Claim · model-written summary
PLS model predictions identified wheat genotypes potentially more susceptible to Septoria tritici blotch, confirmed by visual assessment.
- Taxon
- wheat
Triticum aestivume6 - Interactor
- Septoria tritici
Zymoseptoria triticie7pathogen - Outcome
- identification of wheat genotypes that are potentially more susceptible to STBe6
- Comparator
- STB visual assessmente6
Not reportedMaterialGeneCompoundOrgan / stageSecond interactorSecond interactor roleTreatmentSettingDirectionValueQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e6“allowed for the identification of wheat genotypes that are potentially more susceptible to STB, which was confirmed by the STB visual assessment”
e7“for detecting the Septoria tritici blotch (STB) disease”
Title
Hyperspectral Canopy Sensing of Wheat Septoria Tritici Blotch Disease
Kang Yu; Jonas Anderegg; Alexey Mikaberidze; et al. Frontiers in Plant Science 2018. doi:10.3389/fpls.2018.01195
Other claims from this paper (4)
- Method / resource The normalized difference water index performed best among spectral indices for detecting Septoria tritici blotch.
- Method / resource Canopy reflectance and spectral indices show promise for quantifying Septoria tritici blotch infection.
- Method / resource PLS regression improved the prediction of Septoria tritici blotch metrics.
- Method / resource The PLS discriminant analysis classified diseased and healthy wheat canopies with 93% accuracy (Kappa = 0.60).