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Developed by Fundación Cajamar

PrHo is a software for the estimation of greenhouse-grown crop water requirements and actual evapotranspiration based on the FAO model

TRL7. Integrated pilot system demonstrated
ProSystem prototype demonstration in operational environment. Prototype near or at planned operational system. Represents a major step up from TRL 6 by requiring demonstration of an actual system prototype in an operational environment. The software has been tested and validated in greenhouses experiments for the most typical crop growing cycles in the Almeria province (SE Spain).

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

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

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Collaborators

How does it work?

PrHo quantifies crop water requirements based on two sub-models: a) a reference evapotranspiration (ETo) sub-model, and b) a crop coefficients (Kc) sub-model. The ETo sub-model computes greenhouse ETo values using outside solar radiation estimates retrieved from a radiation model previously calibrated for local conditions. Outputs from this sub-model make possible to adjust the irrigation scheme to particular crop conditions, such as white washing. The Kc sub-model computes the temporal dynamics of Kc values along the growing period, from the sowing/planting to the effective full cover stages. as a function of thermal time retrieved from greenhouse air temperature measurements.

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

The modelling tool is crop-specific and needs to be calibrated for similar climate conditions. The current version has been locally-calibrated and validated for the most typical greenhouse crops in Almeria (SE Spain), but it is not still ready for less usual crop growing cycles (e.g. tomato and cucumber sown in spring) or other climate conditions.

Added value
PrHo quantifies crop water requirements using simple weather data based on the FAO approach with higher accuracy than other similar solutions based on a modified Penman-Monteith algorithm which usually underestimate water requirements during the winter period.

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