MSc-thesis abstract (submitted 11 June 2015):
The aim of this study was to investigate the effect of two different EC treatments that were applied during the first hours of the night in the root zone of a tomato crop, on the night time transpiration, energy consumption and crop production.
The experiments were carried out in the highly insulated Venlow greenhouse, in Bleiswijk, one in 2013 that was used as a control and the other in 2014, where two variable EC treatments were applied in the root zone of the plants. The results showed that there was not any significant effect of the different treatments on the crop transpiration during the night, although it was reduced by 32.3% but as a result of maintenance of high humidity inside the greenhouse during the whole night.
Additionally, transpiration during night time was simulated by the transpiration model of Stanghellini, as it was calibrated for the estimation of the night time transpiration and by training an artificial neural network (ANN), trained with the back propagation algorithm, under 5 different scenarios that represent different combinations of the input climate data. Simulation results by both model approaches showed reasonable estimations in the prediction of the night time transpiration. ANNs though, had a higher performance than the Stanghellini model in every scenario that was tested.