Claim · model-written summary
Temporal precipitation variability was 0.17 to 3.40 mm·day−1.
- Taxon
- corn
Zea mays subsp. mayse1 - Outcome
- Median absolute deviation from a reference yeare0
- Value
- 0.17 to 3.40 mm·day−1e0
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Median absolute deviation from a reference year was 0.17 to 3.40 mm·day−1 (temporal/year-to-year variability)”
t0“crop yield”
e1“by corn and soybean phenological phase”
Title
M. R. O'Neal Purdue e-Pubs (Purdue University System) 2000
Other claims from this paper (10)
- Method / resource The best neural net had an overall yield prediction error of 11.9%.
- Method / resource Farm scale yield error was 10.9%.
- Method / resource County scale yield error was 10.5%.
- Method / resource State scale yield error was 7.9%.
- Observation Spatial precipitation variability among farm gauges was 0.25 to 1.73 mm·day−1.
- Observation Spatial variability was below temporal variability and frequently below 1 mm.
- Method / resource Simulated corn yield differed by 15.8% across precipitation sources.
- Method / resource Simulated yield differed from the long term mean by 21.5%.
- Observation The most profitable nitrogen strategy did not depend on precipitation data source.
- Observation Using the nearest NWS station was more profitable than measuring precipitation on site.