Download Database Bundles
Our extensive food composition database contains only evidence-based data that can be traced back to its source. As a USDA-NSF funded research project, the data is presented as a free resource under the Apache-2.0 license.
How to Cite
Li, F., Youn, J., Xie, K., Chan, T., Gupta, P., Yoo, A., Gunning, M., Ni, K., & Tagkopoulos, I. (2026). A unified knowledge graph linking foodomics to chemical-disease networks and flavor profiles. npj Science of Food, 10(1), 33. https://doi.org/10.1038/s41538-025-00680-9
Bundles
| version | release date | summary | size | |
|---|---|---|---|---|
v4.11 | 2026-09-11 | Weekly update — 165 new associations (156 new food–chemical associations across 57 foods and 83 chemicals) from 56 new papers.
Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 1.00, recall 0.68, F1 0.81. | 53.6 MB | |
v4.10 | 2026-08-28 | Weekly update — 10 new associations (10 new food–chemical associations across 5 foods and 7 chemicals) from 7 new papers.
Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 1.00, recall 0.73, F1 0.84. | 53.6 MB | |
v4.9 | 2026-08-21 | Weekly update — 169 new associations (113 new food–chemical associations across 44 foods and 65 chemicals) from 49 new papers.
Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 0.99, recall 0.74, F1 0.85. | 53.6 MB | |
v4.8 | 2026-07-24 | Weekly update — 46 new associations (46 new food–chemical associations across 15 foods and 20 chemicals) from 25 new papers.
Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 1.00, recall 0.73, F1 0.84. | 53.6 MB | |
v4.7 | 2026-07-17 | Weekly update — 69 new associations (68 new food–chemical associations across 31 foods and 42 chemicals) from 35 new papers.
Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 1.00, recall 0.71, F1 0.83. | 53.5 MB | |
v4.6 | 2026-07-10 | Weekly update — 64 new associations (64 new food–chemical associations across 25 foods and 33 chemicals) from 22 new papers.
Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 1.00, recall 0.75, F1 0.86. | 53.5 MB | |
v4.5 | 2026-07-07 | Weekly update — 225 new food–chemical associations across 76 foods and 108 chemicals from 95 new papers.
Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 1.00, recall 0.72, F1 0.84. | 53.5 MB | |
v4.4 | 2026-06-27 | Weekly update — 78 new associations (78 new food–chemical associations across 32 foods and 48 chemicals) from 42 new papers. | 53.8 MB | |
v4.3 | 2026-06-19 | Weekly update — 136 new associations (107 new food–chemical associations across 40 foods and 56 chemicals) from 54 new papers. | 53.8 MB | |
v4.2 | 2026-06-12 | Weekly update — 359 new associations (308 new food–chemical associations across 52 foods and 152 chemicals) from 65 new papers.
Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 0.98, recall 0.69, F1 0.81. | 53.8 MB |
Weekly update — 165 new associations (156 new food–chemical associations across 57 foods and 83 chemicals) from 56 new papers. Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 1.00, recall 0.68, F1 0.81.
Weekly update — 10 new associations (10 new food–chemical associations across 5 foods and 7 chemicals) from 7 new papers. Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 1.00, recall 0.73, F1 0.84.
Weekly update — 169 new associations (113 new food–chemical associations across 44 foods and 65 chemicals) from 49 new papers. Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 0.99, recall 0.74, F1 0.85.
Weekly update — 46 new associations (46 new food–chemical associations across 15 foods and 20 chemicals) from 25 new papers. Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 1.00, recall 0.73, F1 0.84.
Weekly update — 69 new associations (68 new food–chemical associations across 31 foods and 42 chemicals) from 35 new papers. Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 1.00, recall 0.71, F1 0.83.
Weekly update — 64 new associations (64 new food–chemical associations across 25 foods and 33 chemicals) from 22 new papers. Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 1.00, recall 0.75, F1 0.86.
Weekly update — 225 new food–chemical associations across 76 foods and 108 chemicals from 95 new papers. Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 1.00, recall 0.72, F1 0.84.
Weekly update — 78 new associations (78 new food–chemical associations across 32 foods and 48 chemicals) from 42 new papers.
Weekly update — 136 new associations (107 new food–chemical associations across 40 foods and 56 chemicals) from 54 new papers.
Weekly update — 359 new associations (308 new food–chemical associations across 52 foods and 152 chemicals) from 65 new papers. Extraction quality (LLM-as-a-judge, 100 sample sentences): precision 0.98, recall 0.69, F1 0.81.
Versions prior to v4.0 are retired and no longer available for download.
About AIFS
The AI Institute for Next Generation Food Systems, or AIFS aims to meet growing demands in our food supply by increasing efficiencies using Al and bioinformatics spanning the entire system–from growing crops through consumption. We are dedicated to creating AI applications for a healthier, more sustainable planet from farm to fork.
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