Dairy Aroma Release Modulated by Oral Mucin

Ten key milk fat-derived aroma compounds were analyzed for their interaction with salivary mucin. The dataset contains results from HS-SPME-GC–MS analysis, thermodynamic and spectroscopic data, and machine learning feature importance. Author Weizhe Wang published the study on figshare in April 2026.

Use Cases

• Predict aroma compound release inhibition percentage from molecular features like H-bond acceptors using support vector regression.
• Analyze relationships between compound class (aldehyde, ketone, lactone) and binding affinity to mucin.
• Model thermodynamic parameters of hydrophobic interactions and hydrogen bonds involving phenylalanine and tyrosine residues.
• Correlate spectroscopic data on mucin secondary structure changes with specific aroma compound binding.

Strengths

• Includes data for ten distinct aroma compounds across three chemical classes.
• Provides a maximum binding percentage measurement of 34.79 ± 9.63%.

Limitations

• Dataset size is very small at 15.6 KB, indicating limited scope and sample count.
• Contains only in vitro study data, lacking direct in vivo sensory validation.
• No column names or sample data are provided, limiting immediate usability.

Provenance

Source

Weizhe Wang via figshare.

Collection Method

Data gathered via headspace solid-phase microextraction-gas chromatography–mass spectrometry (HS-SPME-GC–MS) analysis.

Time Range

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Freshness

Last updated April 2026.

Geography

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