Wei Zhenhua, Du Taisheng, Li Xiangnan, Fang Liang, Liu Fulai
Center for Agricultural Water Research in China, China Agricultural University, Beijing, China.
Department of Plant and Environmental Sciences, Faculty of Science, University of Copenhagen, Taastrup, Denmark.
Front Plant Sci. 2018 Apr 9;9:445. doi: 10.3389/fpls.2018.00445. eCollection 2018.
Stomatal conductance () and water use efficiency () of tomato leaves exposed to different irrigation regimes and at ambient CO ([CO], 400 ppm) and elevated CO ([CO], 800 ppm) environments were simulated using the "Ball-Berry" model (BB-model). Data obtained from a preliminary experiment (Exp. I) was used for model parameterization, where measurements of leaf gas exchange of potted tomatoes were done during progressive soil drying for 5 days. The measured photosynthetic rate () was used as an input for the model. Considering the effect of soil water deficits on , an equation modifying the slope () based on the mean soil water potential (Ψ) in the whole root zone was introduced. Compared to the original BB-model, the modified model showed greater predictability for both and of tomato leaves at each [CO] growth environment. The models were further validated with data obtained from an independent experiment (Exp. II) where plants were subjected to three irrigation regimes: full irrigation (FI), deficit irrigation (DI), and alternative partial root-zone irrigation (PRI) for 40 days at both [CO] and [CO] environment. The simulation results indicated that was independently acclimated to [CO] from . The modified BB-model performed better in estimating and , especially for PRI strategy at both [CO] environments. A greater could be seen in plants grown under [CO] associated with PRI regime. Conclusively, the modified BB-model was capable of predicting and of tomato leaves in various irrigation regimes at both [CO] and [CO] environments. This study could provide valuable information for better predicting plant adapted to the future water-limited and CO enriched environment.
利用“Ball-Berry”模型（BB模型）模拟了暴露于不同灌溉制度下，以及在环境CO₂浓度（[CO₂]，400 ppm）和高浓度CO₂（[CO₂]，800 ppm）环境中的番茄叶片气孔导度（gs）和水分利用效率（WUE）。从初步实验（实验I）获得的数据用于模型参数化，在该实验中，对盆栽番茄在土壤逐渐干燥5天期间的叶片气体交换进行了测量。测得的光合速率（Pn）用作模型的输入。考虑到土壤水分亏缺对gs的影响，引入了一个基于整个根区平均土壤水势（Ψ）修正斜率（m）的方程。与原始BB模型相比，修正后的模型在每个[CO₂]生长环境下对番茄叶片的gs和WUE都具有更高的预测能力。这些模型进一步用从独立实验（实验II）获得的数据进行了验证，在该实验中，植物在[CO₂]和[CO₂]环境下分别接受三种灌溉制度：充分灌溉（FI）、亏缺灌溉（DI）和交替部分根区灌溉（PRI），持续40天。模拟结果表明，WUE独立于gs适应[CO₂]浓度。修正后的BB模型在估算gs和WUE方面表现更好，特别是在两种[CO₂]环境下对PRI策略的估算。在与PRI制度相关的[CO₂]浓度下生长的植物中可以看到更高的WUE。总之，修正后的BB模型能够预测在[CO₂]和[CO₂]环境下各种灌溉制度下番茄叶片的gs和WUE。本研究可为更好地预测适应未来水分受限和CO₂浓度升高环境的植物WUE提供有价值的信息。
