UAVs challenge to assess water stress for sustainable agriculture

• Technological recent advances promote new reliable UAVs for precision agriculture.
• UAVs can improve temporal and spatial sensing resolutions for water stress management.
• Multi-spectral and thermal images from UAVs reflect water stress in several crop.
• Easy and low-cost retrieving chlorophyll fluorescence from UAVs is an important challenge.

Unmanned aerial vehicles (UAVs) present an exciting opportunity to monitor crop fields with high spatial and temporal resolution remote sensing capable of improving water stress management in agriculture. In this study, we reviewed the application of different types of UAVs using different remote sensors and compared their performance with ground-truth plant data. Several reflectance indices, such as NDVI, TCARI/OSAVI and PRInorm obtained from UAVs have shown positive correlations related to water stress indicators such as water potential (Ψ) and stomatal conductance (gs). Nevertheless, they have performed differently in diverse crops; thus, their uses and applications are also discussed in this study. Thermal imagery is also a common remote sensing technology used to assess water stress in plants, via thermal indices (calculated using artificial surfaces as references), estimates of the difference between canopy and air temperature, and even canopy conductance estimates derived from leaf energy balance models. These indices have shown a great potential to determine field stress heterogeneity using unmanned aerial platforms. It has also been proposed that chlorophyll fluorescence could be an even better indicator of plant photosynthesis and water use efficiency under water stress. Therefore, developing systems and methodologies to easily retrieve fluorescence from UAVs should be a priority for the near future. After a decade of work with UAVs, recently emerging technologies have developed more user-friendly aerial platforms, such as the multi-copters, which offer industry, science, and society new opportunities. Their use as high-throughput phenotyping platforms for real field conditions and also for water stress management increasing temporal and resolution scales could improve our capacity to determine important crop traits such as yield or stress tolerance for breeding purposes.