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当前位置: 首页 > 文章 > 基于LIF技术分析玉米叶片蒸腾效应模型 农机化研究 2020 (4) 1-5,46
Position: Home > Articles > 基于LIF技术分析玉米叶片蒸腾效应模型 Journal of Agricultural Mechanization Research 2020 (4) 1-5,46

基于LIF技术分析玉米叶片蒸腾效应模型

作  者：
孔丽娟;于海业;陈美辰;朴兆佳;于通;刘爽;隋媛媛
关键词：
玉米叶片;蒸腾速率;激光诱导荧光;叶绿素荧光光谱;无损检测;回归分析
摘  要：
玉米抽丝期是玉米由营养生长进入生殖生长的转折点,是决定玉米产量的关键时期.为此,基于激光诱导荧光光谱(LIF)技术,以抽丝期玉米叶片为研究对象,快速无损地获取植物生理信息的日变化,重点分析玉米叶片蒸腾效应与叶绿素荧光光谱的相关性,并选择706~748nm波段作为敏感光谱波段,建立了基于光谱特征参数的植物叶片蒸腾速率的预测模型.结果表明:采用荧光强度F730研究玉米叶片蒸腾效应最合适;由于气孔导度反映蒸腾效应,且影响CO2的同化过程,故以气孔导度的信号之一的叶片温度作为模型输入修正;通过对蒸腾速率与叶片温度、叶绿素荧光强度进行回归诊断与全回归分析,建立了基于荧光强度F730和叶片温度的蒸腾速率预测模型,分析了蒸腾速率与二者的相关性,模型复相关系数为R=0.833 4,模型校验结果的相关系数R2=0.879 8,认为模型的预测能力较好.通过激光诱导叶绿素荧光光谱技术实现了对植物生理信息的无损检测与分析,建立的玉米抽丝期蒸腾速率预测模型可为玉米优质高产的水肥精准化、智能化控制技术提供数据支持.
作  者：
Kong Lijuan;Yu Haiye;Chen Meichen;Piao Zhaojia;Yu Tong;Liu Shuang;Sui Yuanyuan;School of Biological and Agricultural Engineering,Jilin University;
关键词：
corn leaf;;transpiration rate;;LIF;;chlorophyll fluorescence spectrum;;nondestructive;;regression analysis
摘  要：
Corn silking stage is the turning point of zea mays from vegetative growth to reproductive growth and the key period of zea mays yield. The leaves of corn silking stage as the research object, obtaining the daily variation of physiological information of leaves quickly and nondestructively based on laser induced fluorescence spectroscopy(LIF) technology, the correlation between leaf transpiration effect and chlorophyll fluorescence spectra of zea mays leaves was analyzed emphatically. A prediction model of transpiration rate of plant leaves based on spectral characteristic parameters was established. The results showed that it was most suitable to study the transpiration effect of zea mays leaves by fluorescence intensity F730. The stomatal conductance reflects the transpiration effect and affects the assimilation process of CO_2, so the leaf temperature, one of the signals of stomatal conductance, was used as the model input to amend. The regression diagnosis and whole regression analysis on transpiration rate and leaf temperature, chlorophyll fluorescence intensity were carried out, establishing the prediction model of transpiration rate based on fluorescence intensity F730 and the leaf temperature, analyzing the correlation between transpiration rate and the two indexes as mentioned before. According to the model complex correlation coefficient(R=0.833 4) and the correlation coefficient of the model calibration results(R~2=0.879 8), the prediction ability of the model is good. The nondestructive detection and analysis of plant physiological information by laser induced chlorophyll fluorescence spectrum technology and the silking stage transpiration rate prediction model, can provide reference data for the precise and intelligent control of water and fertilizer for zea mays with high quality, high yield and yield increase.

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