Precision monitoring of vine water stress using UAVs and open-source processing chains

Abstract

This work aimed to evaluate the potential of visible-near-infrared (VNIR) and thermal infrared (TIR) imagery, acquired from an unmanned aerial vehicle (UAV), to detect vine water status. Three irrigation treatments were designed to impose weekly evapotranspiration (ET) to KC=0.2, KC=0.4 and KC=0.8 of reference ET. In situ leaf area index (LAI) and midday leaf (ΨLeaf) and stem water potential were collected during seven UAV overpasses. TIR-based temperature correlated highly with the water status variability observed between treatments (ΨLeaf: r=-0.68). However, VNIR indices were less correlated with ΨLeaf (r<0.4), revealing the importance of TIR imaging to capture the vine physiological response to water stress, with foliage differences being less apparent between treatments.