期刊论文

Determination of soybean leaf SPAD value using characteristic wavelength variables preferably selected by IRIV algorithm

中文

农业工程学报

1002-6819

2018

34

16

148-154

10.11975/j.issn.1002-6819.2018.16.019

国家自然科学基金项目(41401232) 湖北省自然科学基金创新群体项目-《湖北省水土环境变化与健康响应(2016CFA027)》。

本校为第一机构

在植物叶绿素特征波长变量筛选过程中,与叶绿素关系较弱的波长变量极易被忽略,导致这些弱信息变量包含叶绿素的有效信息丢失,因此,确定叶片光谱中弱信息变量对揭示叶绿素高光谱响应规律具有重要意义。该研究以江汉平原大豆鼓粒期的叶片为研究对象,采集80组大豆叶片高光谱和SPAD(soil and plant analyzer development)值,分析SPAD值与大豆叶片反射率相关关系和光谱波长变量自相关关系,基于迭代和保留信息变量法(iteratively retains informative variables,IRIV)筛选大豆叶片的特征波长变量,建立偏最小二乘回归(partial least squares regression,PLSR)和支持向量机(support vector machine,SVM)...

Chlorophyll is a good indicator of plant nutrition stress, photosynthetic ability and aging process. The use of hyperspectral remote sensing technology to monitor the chlorophyll status of soybean leaves is of great significance for soybean growth diagnosis and fertilization regulation. However, the information weakly correlated to chlorophyll is very easy to be neglected in the selecting process, which leads to the loss of effective information containing chlorophyll. Therefore, it is important to determine the weak information variables in le...