Understanding vineyards stress physiology from the leaf to the canopy: How do we accurately measure and scale 'true' ground observations?

Remote sensing techniques are commonly used to characterize spatial variability in water requirements across and within vineyards, and thus fine-tune irrigation. One approach is to use remotely sensed crop water stress index, which is related to water status based on "true" ground measures. Similarly, it has been proposed to monitoring plant responses to water stress through variable chlorophyll-a fluorescence from passive solar-induced fluorescence. Regardless of the technique, not much attention has been paid to how comparable ground measures are to those of remote sensors, which would be particularly important in complex canopies where leaves are exposed to a wide range of environmental conditions temporally. Independent of such variability, there are protocols for measuring water status at the leaf level. Existing sampling protocols (e.g. measuring leaf water potential on fully expanded, mature leaves exposed to direct solar radiation) aim for uniformity across time, fields, and species, however, such protocols misrepresent integrated responses at the canopy level. Here we describe our efforts within the GRAPEX (Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment) framework to link leaf and canopy level measurements to flux and remotely sensed energy balance data used to estimate evapotranspiration (ET) and crop stress. Preliminary results showed that shade and sun exposed leaves have distinct physiological responses to light, temperature and water stress, and consequently, an observational bias is imposed by standard measurement protocols. While reductions of up to 30 percent in irrigation translated into real ET decreases, physiological responses between control and water stress treatment only became evident under extreme environmental conditions (e.g., days of extreme heat) when following standard protocols. By combining a wide range of leaf, canopy, and remotely sensed measurements with multi-layer canopy models, we aim to provide insights on what and how should be performed measurements at the leaf and canopy level which are meant to provide physiologically sounded relationships for remotely sensed measurements and models.