A ground-based mobile platform to measure and map canopy thermal indices in a nectarine orchard

Precise irrigation management tailored to plant water status (PWS) is paramount to sustain agriculture in a climate change and water scarcity scenario. Canopy temperature (Tc), delta temperature [dT = Tc − ambient temperature (Ta)] and crop water stress index (CWSI) can be used to describe PWS. This study aimed to test a mobile platform sensor system (Green Atlas Cartographer equipped with infrared temperature sensors) for rapid measurements of Tc (and derivation of dT and CWSI) in a nectarine orchard. The study was conducted on mature high-density ‘September Bright’ nectarine trees under four irrigation treatments – 100% of crop evapotranspiration (ETc), 40% ETc, 20% ETc and no irrigation (0% ETc). The orchard was scanned using Cartographer to measure Tc. A local weather station was used to obtain Ta and derive dT, and two methods were used to calculate CWSI – a more traditional approach that used the relationship between dT and VPD (CWSI-I) and a statistical approach that used the 99% prediction intervals of the relationship between Tc and VPD (CWSI-II). Correlations of Tc, dT, CWSI-I and CWSI-II with leaf water potential (Ψ_leaf) and irrigation treatments were tested. Tc, dT, CWSI-I and CWSI-II were found to be significantly inversely related to Ψ_leaf and irrigation treatments when measurements were obtained between 1300 and 1915 h (AEDT) at different dates. CWSI-II outperformed CWSI-I in describing a more realistic PWS gradient over time. Spatial maps of Tc revealed clear visual separations of deficit irrigation treatments. We contend that Tc can be used per se as a tool to assess spatial variability of PWS at single points in time when Tc measurements are taken over a relatively short timeframe where Ta and vapour pressure deficit can be considered constant. However, dT, CWSI-I and CWSI-II are the preferred indices of PWS for temporal comparisons between different days and/or times of the day. Our results confirm the suitability and utility of ground-based vehicles for fast and on-demand assessments of spatial and temporal variability of PWS in orchards.