Research on Control Strategy of Light and CO2 in Blueberry Greenhouse Based on Coordinated Optimization Model

As essential environmental parameters in the greenhouse, appropriate light and CO2 will improve agricultural productivity quality. Although many related studies have been carried out on intelligent regulation of these factors, is usually controlled separately, energy consumption rarely considered. This paper proposed a coordinated control strategy for greenhouse based multi-objective optimization model. Firstly, experiments net photosynthetic rate blueberry under different temperatures, photon flux density, concentration nesting were to establish prediction model Support Vector Regression (SVR). Secondly, calculating cost both was constructed. Thirdly, taking maximum minimum as objective functions, Non-dominated Sorting Genetic Algorithm (NSGA-II) leveraged obtain Pareto optimal solutions target values temperature ranges. Then, selected two strategies. Finally, this compared with classical threshold Gaussian curvature maximization strategy. The results indicated that which prioritized saving could reduce by about 22.33% 19.08%, respectively, premise consistent. Meanwhile, production efficiency increase 8.40% 4.42%, same cost. In conclusion, can climate performance other mentioned