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Stomatal resistance modelling under water restriction conditions by means of design of experiments: comparison with the Jarvis method
Abstract : 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 and its performance was compared against the Jarvis model 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. Rs was measured with a porometer and nine scenarios were tested. First the FFD model was implemented for well-watered condition. 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 FFD model was validated against experimental data recorded inside a greenhouse Impatiens crop, and compared with the Jarvis model. The FFD showed its ability to correctly simulate Rs under water restriction conditions. Its main advantage is that just few data were enough to fit this model contrary to the Jarvis method and it provided even better results. Hence, it could be useful to accurately predict the evolution of transpiration.
https://hal-agrocampus-ouest.archives-ouvertes.fr/hal-01816704
Contributor : Catherine Cliquet <>
Submitted on : Friday, June 15, 2018 - 3:51:03 PM
Last modification on : Monday, July 6, 2020 - 3:38:30 PM
Contributor : Catherine Cliquet <>
Submitted on : Friday, June 15, 2018 - 3:51:03 PM
Last modification on : Monday, July 6, 2020 - 3:38:30 PM