|Authors: || Gang Li, Yongyi Dong, Dongsheng An, Shanxiang Yu, Qian Sun, Ningyi Zhang , Weihong Luo|
|Keywords: ||PAR, CO2 concentration, stomatal conductance, lilium, greenhouse, soil water potential, vapor pressure deficit|
Estimating leaf stomatal conductance for water vapour (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-type model (BWB-Leuning-Yin model), for estimating gsc in greenhouse lilium, using data from extensive experiments conducted under a wide range of environmental conditions from 2008 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 1 was from experiments conducted during the similar seasons at the same sites as those for model parameterization, whereas group 2 was from experiments in different seasons and sites.
When using data of group 1, both models gave satisfactory estimations of gsc under both ample water supply and water stress conditions.
When using data of group 2, 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.
The BWB-Leuning-Yin model gave better estimated gsc, suggesting that it is especially suitable for estimation of gsc for crops grown in climatic conditions corresponding to low-investment greenhouses.
In addition, analytical algorithms for the coupled stomatal conductance-biochemical photosynthesis model 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.
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