Flavor Profiling Using Comprehensive Mass Spectrometry Analysis of Metabolites in Tomato Soups

Simon Leygeber; Justus L. Grossmann; Carmen Diez-Simon; Naama Karu; Anne Charlotte Dubbelman; Amy C. Harms; Johan A. Westerhuis; Doris M. Jacobs; Peter W. Lindenburg; Margriet M.W.B. Hendriks; Brenda C.H. Ammerlaan; Marco A. van den Berg; Rudi van Doorn; Roland Mumm; Robert D. Hall; Age K. Smilde; Thomas Hankemeier

doi:10.3390/metabo12121194

Flavor Profiling Using Comprehensive Mass Spectrometry Analysis of Metabolites in Tomato Soups

Simon Leygeber, Justus L. Grossmann, Carmen Diez-Simon, Naama Karu, Anne Charlotte Dubbelman, Amy C. Harms, Johan A. Westerhuis, Doris M. Jacobs, Peter W. Lindenburg, Margriet M.W.B. Hendriks, Brenda C.H. Ammerlaan, Marco A. van den Berg, Rudi van Doorn, Roland Mumm, Robert D. Hall, Age K. Smilde, Thomas Hankemeier^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

3 Citations (Scopus)

Abstract

Trained sensory panels are regularly used to rate food products but do not allow for data-driven approaches to steer food product development. This study evaluated the potential of a molecular-based strategy by analyzing 27 tomato soups that were enhanced with yeast-derived flavor products using a sensory panel as well as LC-MS and GC-MS profiling. These data sets were used to build prediction models for 26 different sensory attributes using partial least squares analysis. We found driving separation factors between the tomato soups and metabolites predicting different flavors. Many metabolites were putatively identified as dipeptides and sulfur-containing modified amino acids, which are scientifically described as related to umami or having “garlic-like” and “onion-like” attributes. Proposed identities of high-impact sensory markers (methionyl-proline and asparagine-leucine) were verified using MS/MS. The overall results highlighted the strength of combining sensory data and metabolomics platforms to find new information related to flavor perception in a complex food matrix.

Original language	English
Article number	1194
Journal	Metabolites
Volume	12
Issue number	12
DOIs	https://doi.org/10.3390/metabo12121194
Publication status	Published - Dec 2022

Keywords

chemometrics
food
GC-MS
LC-MS
metabolomics
sensory evaluation
tomato soup
yeast

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Leygeber, S., Grossmann, J. L., Diez-Simon, C., Karu, N., Dubbelman, A. C., Harms, A. C., Westerhuis, J. A., Jacobs, D. M., Lindenburg, P. W., Hendriks, M. M. W. B., Ammerlaan, B. C. H., van den Berg, M. A., van Doorn, R., Mumm, R., Hall, R. D., Smilde, A. K., & Hankemeier, T. (2022). Flavor Profiling Using Comprehensive Mass Spectrometry Analysis of Metabolites in Tomato Soups. Metabolites, 12(12), Article 1194. https://doi.org/10.3390/metabo12121194

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title = "Flavor Profiling Using Comprehensive Mass Spectrometry Analysis of Metabolites in Tomato Soups",

abstract = "Trained sensory panels are regularly used to rate food products but do not allow for data-driven approaches to steer food product development. This study evaluated the potential of a molecular-based strategy by analyzing 27 tomato soups that were enhanced with yeast-derived flavor products using a sensory panel as well as LC-MS and GC-MS profiling. These data sets were used to build prediction models for 26 different sensory attributes using partial least squares analysis. We found driving separation factors between the tomato soups and metabolites predicting different flavors. Many metabolites were putatively identified as dipeptides and sulfur-containing modified amino acids, which are scientifically described as related to umami or having “garlic-like” and “onion-like” attributes. Proposed identities of high-impact sensory markers (methionyl-proline and asparagine-leucine) were verified using MS/MS. The overall results highlighted the strength of combining sensory data and metabolomics platforms to find new information related to flavor perception in a complex food matrix.",

keywords = "chemometrics, food, GC-MS, LC-MS, metabolomics, sensory evaluation, tomato soup, yeast",

author = "Simon Leygeber and Grossmann, {Justus L.} and Carmen Diez-Simon and Naama Karu and Dubbelman, {Anne Charlotte} and Harms, {Amy C.} and Westerhuis, {Johan A.} and Jacobs, {Doris M.} and Lindenburg, {Peter W.} and Hendriks, {Margriet M.W.B.} and Ammerlaan, {Brenda C.H.} and {van den Berg}, {Marco A.} and {van Doorn}, Rudi and Roland Mumm and Hall, {Robert D.} and Smilde, {Age K.} and Thomas Hankemeier",

year = "2022",

month = dec,

doi = "10.3390/metabo12121194",

language = "English",

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journal = "Metabolites",

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Leygeber, S, Grossmann, JL, Diez-Simon, C, Karu, N, Dubbelman, AC, Harms, AC, Westerhuis, JA, Jacobs, DM, Lindenburg, PW, Hendriks, MMWB, Ammerlaan, BCH, van den Berg, MA, van Doorn, R, Mumm, R , Hall, RD, Smilde, AK & Hankemeier, T 2022, 'Flavor Profiling Using Comprehensive Mass Spectrometry Analysis of Metabolites in Tomato Soups', Metabolites, vol. 12, no. 12, 1194. https://doi.org/10.3390/metabo12121194

TY - JOUR

T1 - Flavor Profiling Using Comprehensive Mass Spectrometry Analysis of Metabolites in Tomato Soups

AU - Leygeber, Simon

AU - Grossmann, Justus L.

AU - Diez-Simon, Carmen

AU - Karu, Naama

AU - Dubbelman, Anne Charlotte

AU - Harms, Amy C.

AU - Westerhuis, Johan A.

AU - Jacobs, Doris M.

AU - Lindenburg, Peter W.

AU - Hendriks, Margriet M.W.B.

AU - Ammerlaan, Brenda C.H.

AU - van den Berg, Marco A.

AU - van Doorn, Rudi

AU - Mumm, Roland

AU - Hall, Robert D.

AU - Smilde, Age K.

AU - Hankemeier, Thomas

PY - 2022/12

Y1 - 2022/12

N2 - Trained sensory panels are regularly used to rate food products but do not allow for data-driven approaches to steer food product development. This study evaluated the potential of a molecular-based strategy by analyzing 27 tomato soups that were enhanced with yeast-derived flavor products using a sensory panel as well as LC-MS and GC-MS profiling. These data sets were used to build prediction models for 26 different sensory attributes using partial least squares analysis. We found driving separation factors between the tomato soups and metabolites predicting different flavors. Many metabolites were putatively identified as dipeptides and sulfur-containing modified amino acids, which are scientifically described as related to umami or having “garlic-like” and “onion-like” attributes. Proposed identities of high-impact sensory markers (methionyl-proline and asparagine-leucine) were verified using MS/MS. The overall results highlighted the strength of combining sensory data and metabolomics platforms to find new information related to flavor perception in a complex food matrix.

AB - Trained sensory panels are regularly used to rate food products but do not allow for data-driven approaches to steer food product development. This study evaluated the potential of a molecular-based strategy by analyzing 27 tomato soups that were enhanced with yeast-derived flavor products using a sensory panel as well as LC-MS and GC-MS profiling. These data sets were used to build prediction models for 26 different sensory attributes using partial least squares analysis. We found driving separation factors between the tomato soups and metabolites predicting different flavors. Many metabolites were putatively identified as dipeptides and sulfur-containing modified amino acids, which are scientifically described as related to umami or having “garlic-like” and “onion-like” attributes. Proposed identities of high-impact sensory markers (methionyl-proline and asparagine-leucine) were verified using MS/MS. The overall results highlighted the strength of combining sensory data and metabolomics platforms to find new information related to flavor perception in a complex food matrix.

KW - chemometrics

KW - food

KW - GC-MS

KW - LC-MS

KW - metabolomics

KW - sensory evaluation

KW - tomato soup

KW - yeast

U2 - 10.3390/metabo12121194

DO - 10.3390/metabo12121194

M3 - Article

AN - SCOPUS:85144690569

SN - 2218-1989

VL - 12

JO - Metabolites

JF - Metabolites

IS - 12

M1 - 1194

ER -

Flavor Profiling Using Comprehensive Mass Spectrometry Analysis of Metabolites in Tomato Soups

Abstract

Keywords

UN SDGs

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