Chin J Plan Ecolo ›› 2017, Vol. 41 ›› Issue (6): 693-706.doi: 10.17521/cjpe.2016.0283

• Reviews • Previous Articles    

A review on the FvCB biochemical model of photosynthesis and the measurement of A-Ci curves

LIANG Xing-Yun and LIU Shi-Rong*   

  1. Key Laboratory of Forest Ecology and Environment, China’s State Forestry Administration, Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China
  • Received:2016-09-09 Revised:2017-06-18 Online:2017-07-19 Published:2017-06-10
  • Contact: LIU Shi-Rong E-mail:liusr@caf.ac.cn

Abstract:

The biochemical model of photosynthesis proposed by Farquhar, von Caemmerer and Berry is a CO2 response model based on photosynthetic processes. It hypothesizes that leaf CO2 assimilation rate (A) of C3 plants is decided by the minimum of three biochemical processes: the carboxylation rate supported by ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco), the ribulose-1,5-bisphosphate (RuBP) regeneration rate supported by electron transport and the triose-phosphate (TP) use rate. Fitting leaf CO2 assimilation rate versus intercellular CO2 concentration (A-Ci) curves with the modified FvCB model could provide several important biochemical parameters, including maximum Rubisco carboxylation rate, maximum rate of electron transport, TP use rate, day respiration rate and mesophyll conductance. The FvCB model has greatly improved our understanding and prediction of plant photosynthetic physiology and its response to environmental changes. In this review, we firstly described the FvCB model, and analysed the characteristics of this model: segmentation and overparameterization. We reviewed the estimation of biochemical parameters which by fitting A-Ci curves with the FvCB model. The biochemical parameters were estimated previously by segmenting subjectively and fitting each limitation state separately, whereas now by segmenting objectively and fitting all limitation simultaneously. In comparison to the previously conventional ordinary least squares (OLS), terativgorithms (eg. Genetic Algorithm, Simulated Annealing Algorithm) based on the modern computer technology are now in common use. However, to further improve the reliability and the precision of the parameters estimation, more studies about Rubisco kinetics parameters and their temperature dependence are needed. In the end, to obtain efficient photosynthetic data for biochemical parameters estimation, we integrated and modified methods concerning the measurement of A-Ci curves according to current knowledge about FvCB model fitting. We expect this review would advance our understanding and application of the FvCB model and A-Ci curves.

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