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Testing two models for the estimation of leaf stomatal conductance in four greenhouse crops cucumber, chrysanthemum, tulip and lilium

文献类型： 外文期刊

作者： Li, Gang 1 ; Lin, Lu 1 ; Dong, Yongyi 1 ; An, Dongsheng 1 ; Li, Yongxiu 1 ; Luo, Weihong 1 ; Yin, Xinyou 2 ; Li, Wenwen 1 ;

作者机构： 1.Nanjing Agr Univ, Nation Engn & Technol Ctr Informat Agr, Nanjing 210095, Jiangsu, Peoples R China

2.Wageningen Univ, Dept Plant Sci, Ctr Crop Syst Anal, NL-6700 AK Wageningen, Netherlands

3.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

关键词： Stomatal conductance; Model; PAR; Ambient air CO2 concentration; Soil water potential; Vapor pressure difference

期刊名称：AGRICULTURAL AND FOREST METEOROLOGY （ 影响因子：5.734； 五年影响因子：5.964 ）

ISSN： 0168-1923

年卷期： 2012 年 165 卷

页码：

收录情况： SCI

摘要： Estimating leaf stomatal conductance for CO2 diffusion (g(sc)) 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 g(sc) 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 g(sc) under both ample water supply and water stress conditions. When using data of group two, the BWB-Leuning-Yin model gave better estimations of g(sc) 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 g(sc) under low light intensities and low CO2 concentrations, suggesting that the new version is especially suitable for estimation of g(sc) 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 g(sc) an easy task, using readily obtained information. (c) 2012 Elsevier B.V. All rights reserved.

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