Formation of taste-active amino acids, amino acid derivatives and peptides in food fermentations – A review
Open accessAbstract
Fermented foods are valued for their rich and complex odour and taste. The metabolic activity of food-fermenting microorganisms determines food quality and generates odour and taste compounds. This communication reviews the formation of taste-active amino acids, amino acid derivatives and peptides in food fermentations. Pathways of the generation of taste compounds are presented for soy sauce, cheese, fermented meats, and bread. Proteolysis or autolysis during food fermentations generates taste-active amino acids and peptides; peptides derived from proteolysis particularly impart umami taste (e.g. α-glutamyl peptides) or bitter taste (e.g. hydrophobic peptides containing proline). Taste active peptide derivatives include pyroglutamyl peptides, γ-glutamyl peptides, and succinyl- or lactoyl amino acids. The influence of fermentation microbiota on proteolysis, and peptide hydrolysis, and the metabolism of glutamate and arginine is well understood, however, the understanding of microbial metabolic activities related to the formation of taste-active peptide derivatives is incomplete. Improved knowledge of the interactions between taste-active compounds will enable the development of novel fermentation strategies to develop tastier, less bitter, and low-salt food products, and may provide novel and "clean label" ingredients to improve the taste of other food products.
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A fine balance between proteolysis and peptidolysis avoids bitterness formation in cheese.
“Also, a fine balance between proteolysis and peptidolysis avoids bitterness formation in the cheese (Zhao et al. 2016).”
From Optimizing the acceleration of Cheddar cheese ripening using response surface methodology by microbial protease without altering its quality features (2021) · cites this paper as Zhao et al. 2016
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Hogenboom, J. A., D’Incecco, P., Fuselli, F., & Pellegrino, L. (2017) · Food Analytical Methods · doi:10.1007/s12161-017-0876-4 · Cited by 38 · see citing works
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- Authors
- Zhao, C. J., Schieber, A., & Gänzle, M. G.
- Affiliations
- University of Alberta (CA)
- University of Bonn (DE)
- Corresponding author
- Gänzle, Michael G.
- Venue
- Food Research International
- Publisher
- Elsevier BV
- Published
- 2016-11
- Volume
- 89
- Issue
- Pt 1
- Pages
- 39-47
- ISSN
- 0963-9969 (ISSN-L)
- OpenAlex
- W2512514802
- Cited by
- 790
- References
- 129
- Citations by year
- 2026: 131 · 2025: 137 · 2024: 120 · 2023: 113 · 2022: 78 · 2021: 73 · 2020: 64 · 2019: 38 · 2018: 24 · 2017: 10 · 2016: 1
- FWCI
- 2.17
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Food Research International (publishedVersion)
- PubMed (publishedVersion)
- ERA: Education and Research Archive (University of Alberta)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Hydrolysis and Bioactive Peptides
- Health Sciences › Nursing › Nutrition and Dietetics › Biochemical Analysis and Sensing Techniques
- Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
- Keywords
- amino acid derivatives, food fermentation, fermented foods, umami taste, bitter taste, proteolysis, autolysis, soy sauce, cheese, fermented meat products, bread, γ-glutamyl peptides, glutamate metabolism, arginine metabolism, fermentation microbiota, low-salt foods, clean-label ingredients
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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