From Jenn's voice brief to 10-artefact research package — 56 food particles decomposed, 7 R&D experiments designed, 12 fusion dishes ranked, taste simulated across 6 personas. The first vertical run of the food-particle semantic framework.
Decomposed Jenn's v1 Harissa Mushroom recipe at molecular level. Found 3 combinatorial alphas (glutamate×GMP umami synergy at 30×, psyllium×soy gel-network at 2× hardness, koji×soy peptidoglutaminase lock). Predicted taste: 7.2/10 baseline · up to 9.5 umami with koji preferment. Surfaced 7 R&D experiments (RM 440 total program) and 12 fusion dishes (JP Curry Udon + Malay Nasi Lemak tied at 8.4/10 composite). Added HP variant designs that hit 25-35g protein per 100g while staying vegan.
| Ingredient pair | Non-linear lift | Mechanism |
|---|---|---|
| L-glutamate × 5'-GMP | +0.24 | T1R1/T1R3 cooperative binding → 30× perceived umami (Yamaguchi 1967) |
| Psyllium husk × Soy isolate | +0.22 | Interpenetrating arabinoxylan-protein gel — WHC +54%, gel strength ×2, adhesiveness ×6 |
| Koji × Soy isolate | +0.21 | Peptidoglutaminase locks free Glu in peptide chain before bitter peptides form |
| Rank | Dish | Composite | Price RM | Persona alpha |
|---|---|---|---|---|
| 1 | JP Curry Udon × Harissa Mushroom | 8.4 | 18-22 | Sara (urban Gen-Z) + James (gym banker) |
| 1 | Malay Nasi Lemak × Tempeh Variant | 8.4 | 16-20 | Auntie Wong + Hafiz (halal-strict fit) |
| 3 | KR Bibimbap × Quinoa Puff Variant | 8.3 | 22-28 | Gen-Z TikTok magnet |
| 4 | Maghrebi Couscous Tagine | 8.2 | 22-28 | Adult dinner, authenticity claim |
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Born from this pilot — the food-domain semantic framework is now a permanent skill capability.
| What | Where |
|---|---|
| Schema spec | skills/market-survey-deep-research/references/FOOD-PARTICLE-SEMANTICS.md |
| CLI mode | --vertical food --ingredient X |
| Skill bump | v1.3.0 → v1.4.0 |
| Reuse claim | Next ingredient deep-dive: 50-70% faster via citation + framework reuse |