1-3. Flavor perception is the result of the interaction between different and complex chemical stimuli (ortho retro-nasal, taste, texture, etc.) and the (bio)chemical and physiological responses. Chemical information from coffee samples was obtained by analyzing both volatile and non-volatile profiles, followed by processing of the resulting chromatograms to reduce the number of variables with statistical tools. Multiple Factorial Analysis was used to study the relationship between the observations, (volatiles, non-volatiles, and sensory scores) and Partial Least Squares Regression analysis to correlate chemical data with well-defined flavor notes in a cup of coffee determined by monadic sensory analysis. Some variables were selected as diagnostic markers, because of their high impact on the statistical models developed. Bitter flavor markers different from caffeine were highlighted as well. The sensory contributions of these markers has been then determined by targeted analysis. 1. J. Charve, Chi Chen, A. D. Hegemanb and G. Reineccius. Flavour Fragr. J. 2011, 26, 429–440 2. I. Andujar-Ortiz, T. L. Peppard, G. Reineccius. In: The Chemical Sensory Informatics of Food: Measurement, Analysis, Integration. Chapter 21, pp 293–312. 3. I. Ronningen. PhD dissertation, 2016. http://hdl.handle.net/11299/180222

Flavoromics approach to describe the sensory properties of a cup of coffee

BRESSANELLO, DAVIDE;LIBERTO, Erica;SGORBINI, Barbara;CORDERO, Chiara Emilia Irma;RUBIOLO, Patrizia;BICCHI, Carlo
2017

Abstract

Flavoromics is an “-omic” and “-holistic” approach focused on low molecular mass compounds (volatile and non-volatile) and linking them to a defined sensorial perception, thanks to advanced chemometric techniques1-3. Flavor perception is the result of the interaction between different and complex chemical stimuli (ortho retro-nasal, taste, texture, etc.) and the (bio)chemical and physiological responses. Chemical information from coffee samples was obtained by analyzing both volatile and non-volatile profiles, followed by processing of the resulting chromatograms to reduce the number of variables with statistical tools. Multiple Factorial Analysis was used to study the relationship between the observations, (volatiles, non-volatiles, and sensory scores) and Partial Least Squares Regression analysis to correlate chemical data with well-defined flavor notes in a cup of coffee determined by monadic sensory analysis. Some variables were selected as diagnostic markers, because of their high impact on the statistical models developed. Bitter flavor markers different from caffeine were highlighted as well. The sensory contributions of these markers has been then determined by targeted analysis. 1. J. Charve, Chi Chen, A. D. Hegemanb and G. Reineccius. Flavour Fragr. J. 2011, 26, 429–440 2. I. Andujar-Ortiz, T. L. Peppard, G. Reineccius. In: The Chemical Sensory Informatics of Food: Measurement, Analysis, Integration. Chapter 21, pp 293–312. 3. I. Ronningen. PhD dissertation, 2016. http://hdl.handle.net/11299/180222
Fourth International Congress on Cocoa, Coffee and Tea
Torino
25-28 June 2017
Book of Abstract
92
92
Bressanello, Davide; Liberto, Erica; Sgorbini, Barbara; Cordero, Chiara; Rubiolo, Patrizia; Pellegrino, Gloria; Ruosi, Manuela R.; Bicchi, Carlo
File in questo prodotto:
File Dimensione Formato  
Poster Flavoromics.pdf

Accesso aperto

Descrizione: Pdf del Poster
Tipo di file: PDF EDITORIALE
Dimensione 6.86 MB
Formato Adobe PDF
6.86 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/1644954
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact