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Smart Agriculture ›› 2021, Vol. 3 ›› Issue (4): 86-98.doi: 10.12133/j.smartag.2021.3.4.202109-SA007

• 智能管理与控制 • 上一篇    下一篇

南方蓝莓智能温室促早熟生产多因子协调控制技术

徐立鸿(), 刘辉辉, 徐赫, 蔚瑞华, 蔡文韬   

  1. 同济大学 电子与信息工程学院,上海 201800
  • 收稿日期:2021-09-17 修回日期:2021-11-18 出版日期:2021-12-30
  • 基金资助:
    上海市科委创新行动计划项目(17391900900);国家自然科学基金项目(61973337)
  • 通信作者: 徐立鸿(1960-),博士,教授,研究方向为温室环境建模与控制、预测控制和智能控制。电话:17321126466。E-mail:

Multi-Factor Coordination Control Technology of Promoting Early Maturing in Southern Blueberry Intelligent Greenhouse

XU Lihong(), LIU Huihui, XU He, WEI Ruihua, CAI Wentao   

  1. College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
  • Received:2021-09-17 Revised:2021-11-18 Online:2021-12-30
  • corresponding author: XU Lihong, E-mail:
  • Supported by:
    Shanghai Science and Technology Commission Innovation Action Plan Project (17391900900);National Natural Science Foundation of China(61973337)

摘要:

为达到蓝莓提前上市、获得更大经济效益的目的,本团队将南方蓝莓移至环境可控型智能温室中试验生产,探索研究出南方蓝莓智能温室促早熟生产控制技术。首先从蓝莓物候期、品种特点、土壤pH、水肥灌溉方式、小气候环境区间等方面进行了较为详细全面的调研与总结,明确了无土栽培蓝莓全周期管理要点和环境调控范围;接着基于Venlo型温室对蓝莓生产做布局,并基于物联网技术,建立蓝莓植物工厂化生产控制系统,串联硬件层、软件层和云端,实现现场端环境检测调控、数据云存储与远程控制等技术;在温室环境多因子协调控制模型基础上,针对蓝莓生长环境特点,探索研究了一套蓝莓温室多因子协调控制算法,用于环境调控。试验温室位于江苏省苏州市昆山市花桥镇东南部。经实际验证,整体调控系统效果显著,并于2021年5月初采收了第一波果实,使南方品种蓝莓提早近一个月进入果实采摘期。其中相比未蓄冷的蓝莓植株,蓄冷后的“明星”“绿宝石”“蓝美1号”“海岸”单株产量分别增加51.5%、85.5%、43.8%和94.7%,单果重量分别增加10.9%、7.2%、2.6%和5.3%。试验证明采用多因子协调控制算法进行调控能够提高蓝莓的产量和品质,取得显著经济效益,为南方温室蓝莓植物工厂化促早熟生产管理提供示范。

关键词: 蓝莓, 栽培管理, 植物工厂, 促早熟, 生产控制系统, 多因子协调控制算法, 物联网

Abstract:

In order to get blueberries goes on sale in advance and obtain greater economic benefits, southern blueberries were moved to an intelligent greenhouse with controllable environment for experimental production. The early maturing production control technology of southern blueberry intelligent greenhouse was explored and studied. First, a detailed and comprehensive investigation and summary were conducted on the production factors of blueberry soilless cultivation, such as the production characteristics of various blueberry varieties, the pH and composition of the substrate, the key points of water and fertilizer irrigation, and the scope of the microenvironment climate. Then, the existing Venlo-type greenhouse was deployed for blueberry production, and the geography, climate and internal structural conditions of the greenhouse were briefly described, and the greenhouse blueberry full-cycle control goal was planned. Finally, the production control system was designed and implemented based on the Internet of Things technology, and the overall framework of the software layer, the hardware layer and the cloud were introduced. Based on multi-factor coordinated control model of greenhouse environment, according to the characteristics of blueberry growth environment, a set of blueberry greenhouse multi-factor coordinated control algorithms were proposed and used for environmental regulation. The experimental greenhouse is located in the southeast of Huaqiao Town, Kunshan city, Suzhou city, Jiangsu province. It has been verified that the overall control system has a significant effect, and the first wave of fruits was harvested in early May 2021, making the southern variety of blueberry enter the fruit picking period nearly one month earlier. Compared with the blueberry plants without cold storage, the yields per plant of "Star" "Emerald" "Lanmei No. 1", and "Coast" after cold storage increased by 51.5%, 85.5%, 43.8%, and 94.7%, respectively, and the weight of each fruit was increased 10.9%, 7.2%, 2.6%, and 5.3%, respectively. Experiments proved that the use of multi-factor coordinated control algorithms for regulation can increase the yield and quality of blueberries and achieve significant economic benefits and provide a demonstration for the industrialization of blueberry plants in southern greenhouses to promote early maturity production and management.

Key words: blueberry, cultivation management, plant factory, promoting early-ripeness, production control system, multi-factor coordination control algorithm, Internet of Things

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