Claim · model-written summary
ECa-based site-specific management is limited to cotton fields with high spatial variability and a strong association between yield and ECa patterns.
- Taxon
- Cotton
Gossypium hirsutumt0 - Outcome
- application of ECa for site-specific managemente1
- Qualifier
- limited to fields with high spatial variabilitye1
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionValue
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Irrigated Cotton Yield in the Southern High Plains”
e1“The application of ECa for site-specific management is limited to fields with high spatial variability and with a strong association between yield spatial and temporal patterns and ECa variation patterns”
Title
Spatial and Temporal Trends of Irrigated Cotton Yield in the Southern High Plains
Wenxuan Guo Agronomy 2018. doi:10.3390/agronomy8120298
Other claims from this paper (8)
- Observation Spatial and temporal cotton yield variability differed among fields.
- Association Fields with high ECa variability showed a stronger association between spatial and temporal yield patterns and ECa.
- Mechanism Soil properties related to ECa were major factors influencing cotton yield variability.
- Mechanism Spatial and temporal yield patterns in low-variability cotton fields might be more influenced by weather or other factors across seasons.
- Recommendation Fields with high spatial variability and a clear temporal stability pattern have great potential for long-term site-specific management of crop inputs.
- Recommendation For cotton fields with unstable yield, long-term management practices are difficult to implement.
- Recommendation For cotton fields with unstable yield patterns, within season site-specific management can be a better choice.
- Recommendation Variable rate application of water, plant growth regulators, nitrogen and harvest aids may be implemented based on spatial variability of crop growth conditions.