Relationship of potato water deficit diurnal variation and UAV-based vegetation indices

This study examines the assessment of crop water stress using UAVs, which is an important factor in the development of sustainable agriculture under conditions of water scarcity and climate variability. Traditional methods for assessing water resources status have limited spatial and temporal resolution, which hinders efficient irrigation. This paper utilizes multispectral UAV imagery to monitor the diurnal dynamics of water stress in potato crops to determine water scarcity. The study, conducted in a 600 m² experimental field, combines UAV data with direct sampling techniques. As a result, optimal vegetation indices were determined to differentiate field plots with different levels of water deficit.