ArboDroughtStress
Changes in climate and their impact on agricultural systems and rural economies are already evident. Tree productivity is inextricably tied to climate, in particular, the increased uncertainty regarding water management in arboriculture as recently reaffirmed by the extreme temperatures coupled to drought. Drought events and heat waves that are supposed to increase in frequency and intensity have increased the importance of knowing what to do. Moreover, we need to study how trees (fruit and ornamental) react to such climatic variability. This is particularly important under Mediterranean growing environments, which alter tree ecophysiology, especially during summer as a consequence of the combined effects of high light, high air temperature, high vapour pressure deficit and low rainfall. It is of vital importance to develop and adopt strategies to face drought–related risks, in order to secure the future supply of fruits, in a society with increasing population. With ArboDroughtStress, growers can monitor tree water status from anywhere, especially the stomata closure due to drought stress which limits photosynthesis and therefore tree productivity. It has a high precision of estimate and reduces data requirements (air temperature, vapour pressure deficit and net radiation) relative to other tools and can automate the irrigation.
Despite the multitude of sensors and DSSs currently available, estimating stomatal conductance and transpiration at orchard level remains a challenge. ArboDroughtStress is a validated model which applies a direct parameterization of the Penman–Monteith equation to compute diurnal courses of orchard canopy conductance (gc) from sap flow in sub-hour resolution for both day and night conditions.
Technology validated in lab.
Basic technological components are integrated to establish that they will work together. This is relatively “low fidelity” compared with the eventual system. Examples include integration of “ad hoc” hardware in the laboratory.
Basic technological components are integrated to establish that they will work together. This is relatively “low fidelity” compared with the eventual system. Examples include integration of “ad hoc” hardware in the laboratory.
Following the definition of TRL, we have tested the model in specific environments and tree species. There is still work to be done to validate the model and especially to use the IoT tools to provide the data on drought stress (stomata closure) very easy for farmer usage and linked to the automation of the irrigation system.
How does it work?
Sap flow sensors are installed in some trees within the plantation for monitoring purposes. A portable meteorological station measures net Radiation (Rn), air Temperature (Ta) and Relative Humidity (RH) of air. Atmospheric vapour pressure Deficit (D) is calculated from temperature and relative humidity. Our modeling approach is different as it uses diurnal courses of variables instead of commonly used daily means (see dattached paper for details of the model). The farmers can monitor the field conditions from anywhere, especially the stomata closure due to drought stress which limits photosynthesis and therefore tree productivity. The innovation is precise farming and is highly efficient when compared with the conventional approach.
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