Repository logo
Log In(current)
  1. Home
  2. Prodotti della ricerca
  3. A. Contributo su rivista
  4. A1. Articolo in rivista
  5. E-Senses, Panel Tests and Wearable Sensors: A Teamwork for Food Quality Assessment and Prediction of Consumer’s Choices

E-Senses, Panel Tests and Wearable Sensors: A Teamwork for Food Quality Assessment and Prediction of Consumer’s Choices

Author(s)
Modesti, Margherita  
Tonacci, Alessandro
Sansone, Francesco
Billeci, Lucia
Bellincontro, Andrea  
more
Date Issued
2022
Type
article
Volume
10
Issue
7
DOI
https://doi.org/10.3390/chemosensors10070244
Journal
CHEMOSENSORS  
Abstract
At present, food quality is of utmost importance, not only to comply with commercial regulations, but also to meet the expectations of consumers; this aspect includes sensory features capable of triggering emotions through the citizen’s perception. To date, key parameters for food quality assessment have been sought through analytical methods alone or in combination with a panel test, but the evaluation of panelists’ reactions via psychophysiological markers is now becoming increasingly popular. As such, the present review investigates recent applications of traditional and novel methods to the specific field. These include electronic senses (e-nose, e-tongue, and e-eye), sensory analysis, and wearables for emotion recognition. Given the advantages and limitations highlighted throughout the review for each approach (both traditional and innovative ones), it was possible to conclude that a synergy between traditional and innovative approaches could be the best way to optimally manage the trade-off between the accuracy of the information and feasibility of the investigation. This evidence could help in better planning future investigations in the field of food sciences, providing more reliable, objective, and unbiased results, but it also has important implications in the field of neuromarketing related to edible compounds.
Handle
http://hdl.handle.net/2067/48151
File(s)
Thumbnail Image
Name

chemosensors-10-00244-v2.pdf

Description
articolo open access
Size

1.09 MB

Format

Adobe PDF

Checksum (MD5)

708c56080e9abb91dc389ecf1f05293c

Metrics

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Accessibility settings
  • Privacy policy
  • End User Agreement
  • Send Feedback
Repository logo COAR Notify