Food Graph Sources Research
Status
Research completed 2026-04-10. SIGHI covers histamine well. Other categories need additional sources.
The Problem
The app’s 7-category system requires per-food severity data (low/medium/high) across all categories. No single source covers all 7. The SIGHI data already in the vault covers histamine-pathway mechanisms comprehensively but has gaps in salicylate, oxalate, FODMAP, lectin, glutamate, and capsaicin coverage.
Source Assessment
✅ Histamine — SIGHI (Already Have)
The SIGHI Food Compatibility List (2024-08-29 edition) is the gold standard for histamine-related food classification. Already extracted into the vault as structured markdown files.
Coverage: Histamine content, histamine liberators, DAO blockers, biogenic amines. Excellent.
Gap: SIGHI’s mechanism codes (H, H!, A, L, B) map to histamine sub-mechanisms, not to the other 6 categories. See Issue 6 SIGHI Category Mapping Gap.
🔶 FODMAP — Monash University
Monash maintains the largest laboratory-tested FODMAP database in the world (~450 foods, 900 serving sizes). They use a traffic light system (green/amber/red) with per-FODMAP-subtype breakdown (fructans, GOS, lactose, fructose, polyols).
Access problem: No public API or downloadable dataset. Data is locked inside the Monash FODMAP app ($8.99 AUD, iOS/Android). Monash explicitly states that food scanning by ingredients is insufficient because FODMAP levels depend on processing methods, not just ingredient lists. Foods must be laboratory-tested.
Workaround options:
- Manual extraction from the app for the top 50-100 foods relevant to the suspect food pool — labor-intensive but doable for MVP
- Use published FODMAP food lists from peer-reviewed papers (Monash publishes some in journals) as a lower-fidelity seed
- Community-sourced FODMAP lists exist but Monash warns these are often inaccurate
Recommendation: Purchase the app, manually seed the top 100 FODMAP-relevant foods for MVP. Treat as approximate (Monash’s traffic light → our low/medium/high mapping). Note: Monash’s FODMAP subcategories (fructans, GOS, lactose, fructose, sorbitol, mannitol) are more granular than our single “fodmap” category — consider whether the schema needs a subcategory field on food_category_memberships.
🔶 Salicylates, Amines, Glutamates — RPAH Elimination Diet Handbook
The Royal Prince Alfred Hospital (RPAH) handbook is the gold standard for food chemical classification — salicylates, amines, and glutamates. Also known as the FAILSAFE diet. Developed by Anne Swain, Velencia Soutter, and Robert Loblay at the RPAH Allergy Unit.
Coverage: Comprehensive food chemical charts categorizing foods as Low, Moderate, High, or Very High with per-chemical-type labels (S = salicylate, A = amine, G = glutamate).
Access: The handbook is a published book (ISBN 9780980616408, ~$30 AUD). No public API or downloadable dataset. The food charts are copyrighted.
Workaround options:
- Purchase the handbook and manually extract data for the top 100 foods
- Community-maintained lists exist (Cooking for Oscar, idealnutrition.com.au) but the RPAH handbook author warns these are often inaccurate
- Published research papers by Swain et al. contain some food chemical composition data
Recommendation: Purchase the handbook. Manually seed salicylate, amine, and glutamate severity for the top 100 foods. This single source covers 3 of our 7 categories.
Important note: The RPAH “amines” category overlaps significantly with SIGHI’s histamine/biogenic amines data. Need to reconcile: RPAH amines include tyramine, phenylethylamine, and other biogenic amines beyond histamine. For the app’s purposes, the SIGHI histamine data + RPAH amine data together provide comprehensive biogenic amine coverage.
✅ Oxalates — Harvard Oxalate Table
Harvard T.H. Chan School of Public Health publishes the gold-standard oxalate food composition table. Updated 2023/2024 with hundreds of foods and mg/serving measurements.
Access: Freely downloadable as an Excel spreadsheet (.xlsx) from:
https://hsph.harvard.edu/wp-content/uploads/2024/07/OXALATE-TABLE-1.xlsx
Also available: oxalate.org maintains a community database cross-referencing Harvard 2008, NUTTAB 2010, USDA 1984, and other sources for 750+ foods.
Quality note: Oxalate measurement is notoriously variable — different growing conditions, soil, and measurement techniques produce different numbers for the same food. Harvard is the most trusted single source, but the data should be treated as approximate.
Mapping: Harvard uses mg/serving with categories from “little to none” through “very high.” Map to our severity enum:
- Little to none / Low → no membership (or low if >2mg/serving)
- Medium → medium (1)
- High / Very High → high (2)
Recommendation: Download the Harvard .xlsx, write an import script, and seed directly. This is the easiest category to populate — the data is free, structured, and machine-readable.
🔴 Lectins — No Single Authoritative Source
Lectin data is fragmented. No equivalent of SIGHI or RPAH exists for lectins.
Available sources:
- Steven Gundry’s “The Plant Paradox” contains a lectin food list but is commercially motivated and not peer-reviewed
- USDA databases include some lectin content data for raw legumes
- Published research on specific lectins (PHA in kidney beans, WGA in wheat, SBA in soybeans) exists but is per-food, not a comprehensive database
Recommendation: Hand-curate the lectin category for MVP based on established food groups known to contain lectins: legumes (raw/undercooked), nightshades (tomatoes, peppers, eggplant, potatoes), grains (wheat, corn, rice bran), and dairy (A1 casein). Use a conservative severity scale — mark only the strongest evidence foods as “high.” Note the evidence tier caveat: lectin sensitivity evidence outside of acute toxicity is weaker than for other categories.
🔴 Capsaicin — Derives from Scoville Scale
Capsaicin content roughly tracks Scoville Heat Units (SHU), which are well-documented.
Mapping:
- Bell peppers (0 SHU) → low or no membership
- Mild peppers (100-2,500 SHU: poblano, Anaheim) → low
- Medium peppers (2,500-30,000 SHU: jalapeño, serrano) → medium
- Hot peppers (30,000+ SHU: cayenne, habanero, ghost) → high
Recommendation: Seed from any standard Scoville reference. This is a small category — maybe 20-30 foods. Manual entry is trivial.
Seeding Strategy for MVP
Phase 1: Core 100 foods (covers POC needs)
Manually seed the top 100 foods most likely to appear in the suspect food pool and daily meals. Sources per category:
| Category | Source | Format | Cost | Effort |
|---|---|---|---|---|
| Histamine | SIGHI (in vault) | Structured markdown | Free (done) | Import script |
| FODMAP | Monash app + published papers | Manual extraction | $9 | ~4 hours |
| Salicylate | RPAH handbook | Manual extraction | ~$30 | ~4 hours |
| Glutamate | RPAH handbook | Manual extraction | (same book) | ~2 hours |
| Oxalate | Harvard .xlsx | Spreadsheet | Free | Import script |
| Lectin | Hand-curated from literature | Manual | Free | ~2 hours |
| Capsaicin | Scoville references | Manual | Free | ~30 min |
Total estimated effort: ~15 hours of data entry + import script writing.
Phase 2: Expand to 300+ foods
After MVP validation, expand the food graph using the full SIGHI dataset (already extracted), full Harvard oxalate spreadsheet, and broader RPAH/Monash coverage.
Phase 3: Community contribution + verification
Allow users to flag foods with suspected category memberships. Require 3+ independent reports before adding to the graph. Cross-reference with published data where possible.
Schema Considerations
Two issues surfaced during this research:
1. FODMAP subcategories: Monash tracks 6 FODMAP subtypes (fructans, GOS, lactose, fructose, sorbitol, mannitol). Our schema has a single “fodmap” category. Consider adding a subcategory string to food_category_memberships — e.g. { food: "garlic", category: "fodmap", subcategory: "fructans", severity: "high" }. This preserves granularity without adding 6 top-level categories.
2. Mechanism field for histamine: See Issue 6 SIGHI Category Mapping Gap. Adding a mechanism enum (direct, liberator, blocker) to food_category_memberships enables the quality scorer to distinguish between histamine-containing foods and DAO-blocking foods without proliferating categories.
References
- README — existing SIGHI data and mapping documentation
- Issue 4 Food Knowledge Graph Coverage Beyond Histamine
- Sensitivity Categories — the 7 categories this data feeds
- Harvard oxalate table: https://hsph.harvard.edu/wp-content/uploads/2024/07/OXALATE-TABLE-1.xlsx
- oxalate.org — cross-referenced oxalate database (750+ foods)
- RPAH Elimination Diet Handbook (ISBN 9780980616408)
- Monash FODMAP app: https://www.monashfodmap.com/ibs-central/i-have-ibs/get-the-app/