Improving water use efficiency for ornamental crops grown in greenhouses: a substrate-plant-atmosphere model validation for transpiration prediction
In greenhouses, reducing water consumption by increasing water efficiency is of high interest. Water need is linked to the plant transpiration, which itself depends on the stomatal resistance (Rs). Up until now however, prediction of Rs through models was mainly conducted for well-watered plants in open field conditions and very few models exist for greenhouse plants grown in pots. The aim of this work was to develop a dynamic model of Rs based on the full factorial design (FFD) under water restriction conditions. Then, the model was validated inside a greenhouse. The FFD is based on an optimization process to establish a polynomial relationship between Rs and the radiation, humidity and temperature. To implement the model, a set of experiments was conducted inside a 10 m2 growth chamber equipped with Impatiens New Guinea planted in 0.74-L pots under well-watered conditions. Rs was measured with a porometer and nine climatic scenarios were tested. First the FFD model was implemented for well-watered conditions. Then it was adapted to calculate Rs under water restriction, through the introduction of a new multiplicative function depending on the growing media matric potential. Once these parameters had been determined, the obtained transpiration model was validated against experimental data recorded inside a greenhouse Impatiens crop. The transpiration model derived from the FFD method showed its ability to correctly simulate Rs under water restriction conditions. Hence, it could be useful to accurately predict the evolution of transpiration.
Cannavo, P., Bouhoun Ali, H., Chantoiseau, E. and Bournet, P.E. (2017). Improving water use efficiency for ornamental crops grown in greenhouses: a substrate-plant-atmosphere model validation for transpiration prediction. Acta Hortic. 1182, 161-168
irrigation, stomatal resistance, water restriction, New Guinea Impatiens, energy balance, matric potential