应用生态学报2018，Vol.29Issue(2)：583-591,9.DOI:10.13287/j.1001-9332.201802.025
不同CO2浓度下大豆叶片的光合生理生态特性
Photosynthetic physio-ecological characteristics in soybean leaves at different CO2 concentrations
摘要
Abstract
The availability of CO2,a substrate for photosynthesis,affects the photosynthesis process and photosynthate production.Using the Li-6400-40B,we measured the photosynthetic electron transport rate and the photosynthetic light-response curves of soybean (Glycine max) leaves at different CO2 concentrations (300,400,500 and 600 μmol · mol-1).By fitting these parameters with a mechanistic model characterizing the light response of photosynthesis,we obtained a series of photosynthetic parameters,eco-physiological parameters,as well as the physical parameters of photosynthetic pigments.The results showed that the electronic use efficiency,maximum electron transport rate,and maximum net photosynthetic rate increased with the increase of CO2 concentration.The light compensation point and dark respiration rate decreased with the increase of CO2 concentration.In addition,the light-use efficiency and intrinsic (instantaneous) water-use efficiency increased with the increase of CO2 concentration,and their values differed significantly among different CO2 concentrations.There was no significant difference on the maximum carboxylation efficiency among different CO2 concentrations.Those results suggested that CO2 concentration could affect the primary light reaction of photosynthesis in soybean leaves,and thus higher CO2 concentration could decrease the minimum average lifespan of excitons at the lowest excited state,which would enhance the velocity of light energy transport and the use efficiency of photosynthetic electron flow.关键词
光响应机理模型/光能利用效率/水分利用效率/大豆/CO2浓度Key words
mechanistic model of light-response/light-use efficiency/water-use efficiency/soybean/CO2 concentration引用本文复制引用
叶子飘,康华靖,段世华,王怡娟..不同CO2浓度下大豆叶片的光合生理生态特性[J].应用生态学报,2018,29(2):583-591,9.基金项目
本文由国家自然科学基金项目(31560069)、江西省自然科学基金项目(20142BAB20402)和温州市重点科技创新团队项目(C20150008)资助 This work was supported by the Natural Science Foundation of China (31560069),the Natural Science Foundation of Jiangxi Province(20142BAB20402),and the Key Science and Technology Innovation Team Project of Wenzhou (C20150008). （31560069）
