宽带信号激励的叶绿素荧光建模及其用于水稻干旱胁迫测量的机理研究

干旱胁迫会改变农作物生理特征，影响其光合系统效率，从而导致农作物的减产。课题拟将叶绿素荧光检测技术引入到农作物干旱胁迫测量，以解决传统的基于农作物土壤含水量测量方法难以准确反映农作物干旱胁迫状态的问题。项目：（1）研究宽带激励下的叶绿素荧光激发方法，探究其合理的激励参数和特征多维提取方法，以克服传统窄带激励信号难以充分获取农作物光合系统动态特性问题；（2）研究建立宽带信号激励下叶绿素荧光模型结构、分析模型结构的可辨识性和参数识别算法，以提高检测精度，满足在线测量需求；（3）以水稻为研究对象，探索宽带信号激励下的叶绿素荧光参数同水稻干旱胁迫的关系机理，利用多种信号分析方法，建立水稻干旱胁迫的融合模型，构建基于宽带信号激励叶绿素荧光的水稻干旱胁迫测量方法体系。本课题的研究，对于完善现有的叶绿素荧光测量方法，促进其在农作物生长环境感知中的应用，特别是水稻干旱胁迫检测中的应用提供理论和科学依据。

Drought stress may change crop physiological status, reduce photosynthetic efficiency, and lead to crop yield reduction. This proposal aims to employ chlorophyll fluorescence (ChlF) as a technique for crop drought stress measurement, which is expected to eliminate the drawback of characterizing drought stress by measuring soil moister content. In this project: (1) A broad-band ChlF excitation technique, including optimal excitation parameters and multiple dimensional feature extraction methods, will be studied to solve the problem that traditional narrow-band excitations cannot perturb the whole dynamics of the photosystems. (2) In order to improve drought stress measurement accuracy and make ChlF as an online measuring technique, a model structure for broad-band ChlF excitations will be built and the model parameter identifiability and identification algorithms will be investigated. (3) Rice will be used as an example to study the relationship and mechanism of ChlF under broad-band excitations for drought stress measurement. ChlF signals under broad-band excitations will be analyzed from multiple dimensions, an information fusion model will be built for rice drought stress characterization, and a systematic foundation for rice drought stress measurement will be developed through ChlF under broad-band excitations. This project will improve traditional ChlF measurement techniques and enhance ChlF applications in sensing crop physiological status and environmental changes, especially provide theoretical and scientific base for rice drought stress measurement.