Discovery and Identification of Tastants and Taste-Modulating <i>N</i>-Acyl Amino Acid Derivatives in Traditional Korean Fermented Dish Kimchi Using a Sensomics Approach
Bibliographic record
Abstract
Sensory-guided fractionation by means of ultrafiltration and gel permeation chromatography followed by high-performance liquid chromatography, synthesis, liquid chromatography–tandem mass spectrometry (LC–MS/MS) quantitation, and taste re-engineering experiments revealed taste-active and taste-enhancing compounds contributing to the umami, mouthful and complex taste profile of the fermented Korean dish, kimchi. Besides basic taste-active compounds, in particular, various N-acylated amino acids deriving from succinic acid and lactic acid imparted taste-modulating properties in food matrices. Taste threshold concentrations were determined to evaluate intrinsic and modulating effects. Quantitation of N-acylated amino acids in kimchi following synthesis revealed the presence of numerous derivatives showing taste–active properties. Sensory evaluation including recombination and partial addition experiments highlighted that both the N-lactoyl- and the N-succinoyl amino acid derivatives contribute to increasing the fullness, volume, and complexity of food matrices, whereas the latter directly contributes to the overall taste of kimchi in natural concentrations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".