A 400-record sample of the USDA Dr. Duke's Phytochemical and Ethnobotanical Database, denormalized into a flat 16-column schema and enriched with quantitative signals and structural identifiers. Enrichment Sources: pubmed_mentions_2026: PubMed publication count per compound clinical_trials_count: ClinicalTrials.gov v2 study count per compound chembl_bioactivity_count: ChEMBL v35 bioassay data points (CC BY-SA 3.0) patent_count: USPTO patents since 2020-01-01 (Patent-Literature Gap Analysis) pubchem_cid + canonical_smiles + inchi_key: PubChem compound identifiers and structural notations Schema (16 Columns): plant_id, plant_species, common_name, chemical, activity, reference, pubchem_cid, canonical_smiles, patent_count, patent_count_method, compound_type, clinical_trials_count, partner_cid, inchi_key, iupac_verified, partner_match_method Records: 400 (top compounds by PubMed mentions). Total dataset: 76,907 records across 24,746 compounds and 2,313 species. Full dataset available at: https://ethno-api.com Formats: JSON (~41 MB full dataset) + Parquet (~1.3 MB full dataset, Snappy compression). Methodology: https://github.com/wirthal1990-tech/USDA-Phytochemical-Database-JSON/blob/main/METHODOLOGY.md Changes in v2.4.0 vs v2.3.1: Integrated an expert-reviewed crossmatch pipeline leveraging structural mappings against COCONUT and FooDB. Expanded the schema from 12 to 16 columns to include partner_cid, inchi_key, iupac_verified, and partner_match_method. Recovered an additional 1,534 PubChem CIDs, reducing the Null-CID rate by a further 8% (now 17,616 missing). Introduced InChIKey structural identifiers (157 entries) and IUPAC nomenclature verification (459 entries).