Claim · model-written summary
The support vector machine model had significantly higher total accuracy.
Not reportedTaxonMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingValueQualifier
Verbatim
e4“the total accuracy was significantly higher, demonstrating the absence of chance prediction”
Title
Ernesto San‐Blas; Gabriel Paba; Néstor Cubillán; et al. Plant Pathology 2020. doi:10.1111/ppa.13246
Other claims from this paper (8)
- Observation Meloidogyne-infested tomato plants had different spectral patterns than uninfested plants.
- Observation Meloidogyne-infested guava plants had different spectral patterns than uninfested plants.
- Method / resource Principal component analysis diagnosed symptomless infested tomato plants after five weeks.
- Method / resource Principal component analysis diagnosed symptomless infested guava plants after eight weeks.
- Method / resource The support vector machine model achieved over 97% overall performance.
- Method / resource The best infestation prediction occurred in the second week for tomatoes, halving diagnostic time.
- Method / resource The best infestation prediction occurred in the fourth week for guavas, halving diagnostic time.
- Method / resource The combined techniques reduced processing time from field to laboratory and avoided root and soil sampling.