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Kostas Test 2

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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.

Developed by Agricultural University of Tirana

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.

TRL4. Laboratory testing of prototype component or process
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. 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.

See more information about this level and the TRL and SRL levels.

Business plan completed

The BRIGAID Business Development Programme has been successfully completed. A MAF+ assessment has been conducted and its results have been enriched and incorporated into a business plan document.

The main components of the system have been tested separately, and an initial integration exercise has been conducted.

Credits
Collaborators

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.

Limitations/conditions under which this innovation does not work or is less effective

The model was tested in various environments within Albania, ranging from temperate to semi-arid (see attached paper), however there is a need to further test it in a wide range of environments. The model was tested on apple trees but it can be used to all other trees. Preliminary testing has been made also on olive trees. However, there is a need to test it further. Another limitation is related to the training system of the trees and the positioning of the sensors to capture the entire water status of the tree. The visual appraisal of the calibrated model output suggests the following observations that in all the cultivars and experiments, the output of complex P-M equation matches the seasonal pattern without any clear period of over– or underestimation, suggesting that in the climates where these experiments took place – this model accounts for the seasonal variability of transpiration. This implies that the capacity of this tool to predict when transpiration will increase over periods longer than a day (irrigation amounts are often calculated at a weekly or a monthly basis). However, it seems that short periods of low transpiration (associated to occasional cloudy days or in general transitory low evaporative demand) are sometimes cause of worse fit over the measured data.

Added value
Our model increases the precision of the estimate and reduces data requirements (air temperature, vapour pressure deficit and net radiation) relative to other models. Use of diurnal courses brings more details to the analysis of tree transpiration and canopy conductance and it satisfactorily shows the agreement between observed and simulated transpiration patterns. The sensitivity of canopy conductance to vapour pressure deficit in our model offers an approach to study stomata behaviour to environmental variables and agricultural practices. It is a promising tool for understanding of fruit tree behavior under drought environments, including the environmental and biological interactions that affect their productivity.

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