指数改进模型在大麦光合-CO_2响应曲线中的适用性

Applicability of modified exponential model in photosynthetic-CO_2 response curve of barley

光合-CO2响应曲线是研究植物对CO2响应的重要工具。常用的光合-CO2响应曲线模型,除直角双曲线修正模型外,均无法准确地计算出CO2饱和点和光合能力。该文利用新的指数改进模型拟合大麦(Hordeum vulgare)光合-CO2响应曲线,与直角双曲线修正模型、直角双曲线模型、指数模型、非直角双曲线模型进行比较,并随机选取部分数据进行检验,同时得到了各个光合-CO2响应曲线模型的主要生理参数,对这些数据进行了比较分析,讨论了各模型之间的优缺点和准确合理性。结果表明,指数改进模型在5个模型中具有最好的精确度和合理性,能准确地描述出大麦的光合-CO2响应曲线,计算出CO2饱和点为484μmol·mol-1,光合能力为25.9μmolCO2·m-2·s-1。

Aims The photosynthetic-CO2 response curve is an important tool for understanding the response of plants to CO2. Common models of photosynthetic-CO2 response curve can not calculate the max net photosynthetic rate accurately. In our study, we used a new model called the modified exponential model to simulate the relationship between net photosynthetic rate and CO2 concentration of barley. We then compared the differences and accura- cies with the modified rectangular hyperbola model, rectangular hyperbola model, nonrectangular hyperbola model and exponential model. Our objectives were to test the merit and precision of these models and provide reference for selecting the best models for the photosynthetic-CO2 response curves of plants. Methods The CO2-response curves of Tibetan hulless barley were recorded with an infrared gas analyzer system （LI-6400）. The measured data were used to simulate and test the precision of the models. Mean square error （MSE） and mean absolute error （MAE） were used to evaluate the precision of the models. Some predicted physio- logical parameters of the four models were compared with the measured values. lmportantfindings The photosynthetic-CO2 response curves of barley were best described by the modified ex- ponential model. The CO2 saturation point and maximum net photosynthetic rate of barley obtained by the modi- fied exponential model were 25.9 μmol CO2·m^-2·s^-1 and 484 μmol·mol^-1, respectively. Key words Hordeum vulgare, modified exponential model, photosynthetic capacity, photosynthetic-CO2 response curve, saturation CO2 concentration