ASSESSING CHANGES IN POTATO CANOPY CAUSED BY LATE BLIGHT IN ORGANIC PRODUCTION SYSTEMS THROUGH UAV-BASED PUSHBROOM IMAGING SPECTROMETER

12 citations as recorded by crossref.

1. Feasibility of Unmanned Aerial Vehicle Optical Imagery for Early Detection and Severity Assessment of Late Blight in Potato M. Franceschini et al. https://doi.org/10.3390/rs11030224
2. Progress in Research on Prevention and Control of Crop Fungal Diseases in the Context of Climate Change J. Zhou et al. https://doi.org/10.3390/agriculture14071108
3. Development and Validation of Methodology for Estimating Potato Canopy Structure for Field Crop Phenotyping and Improved Breeding F. de Jesus Colwell et al. https://doi.org/10.3389/fpls.2021.612843
4. Remote sensing and machine learning techniques for high throughput phenotyping of late blight-resistant tomato plants in open field trials F. de Oliveira Dias et al. https://doi.org/10.1080/01431161.2023.2192878
5. Potato Late Blight Detection at the Leaf and Canopy Level Using Hyperspectral Data C. Fernández et al. https://doi.org/10.1080/07038992.2020.1769471
6. A Review on the Use of Unmanned Aerial Vehicles and Imaging Sensors for Monitoring and Assessing Plant Stresses J. Barbedo https://doi.org/10.3390/drones3020040
7. Feasibility Study of Detection of Ochre Spot on Almonds Aimed at Very Low-Cost Cameras Onboard a Drone J. Martínez-Heredia et al. https://doi.org/10.3390/drones7030186
8. Evaluating Late Blight Severity in Potato Crops Using Unmanned Aerial Vehicles and Machine Learning Algorithms J. Duarte-Carvajalino et al. https://doi.org/10.3390/rs10101513
9. A review of remote sensing for potato traits characterization in precision agriculture C. Sun et al. https://doi.org/10.3389/fpls.2022.871859
10. Potato Late Blight Detection at the Leaf and Canopy Levels Based in the Red and Red-Edge Spectral Regions C. Fernández et al. https://doi.org/10.3390/rs12081292
11. Drones in Plant Disease Assessment, Efficient Monitoring, and Detection: A Way Forward to Smart Agriculture A. Abbas et al. https://doi.org/10.3390/agronomy13061524
12. A Systematic Review of Vegetation Indices for Potato Growth Monitoring and Tuber Yield Prediction from Remote Sensing A. Mukiibi et al. https://doi.org/10.1007/s11540-024-09748-7