Claim · model-written summary
The start decrease stage was highly correlated with yield in 2020 irrigated (r=0.53).
Triticum aestivumVerbatim
t0“winter wheat growth dynamics”
e4“the start decrease stage (SDS) was highly correlated with yield (r=0.53 in 2020 irrigated, p<0.001)”
Title
A double-sigmoid approach for high-throughput phenotyping of winter wheat growth dynamics
Shannon Baker; Lei Zhao; Jose Landivar Scott; et al. Smart Agricultural Technology 2026. doi:10.1016/j.atech.2026.101948
Other claims from this paper (12)
- Method / resource The double-sigmoid model captured canopy cover with high coefficients of determination above 0.99.
- Method / resource The double-sigmoid model had low root mean square error of 1.73 to 4.06 for canopy cover.
- Observation Genotypic effects were highly significant for yield, heading and Green Leaf Area Duration in all environments except 2020 dryland.
- Observation In the 2020 dryland environment, no significant differences among genotypes were detected.
- Association Extracted canopy parameters were positively correlated with agronomic traits, particularly under rainfed and stress-prone conditions.
- Association The end decrease stage was positively correlated with grain yield in 2019 dryland (r=0.56).
- Association The end decrease stage was positively correlated with grain yield in 2020 irrigated (r=0.53).
- Association The maximum decrease rate date was positively correlated with yield in 2019 dryland (r=0.55).
- Association Green Leaf Area Duration was correlated with yield in 2019 dryland (r=0.56).
- Association Green Leaf Area Duration was correlated with yield in 2020 irrigated (r=0.58).
- Recommendation The double-sigmoid model provides a non-invasive framework for quantifying canopy development, senescence timing and stress responses.
- Recommendation The approach enhances selection accuracy for stress-resilient winter wheat cultivars.