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© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Background: There is a continuous demand to create new, superior sensory food experiences. In the food industry, yeast-derived flavor products (YPs) are often used as ingredients in foods to create new aromas and taste qualities that are appreciated by consumers. Methods: Chicken bouillon samples containing diverse YPs were chemically and sensorially characterized using statistical multivariate analyses. The sensory evaluation was performed using quantitative descriptive analysis (QDA) by trained panelists. Thirty-four sensory attributes were scored, including odor, flavor, mouthfeel, aftertaste and afterfeel. Untargeted metabolomic profiles were obtained using stir bar sorptive extraction (SBSE) coupled to GC-MS, RPLC-MS and targeted HILIC-MS. Results: In total, 261 volatiles were detected using GC-MS, from chemical groups of predominantly aldehydes, esters, pyrazines and ketones. Random Forest (RF) modeling revealed volatiles associated with roast odor (2-ethyl-5-methyl pyrazine, 2,3,5-trimethyl-6-isopentyl pyrazine) and chicken odor (2,4-nonadienal, 2,4-decadienal, 2-acetyl furan), which could be predicted by our combined model with R2 > 0.5. In total, 2305 non-volatiles were detected for RPLC-MS and 34 for targeted HILIC-MS, where fructose-isoleucine and cyclo-leucine-proline were found to correlate with roast flavor and odor. Furthermore, a list of metabolites (glutamate, monophosphates, methionyl-leucine) was linked to umami-related flavor. This study describes a straightforward data-driven approach for studying foods with added YPs to identify flavor-impacting correlations between molecular composition and sensory perception. It also highlights limitations and preconditions for good prediction models. Overall, this study emphasizes a matrix-based approach for the prediction of food taste, which can be used to analyze foods for targeted flavor design or quality control.

Details

Title
A Data-Driven Approach to Link GC-MS and LC-MS with Sensory Attributes of Chicken Bouillon with Added Yeast-Derived Flavor Products in a Combined Prediction Model
Author
Leygeber Simon 1 ; Diez-Simon, Carmen 2 ; Großmann, Justus L 3 ; Anne-Charlotte, Dubbelman 1   VIAFID ORCID Logo  ; Harms, Amy C 1   VIAFID ORCID Logo  ; Westerhuis, Johan A 3   VIAFID ORCID Logo  ; Jacobs, Doris M 4 ; Lindenburg Peter W. 5 ; Hendriks Margriet M. W. B. 6   VIAFID ORCID Logo  ; Ammerlaan Brenda C. H. 6 ; van den Berg Marco A. 7   VIAFID ORCID Logo  ; van Doorn Rudi 7 ; Mumm, Roland 8   VIAFID ORCID Logo  ; Smilde Age K. 3 ; Hall, Robert D 9   VIAFID ORCID Logo  ; Hankemeier, Thomas 1   VIAFID ORCID Logo 

 Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands 
 Laboratory of Plant Physiology, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands 
 Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands 
 Unilever Foods Innovation Centre, Bronland 14, 6708 WH Wageningen, The Netherlands 
 Leiden Center for Applied Bioscience, University of Applied Sciences Leiden, Zernikedreef 11, 2333 CK Leiden, The Netherlands 
 Science & Research, DSM-Firmenich, Alexander Fleminglaan 1, 2613 AX Delft, The Netherlands 
 Taste, Texture & Health, DSM-Firmenich, Alexander Fleminglaan 1, 2613 AX Delft, The Netherlands 
 Wageningen Plant Research (Bioscience), Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands 
 Laboratory of Plant Physiology, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands, Wageningen Plant Research (Bioscience), Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands 
First page
317
Publication year
2025
Publication date
2025
Publisher
MDPI AG
e-ISSN
22181989
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3212076393
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.