Abstract:CO2 is one of the main resources for plant photosynthesis. The slope of CO2 response curve represents the effect of CO2 concentration on photosynthetic rate. The first curvature maximum point represents the characteristic point where the effect of CO2 concentration on photosynthetic rate becomes weak. Therefore, the acquisition of this point is the key to realize the optimal benefit control of CO2. A CO2 optimal control model based on discrete curvature algorithm was proposed. Firstly, a photosynthetic rate experiment was designed. The subject of the experiment was tomato. The experimental conditions were the different combinations of temperature, photonic flux density and CO2 concentration. In the experiment, temperature, photon flux density and CO2 concentration gradients were set as 6, 10 and 20, respectively. Totally 1200 sets of CO2 response data were obtained by LI-6800 portable photosynthetic rate instrument. And 80% data were used to construct photosynthetic rate prediction model based on the support vector regression, and the rest of the data were used for model verification. Then, the CO2 response curves under the nested conditions were obtained by using the established photosynthetic rate prediction model. Next, the discrete curvature value of every response curve was calculated by the L-chord discrete curvature algorithm. Using hill-climbing method, the maximum curvature value of every response curve was obtained. The CO2 concentrations corresponding to the maximum curvature values were taken as the control target values. Finally, the CO2 optimal control model was constructed based on the support vector regression. The results showed that the decision coefficient of the control model was 0.99, the mean square error was 4.42μmol/mol, and the average absolute error was 3.17μmol/mol. Compared with the CO2 saturation point, the CO2 demand was decreased by 61.81%, but the photosynthetic rate was decreased by 15.58%. In the verification experiment, compared with the saturation point regulation, the average photosynthetic rate was decreased by 15.14% by using the proposed regulation method, the supply of CO2 was decreased by 57.61%. Compared with the natural method without any regulation, the photosynthetic rate was increased by 26.70% with the regulation proposed method. This indicated that the CO2 optimization control model was of high efficiency and energy saving. This control model could provide theoretical basis for efficient and precise regulation of CO2 for facility crops.
