Method / resourcemodel-written summary

Multi-environment models more than doubled prediction accuracy relative to a single-environment model for most maize traits.

A claim from Genomic prediction of stalk lodging resistance and the associated intermediate phenotypes in maize using whole‐genome resequence and multi‐environmental data · 2025

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Multi-environment models more than doubled prediction accuracy relative to a single-environment model for most maize traits.

Taxon
maizeZea mayst0
Outcome
prediction accuracye0
Direction
more than doublede0
Value
more than doublede0
Qualifier
particularly when predicting lines in a sparse testing designe0
Comparator
single-environment modele0

Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentSetting

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

Zea mays
Zea mays · TaxonAkwugo · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

e0

“The multi-environment models more than doubled the prediction accuracy compared to the single-environment model for most traits, particularly when predicting lines in a sparse testing design”

✓ located verbatim in the source · abstract, characters 1005–1195
t0

“maize”

✓ located verbatim in the source · title, characters 93–98

Title

Genomic prediction of stalk lodging resistance and the associated intermediate phenotypes in maize using whole‐genome resequence and multi‐environmental data

Caique Machado e Silva; Bharath Kunduru; Norbert Bokros; et al. The Plant Genome 2025. doi:10.1002/tpg2.70125

Other claims from this paper (3)

Record rev-91dd3b571d8908c809345eacb27be790acc6703ef4a5a28e8dc46fc4d8f48da4 · schema claims-v0.9 · position 1 in the model’s answer