Claim · model-written summary
Temporal disaggregation increased overfitting risk with sample sizes below 300.
Zea maysNot reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“maize yields”
e1“with sample sizes below 300, temporal disaggregation increases the risk of overfitting”
Title
G. Varalakshmi Advances in Research 2026. doi:10.9734/air/2026/v27i41658
Other claims from this paper (7)
- Method / resource Statistical crop models performed reliably with at least 10–20 observations per predictor.
- Observation Simulated maize yields fluctuated between 15 and 65 q/ha across years.
- Association Maize yields were lower during rainfall deficits.
- Association Maize yields were higher with well-distributed precipitation.
- Recommendation The authors recommend adequate sample sizes and aggregation for reliable climate impact assessment.
- Recommendation The authors recommend improved climate data, adaptive agricultural practices, irrigation and cropping strategies.
- Recommendation The authors recommend integrating statistical models with advanced machine learning to improve predictive accuracy.