Treffer: Olfactometric process: new insights in automated acquisition and data treatment

Title:
Olfactometric process: new insights in automated acquisition and data treatment
Contributors:
Matrices Aliments Procédés Propriétés Structure - Sensoriel (GEPEA-MAPS2), Laboratoire de génie des procédés - environnement - agroalimentaire (GEPEA), Institut Universitaire de Technologie - Nantes (IUT Nantes), Université de Nantes (UN)-Université de Nantes (UN)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-Institut Universitaire de Technologie Saint-Nazaire (IUT Saint-Nazaire), Université de Nantes (UN)-Ecole Polytechnique de l'Université de Nantes (EPUN), Université de Nantes (UN)-École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut Universitaire de Technologie - La Roche-sur-Yon (IUT La Roche-sur-Yon), Université de Nantes (UN)-Institut Universitaire de Technologie - Nantes (IUT Nantes), Université de Nantes (UN), École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS), Data User Knowledge (LS2N - équipe DUKe), Laboratoire des Sciences du Numérique de Nantes (LS2N), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)
Source:
32nd EFFoST International Conference - Developing innovative food structures and functionalities through process and reformulation to satisfy consumer needs and expectations, Nov 2018, Nantes, France. 2018
Publisher Information:
CCSD, 2018.
Publication Year:
2018
Collection:
collection:UNIV-NANTES
collection:CNRS
collection:EC-NANTES
collection:UNAM
collection:LS2N
collection:LS2N-DUKE
collection:GEPEA
collection:AGREENIUM
collection:GEPEA-MAPS2
collection:INSTITUTS-TELECOM
collection:NANTES-UNIVERSITE
collection:UNIV-NANTES-AV2022
collection:NU-CENTRALE
collection:ONIRIS
Subject Geographic:
Original Identifier:
HAL: hal-01943996
Document Type:
Konferenz conferenceObject<br />Conference poster
Language:
English
Accession Number:
edshal.hal.01943996v1
Database:
HAL

Weitere Informationen

Olfactometry is a valuable methodology commonly used to investigate odorant active compounds in food aroma profiles. Considering the number of studies using this technique, little is done to improve olfactometric data acquisition, although it is essential for quality outcomes. Efforts were mainly done to automate recording of moment and duration of perceptions but their intensity and description are still often communicate orally, which disrupt judge’s breathing rhythm during analysis. Solutions that integrate intensity and description parameters recording, result in a multiple steps acquisition procedure, scarcely compatible with the transience of the perceptions evaluated during olfactometry experiment. This work aims to present an olfactometry dedicated software developed to simplify the user task, overcoming constraints and bias of existing systems, and associating data treatment capabilities. More specifically the WheelOscent software, coded with Java technologies, implements innovative components:- a data acquisition interface based on adaptable aroma wheels, which permits judges to characterize all parameters related to odors perceived, in a single and intuitive move (patented sensory system),- a data store, which stores collected data into adapted representation describing aroma wheels, experiments, products, judges, and aromagrams, - a data analysis interface, providing a direct and interactive visualization of data resulting from several processing such as data aggregation over judges. The WheelOstat module also provides a straight statistical comparison of aroma profiles.Assessment of the software was performed on food products with complex aroma such as wines or coffee. Providing a good usability for judges, it enables a precise aromatic characterization. Moreover, the statistical comparison module allows to point out singular features of products. Finally, judges take advantage of this wheel aroma presentation, already used for sensory characterization. This consistent presentation for olfactometric and sensory analysis facilitate approaches that attempt to determine contribution of compounds to an overall aroma and apprehend existing interactions.