RAPID IDENTIFICATION OF ABIOTIC STRESS (FROST) IN IN-FILED MAIZE CROP USING UAV REMOTE SENSING

11 citations as recorded by crossref.

1. A Review of Methods and Techniques for Detecting Frost on Plant Surfaces H. Song et al. 10.3390/agriculture11111142
2. Sun/Shade Separation in Optical and Thermal UAV Images for Assessing the Impact of Agricultural Practices C. Marais-Sicre et al. 10.3390/rs16081436
3. Evaluation of Climate Suitability for Maize Production in Poland under Climate Change A. Król-Badziak et al. 10.3390/su16166896
4. Insight of Unmanned Aerial Vehicles Accessing Ensemble Techniques C. Dabas 10.1007/s42979-021-00842-y
5. UAV remote sensing phenotyping of wheat collection for response to water stress and yield prediction using machine learning V. Sharma et al. 10.1016/j.stress.2024.100464
6. Using the Multiple-Sensor-Based Frost Observation System (MFOS) for Image Object Analysis and Model Prediction Evaluation in an Orchard S. Kim et al. 10.3390/atmos15080906
7. An enhanced chlorophyll estimation model with a canopy structural trait in maize crops: Use of multi-spectral UAV images and machine learning algorithm G. Singhal et al. 10.1016/j.ecoinf.2024.102811
8. A survey of image-based computational learning techniques for frost detection in plants S. Shammi et al. 10.1016/j.inpa.2022.02.003
9. Estimating the frost damage index in lettuce using UAV-based RGB and multispectral images Y. Liu et al. 10.3389/fpls.2023.1242948
10. Automatic freezing-tolerant rapeseed material recognition using UAV images and deep learning L. Li et al. 10.1186/s13007-022-00838-6
11. Phenotyping for heat stress tolerance in wheat population using physiological traits, multispectral imagery, and machine learning approaches N. Sharma et al. 10.1016/j.stress.2024.100593