基于荧光光谱的空间高等植物叶绿素含量测量技术

摘要

开展高等植物光合作用过程参数的实时检测技术研究，对于深入开展空间生物学效应具有重要意义。作为光合作用重要参数的高等植物叶绿素含量与其荧光光谱具有较好的相关性，为此，可以通过探测分析植物荧光光谱，建立其与叶绿素的相关性模型，间接表征其中的叶绿素含量。介绍一种新的建模方法即支持向量机（SVM），通过实验验证，方法预测叶绿素含量是可行的，相对于一般采用的线性回归法具有更好的预测效果和更高的测量精度。%Doing research on technology for real-time detection of process parame-ters of photosynthesis in higher plants have great significance for deeply studying biological effects of space. Chlorophyll content which is an important parameter of photosynthesis in higher plants shows a very good correlation with fluorescence spectra. Therefore,establish correlation model between fluorescence spectra and chlorophyll to indirectly represent the chlorophyll content by detecting and analyzing fluorescence spectra of plants. Describe a new method of modeling which is support vector machine(SVM). Through experimental verification,the method is feasible to predict the chlorophyll content,which has better prediction performance and higher precision than linear regression method.