封闭式基质栽培日光温室环境最优调控与管理策略

China solar greenhouse has made a great development since it has better properties on daylighting, insulation, and energy-saving. On the other hand, it also has some bottleneck problems to limit its sustainable development, such as continuous cropping obstacles, fertility degradation and pollution of soil, low water and nutrient management. Hence, it is very important to conduct the research on optimal strategy of environmental control and cultivating management to China solar greenhouse with closed soilless cropping system. In this project, tomato is selected as a research object and planted in the closed soilless solar greenhouse. The objectives of the research are the optimal control methods and strategies of environmental factors, the optimal control methods and strategies of nutrient solution and CO2 fertilizer supply, the deployment scenarios and the data fusion methods of sensor nodes. First, the dynamic model of environmental factors and the supply model of crop nutrients and CO2 fertilizer will be built taking into account all environmental factors and nutritional supplements. And then, the models will be optimized and simplified by the decoupled computing, data mining and data fusion, and linear/nonlinear dimensionality reduction operation. Finally, through the optimization of the sensor node deployment scenarios, the optimal strategy of environmental control and cultivating management to solar greenhouse with closed soilless cropping system will be established. This project will promote the healthy and sustainable development of China solar greenhouse.

针对日光温室连作障碍、土壤肥力退化和污染、水肥管理和温室群管理水平低等影响可持续性发展的瓶颈问题，采用封闭式基质栽培模式，开展"封闭式基质栽培日光温室环境最优调控与管理策略"研究,研究成果将具有重要的科学意义和应用前景。本项目选择番茄作为研究对象，主要开展：封闭式基质栽培日光温室环境因子最优调控策略与方法研究、封闭式基质栽培日光温室营养液及CO2气肥循环补给最优控制策略与方法研究、以及封闭式基质栽培日光温室集群管理物联网节点部署方案和数据融合方法研究。首先在充分考虑各种环境因子和营养补给方案的基础上，建立温室环境因子动态模型和作物生长营养素补给模型；再通过因子分析、解耦运算、数据挖掘和数据融合以及线性/非线性降维运算优化和简化模型；通过物联网传感器节点部署方案的优化，确立适应封闭式基质栽培日光温室生产和管理的环境最优调控策略，促进日光温室的健康可持续性发展。

本项目以封闭式基质栽培日光温室作为研究对象，研究日光温室环境最优调控与管理策略。主要研究成果包括：（1）研究开发了基于物联网的温室环境/作物信息获取方法与感知系统，包括作物叶片表面微环境参数检测系统、主动式作物冠层光谱反射率监测系统、作物水分快速检测仪以及冠层氮素营养诊断光谱监测仪，为温室环境及作物信息获取提供了有效的方法和技术支持；（2）确立了封闭式基质栽培日光温室环境因子最优调控策略与方法。采用主成分分析、粗糙集属性约简等方法对获取数据进行预处理，基于BP神经网络算法建立了封闭式基质栽培日光温室CO2浓度调控和光合预测模型；（3）确立了封闭式基质栽培日光温室营养液及CO2气肥循环补给最优控制策略与方法。分别研究了CO2增施与养分、土壤水分的交互作用对番茄生长的影响，为模型优化提供了理论依据；（4）确立了封闭式基质栽培日光温室集群管理物联网节点部署方案和数据挖掘及融合方法。搭建了基于无线传感器网络的日光温室环境调控决策服务平台，对温室环境数据和作物数据进行远程获取，结合所建立的温室CO2浓度调控模型和光合预测模型，对海量异构信息进行智能处理与分析，并最终实现温室智能调控。