Read the burn as a moving blend, not a single SHU number. Select up to six peppers in the frozen menu. Their individual curves and the non-linear net blend are displayed together, while formulation ingredients in Interaction Lab reshape the final event.
The burn right now
What is being modelled?
| Ingredient dose | — |
|---|---|
| Midpoint SHU | — |
| Estimated capsaicinoid equivalent | — |
| Processing concentration factor | — |
| Model uncertainty | — |
Mouth heat map
Heat fingerprint
Capsaicinoid profile
Dose–response surface
What matters in this scenario
Heat and flavour are deliberately separated. A hotter pepper is not automatically more aromatic, fruitier or more useful. Processing can intensify dry-mass pungency while stripping fresh volatiles, or create entirely new smoky, roasted and fermented notes.
Flavour architecture
Descriptor field
Top · core · base
Sensory release through time
Volatile/aroma markers
Food & beverage uses
Pairing directions
Processing is not a cosmetic label. Moisture loss changes dose-on-a-mass-basis, heating can cause loss or greater extractability, smoking adds powerful phenolic notes, and fermentation rebalances acids, esters, alcohols and aldehydes. The direction is often predictable; the exact magnitude is process-specific.
Fresh, dried, smoked, roasted, fermented & extracted
Processing impact on the heat curve
Transformation report
Brine, time & temperature
Expected sensory trajectory
“Enhances heat” is not one mechanism. Some ingredients potentiate TRPV1, some add an independent oral irritation, some improve dispersion, and others suppress or mask the burn. Acid, vinegar and salt are therefore treated cautiously rather than hard-coded as universal enhancers.
Chemesthetic co-ingredients
Shape the product around the pepper blend
The atlas is built for selection, not trivia. Filter by species, practical heat class and dominant flavour family, then set Pepper 1 or add a selection to the next available blend slot.
Pepper atlas
This is a transparent comparative model. Reference-backed elements, model assumptions and user calibration are kept visible so the dashboard does not create false analytical precision.