设施番茄栽培智能补光系统关键技术研究

Research on Key Technology of Intelligent Light-filling System for Facility Tomato Cultivation

为了进一步提高设施番茄的品质与产量,在国内外对设施番茄栽培补光研究的基础上,研发了一套设施番茄栽培智能补光系统。该系统通过人工神经网络自主学习并识别番茄不同生长阶段,根据识别的番茄生长周期内所处的不同生长阶段,实现对补光光源红蓝光比例的动态调整,建立了对应于番茄不同生长阶段的补光控制线性模型,完成了对设施番茄生长全过程的精准补光诱导。测试结果表明,该系统识别准确度高,满足了设施番茄生长全过程精准补光的需求。

In order to further improve the quality and production of greenhouse tomatoes,a set of intelligent light supplement system for greenhouse tomatoes cultivation was developed on the basis of the research on greenhouse tomatoes cultivation at home and abroad.The system independently learns and recognizes different growth stages of tomatoes through artificial neural network,then adjusts the ratio of red and blue light according to the different growth stages of the tomatoes,and completes the precise supplementary light induction of the whole growth process of the greenhouse tomatoes at last.The test results show that the system has high recognition accuracy,which meets the needs of light supplement in the whole process of tomato growth in the facility.