玉米光谱小波奇异熵的铜污染监测研究

不同浓度铜离子(Cu2+)胁迫梯度下的玉米叶片光谱存在细微差异,但传统的光谱相似性测度方法难以区分健康的与受污染的玉米叶片光谱间的变异信息.为此,本文结合小波变换和奇异熵理论,构建小波奇异熵(Wavelet Singular Entropy,WSE)方法用于Cu2+胁迫下的玉米污染程度分析与污染监测.通过设置不同浓度Cu2+胁迫梯度下的玉米盆栽实验,依据玉米叶片的光谱测量数据和所测定的叶片中Cu2+含量,并与绿峰高度(Green-peak Height,GH)和红谷吸收深度(Red-valley Depth,RD)光谱特征参数法污染监测应用结果进行对比分析,研究WSE方法的Cu2+污染监测效果.结果表明,WSE值与Cu2+胁迫梯度、玉米叶片中Cu2+含量呈显著正相关,WSE值大小能够较好地表征叶片光谱的污染信息奇异性及其污染程度.

Monitoring copper pollution based on wave singular entropy of corn leaves

There were slight differences in the spectra of corn leaves stressed by different concentration gradients of Cu²⁺, but the traditional spectral similarity measurement methods were difficult to distinguish the variant spectral information between the healthy and polluted corn leaves. In this regard, a wavelet singular entropy (WSE) method was built and used to analyze and monitor pollution degrees of the corn stressed by Cu²⁺ in this paper. By setting the potted corn experiments stressed by different concentration gradients of Cu²⁺ and according to the measured parameters on spectra of corn leaves and Cu²⁺ contents in the leaves, Cu²⁺ pollution was monitored with the WSE method and compared with the pollution monitoring results based on the spectral characteristic parameters of green peak height (GH) and red-valley depth (RD). The results showed that the WSE values were positively correlated with the stress gradient of Cu²⁺ and the content of Cu²⁺ in the leaves of corn, and the WSE values could monitor the singularity of the pollution information on the spectra of corn leaves and the degree of pollution.