Claim · model-written summary
The developed monitoring model had the highest overall accuracy, 98%, among the compared methods.
- Taxon
- Wheat
Triticum aestivumt0 - Outcome
- overall accuracye0
- Direction
- higheste0
- Value
- 98%e0
FusariumNot reportedMaterialGeneCompoundOrgan / stageSecond interactorSecond interactor roleTreatmentComparatorSettingQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The results showed that the developed Fusarium head blight monitoring model achieved the highest overall accuracy of 98%”
t0“Wheat”
Title
Monitoring Wheat Fusarium Head Blight Using Unmanned Aerial Vehicle Hyperspectral Imagery
Linyi Liu; Yingying Dong; Wenjiang Huang; et al. Remote Sensing 2020. doi:10.3390/rs12223811
Other claims from this paper (4)
- Method / resource Red bands distinguished slight from severe Fusarium head blight infection in wheat canopies.
- Method / resource The modified chlorophyll absorption reflectance index was the best feature, with AUC 1.0 and standard deviation 0.0.
- Method / resource The improved BP neural network had the smallest difference between producer and user accuracy, indicating better stability.
- Method / resource UAV hyperspectral images can monitor Fusarium head blight in winter wheat.