LI Kai,WEI Xiaoming,HE Fen.Research Progress of Greenhouse Environmental Control Based on Plant Physiological Detection[J].Northern Horticulture,2020,44(15):130-137.[doi:10.11937/bfyy.20194095]
基于植物生理检测参数的温室环境控制研究进展
- Title:
- Research Progress of Greenhouse Environmental Control Based on Plant Physiological Detection
- 文献标志码:
- A
- 摘要:
- 随着我国设施农业面积的不断扩大、温室栽培技术的不断提升，温室环境的智能化控制需求明显。传统温室生产完全依靠经验判断植物生长状况，标准无法统一，时效性过于随机，对人员体力经验要求很高，而植物生理检测可准确、实时地获取植物本体信息，对于分析植物生长状况和对环境控制实现预指导等具有重要意义。通过对国内外大量参考文献进行分析发现，原位在线式的植物生理检测参数主要包含叶片厚度、叶片温度、茎直径、茎流4个方面。为此针对这4项参数分析和总结了国内外用以指导温室环境控制的研究情况，并提出了植物生理信息在智能化温室环境控制方面的前景及难点，以期为基于植物生理检测参数的温室环境控制研究提供参考依据。
- Abstract:
- With continuous expansion of protected agriculture area and continuous improvement of greenhouse cultivation technology in China,the demand for greenhouse environment intelligent control becomes more and more obvious.With the traditional greenhouse production methods,determine plant growth depends on experience entirely.Standards could not be unified,timeliness was too random,so personnel physical experience was highly demanded.Plant physiological detection could acquire plant ontology information accurately and in real time.This method was of great significance to the analysis of plant growth and the pre-guidance of environmental control.Based on the analysis of a large number of references in China and abroad,it was found that in situ on-line plant physiological detection mainly included leaf thickness,leaf temperature,stem diameter and stem flow.In this study,the research situation of using these four parameters to guide greenhouse environmental control in China and abroad was analyzed and summarized,and the prospects and difficulties of plant physiological information in intelligent greenhouse environmental control were put forward.It was hoped that it could provide reference for greenhouse environmental control research based on plant physiological parameters.
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备注/Memo
第一作者简介：李恺（1986-），男，山西太原人，博士，工程师，现主要从事现代农业装备研发等研究工作。E-mail:will25505177@163.com.基金项目：国家重点研发计划资助项目（2017YFD0701500）;河北省重点研发计划资助项目（20327207D）。收稿日期：2019-10-30