PREDICTING BIOMASS AND YIELD AT HARVEST OF SALT-STRESSED TOMATO PLANTS USING UAV IMAGERY

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1. Prediction of Carlson Trophic State Index of Small Inland Water from UAV-Based Multispectral Image Modeling C. Lin et al. 10.3390/app13010451
2. Prediction of plant-level tomato biomass and yield using machine learning with unmanned aerial vehicle imagery K. Tatsumi et al. 10.1186/s13007-021-00761-2
3. Under-Canopy Drone 3D Surveys for Wild Fruit Hotspot Mapping P. Trybała et al. 10.3390/drones8100577
4. UAV-g 2019: Unmanned Aerial Vehicles in Geomatics F. Nex 10.3390/drones3030074
5. Prediction of Strawberry Dry Biomass from UAV Multispectral Imagery Using Multiple Machine Learning Methods C. Zheng et al. 10.3390/rs14184511
6. Estimating the frost damage index in lettuce using UAV-based RGB and multispectral images Y. Liu et al. 10.3389/fpls.2023.1242948
7. Yield sensing technologies for perennial and annual horticultural crops: a review L. Longchamps et al. 10.1007/s11119-022-09906-2
8. A Tomato Fruit Biomass Prediction Model for Aquaponics System Using Machine Learning Algorithms P. Debroy & L. Seban 10.1016/j.ifacol.2022.04.116
9. Early Estimation of Tomato Yield by Decision Tree Ensembles M. Lillo-Saavedra et al. 10.3390/agriculture12101655
10. Temporal prediction and evaluation of Brassica growth in the field using conditional generative adversarial networks L. Drees et al. 10.1016/j.compag.2021.106415