High-throughput phenotyping of fire blight disease symptoms using sensing techniques in apple

Keyphrases

• Disease Symptoms 100%
• Apple 100%
• High-throughput Phenotyping 100%
• Sensing Technique 100%
• Fire Blight Disease 100%
• Visible-infrared 66%
• Near-infrared Spectrum 50%
• Spectral Reflectance 50%
• Disease Severity 50%
• Multispectral Imaging 33%
• Multispectral Image 33%
• Breeding Program 33%
• Spectral Bands 33%
• Stomatal Conductance 33%
• Apple Breeding 33%
• Reflectance Data 33%
• Fire Blight 33%
• Severity Rating 33%
• Normalized Difference Spectral Index 33%
• United States 16%
• Disease Diagnosis 16%
• Production System 16%
• Unmanned Aerial Systems 16%
• Multispectral Camera 16%
• Classification Accuracy 16%
• Two-field 16%
• Sensing System 16%
• Detection Device 16%
• New Cultivar 16%
• Hyperspectral Sensing 16%
• Image Data 16%
• High Correlation 16%
• Washington State 16%
• Disease Score 16%
• RGB Image 16%
• Partial Least Squares Regression 16%
• Imaging Sensor 16%
• RGB-D Camera 16%
• System Image 16%
• Early Fire 16%
• Apple Tree 16%
• Regression Support Vector Machine 16%
• Multiple Season 16%
• RGB Imaging 16%
• Photosynthetic System 16%
• Fresh Market Apple 16%
• Hyperspectral System 16%
• Near Infrared Reflectance Spectra 16%
• Quadratic Support Vector Machine 16%
• Young Apple Tree 16%

Chemistry

• Conductance 100%
• IR Reflectance Spectrum 50%
• Photosynthesis 50%

Agricultural and Biological Sciences

• Blight 100%
• Stomatal Conductance 25%
• Cultivar 12%
• Least Square 12%
• Support Vector Machine 12%
• Photosystem 12%