Associationmodel-written summary

Daidzin was a major contributor to soybean phenotypic variation under drought.

A claim from Interpretable multi-omics machine learning reveals drought-driven shifts in plant-microbe interactions · 2026

Associationobservedoriginal resultmeasured

Claim · model-written summary

Daidzin was a major contributor to soybean phenotypic variation under drought.

Taxon
soybeanGlycine maxe1
Compound
daidzine0
Outcome
phenotypic variatione0
Qualifier
under drought stresse0

Not reportedMaterialGeneOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionValue

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Glycine max
Glycine max · TaxonPublic domain · Wikimedia Commons ↗

Verbatim

e0

“the isoflavone derivative, daidzin, and the drought-tolerant Candidatus Nitrosocosmicus, were major contributors to phenotypic variation, specifically under drought stress”

✓ located verbatim in the source · abstract, characters 991–1162
t0

“Interpretable multi-omics machine learning reveals drought-driven shifts in plant-microbe interactions”

✓ located verbatim in the source · title, characters 0–102
e1

“198 soybean accessions grown under both control and drought conditions”

✓ located verbatim in the source · abstract, characters 427–497

Title

Interpretable multi-omics machine learning reveals drought-driven shifts in plant-microbe interactions

Hayato Yoshioka; Pavla Debeljak; Soizic Prado; et al. Environmental Microbiome 2026. doi:10.1186/s40793-026-00883-x

Other claims from this paper (3)

Record rev-a2ec89790a2ef3c5278a6bd2b14f11e3cd81827af188c4df8c47e98c827e9ff6 · schema claims-v0.9 · position 2 in the model’s answer