چکیده (انگلیسی):

Estimating leaf stomatal conductance for CO2 diffusion (gsc) is pivotal for further estimation of crop transpiration as well as energy and mass balances between air and plant in greenhouses. In this study, we tested two models, i.e. the Jarvis model and a new version of BWB–Leuning model (BWB–Leuning–Yin model), for estimating gsc in four greenhouse crops (cucumber, chrysanthemum, tulip and lilium), using data from extensive experiments conducted under a wide range of environmental conditions from 2003 to 2010. The models were parameterized from a subset of the experimental data. The remaining data sets for model validation were classified into two groups: group one was from experiments conducted during the similar seasons at the same sites as those for model parameterization, whereas group two was from experiments in different seasons and sites. When using data of group one, both models gave satisfactory estimations of gsc under both ample water supply and water stress conditions. When using data of group two, the BWB–Leuning–Yin model gave better estimations of gsc than the Jarvis model did. Functions or parameters of the Jarvis model, if applied to independent environmental conditions, have to be re-derived. Compared to its earlier versions, the BWB–Leuning–Yin model gave better estimated gsc under low light intensities and low CO2 concentrations, suggesting that the new version is especially suitable for estimation of gsc for crops grown in low-investment greenhouses where levels of light and CO2 are lower than ambient levels. In addition, analytical algorithms for the coupled FvCB model and diffusional conductance as adopted in the BWB–Leuning–Yin model make parameterization and simultaneous estimation of net photosynthetic rate and gsc an easy task, using readily obtained information.