光谱学与光谱分析 |
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Photosynthetic Parameters Inversion Algorithm Study Based on Chlorophyll Fluorescence Induction Kinetics Curve |
QIU Xiao-han1, 2, ZHANG Yu-jun1*, YIN Gao-fang1, SHI Chao-yi1, YU Xiao-ya1, ZHAO Nan-jing1, LIU Wen-qing1 |
1. Key Laboratory of Environment Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China 2. University of Science and Technology of China, Hefei 230026, China |
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Abstract The fast chlorophyll fluorescence induction curve contains rich information of photosynthesis. It can reflect various information of vegetation, such as, the survival status, the pathological condition and the physiology trends under the stress state. Through the acquisition of algae fluorescence and induced optical signal, the fast phase of chlorophyll fluorescence kinetics curve was fitted. Based on least square fitting method, we introduced adaptive minimum error approaching method for fast multivariate nonlinear regression fitting toward chlorophyll fluorescence kinetics curve. We realized Fo (fixedfluorescent), Fm (maximum fluorescence yield), σPSII (PSII functional absorption cross section) details parameters inversion and the photosynthetic parameters inversion of Chlorella pyrenoidosa. And we also studied physiological variation of Chlorella pyrenoidosa under the stress of Cu2+.
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Received: 2014-06-19
Accepted: 2014-10-15
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Corresponding Authors:
ZHANG Yu-jun
E-mail: yjzhang@aiofm.cas.cn
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[1] HAN Bo-ping, HAN Zhi-guo, FU Xiang(韩博平, 韩志国, 付 翔). Algal Photosynthesis: Mechanisms and Models(藻类光合作用机理与模型). Beijing: Science Press(北京:科学出版社), 2003. 6. [2] Stirbet A, Strasser B J, Govindjee, et al. Theor Biol., 1998, 193: 131. [3] SHI Chao-yi, ZHANG Yu-jun, YIN Gao-fang(石朝毅, 张玉钧, 殷高方, 等). Chinese Optics Litters, 2014, 12(8): 080101. [4] PANG Ju-feng(庞巨丰). Gamma Spectrometer Data Analysis(γ能谱数据分析). Xi’an: Shanxi Science and Technology Publishing House(西安:陕西科学技术出版社), 1990. [5] CHEN Lei, ZHENG Qing-song, LIU Zhao-pu, et al(陈 雷, 郑青松, 刘兆普, 等). Ecology and Environmental Sciences(生态环境学报), 2009, 18(4): 1231. |
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