UAV-Thermal imaging and agglomerative hierarchical clustering techniques to evaluate and rank physiological performance of wheat genotypes on sodic soil
Sumanta Das(The University of Queensland), Yash P. Dang(The University of Queensland), Scott Chapman(Dalhousie University), Armando Apan(University of Southern Queensland), Neal W. Menzies(Griffith University), Jack Christopher(The University of Queensland), Malini Roy Choudhury(The University of Queensland)
Cited by 44
Related Papers
Pheno-Copter: A Low-Altitude, Autonomous Remote-Sensing Robotic Helicopter for High-Throughput Field-Based Phenotyping
|Agronomy|2014|286
Unraveling the urban climate crisis: Exploring the nexus of urbanization, climate change, and their impacts on the environment and human well-being – A global perspective
|AIMS Public Health|2024|109
Spectral behaviour of salt-affected soils
|International Journal of Remote Sensing|1995|107
Water scarcity: A global hindrance to sustainable development and agricultural production – A critical review of the impacts and adaptation strategies
|Cambridge Prisms Water|2025|97
Evaluation of water status of wheat genotypes to aid prediction of yield on sodic soils using UAV-thermal imaging and machine learning
|Agricultural and Forest Meteorology|2021|63