Claim · model-written summary
Soil organic matter content did not affect prediction models.
- Taxon
- potato
Solanum tuberosumt0 - Outcome
- prediction modelse0
- Direction
- did not affecte0
- Setting
- Soil organic matter contente0
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorValueQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Verbatim
e0“Soil organic matter content increased the yield significantly but did not affect the prediction models.”
t0“potato”
Title
In‐season potato yield prediction with active optical sensors
Ahmed A. Zaeen; Lakesh Sharma; Ahmed Jasim; et al. Agrosystems Geosciences & Environment 2020. doi:10.1002/agg2.20024
Other claims from this paper (6)
- Intervention effect 168 kg N ha −1 produced the maximum potato yield.
- Association Indices at the 16th and 20th leaf stages correlated significantly with tuber yield.
- Method / resource Multiple regression using NDVI and CI improved prediction accuracy and determination coefficient.
- Method / resource Exponential and linear models fit the data better.
- Association Soil organic matter content significantly increased potato yield.
- Recommendation The authors identify the 18th and 20th leaf stages as best for sensor prediction.