ABSTRACT

If crops were polluted by heavy metals, the spectra will change. Therefore, the variation information of spectral changes has become an important basis for heavy metal pollution monitoring. Based on spectral frequency domain, we studied the spectra of maize leaves. Combined with time-frequency analysis method, we proposed DDCR-Db (Second-order Differential Continuum Removal- Daubechies) method to detect the sensitive spectral ranges of leaves. Furthermore, we proposed VCPs (Variation Characteristic Parameters), and studied correlation between VCPs and heavy metal content of leaves. And compared with CSI (Conventional Spectral Index) to explore the spectral ranges which are particularly sensitive to Cu²⁺ (Copper ion) and Pb²⁺ (Lead ion) stress. Finally, combined with the nonlinear time-frequency distribution, we constructed DDCR-Db-CW (Second-order Differential Continuum Removal-Daubechies-Choi-Williams) transform of the spectra transformation method to distinguish copper and lead pollution. The results showed that DDCR-Db can effectively extract weak spectral information of leaves under copper and lead stress. We obtained the spectral ranges which are particularly sensitive to Cu²⁺ and Pb²⁺ stress. DDCR-Db-CW transform can distinguish the spectral difference between no heavy metal stress and heavy metal stress, and intuitively distinguish the types of copper and lead stress.

摘要

如果农作物被重金属污染，光谱将发生变化。因此，光谱变化的变化信息已成为重金属污染监测的重要依据。基于光谱频域，我们研究了玉米叶片的光谱。结合时频分析方法，我们提出了DDCR-Db（二阶微分连续谱去除-道贝基斯）方法来检测叶片的敏感光谱范围。此外，我们提出了VCP（变异特征参数），并研究了VCP与叶片中重金属含量之间的相关性。并与CSI（常规光谱指数）进行比较，以探索对Cu ²⁺（铜离子）和Pb ²⁺特别敏感的光谱范围（铅离子）应力。最后，结合非线性时频分布，构造了光谱变换法的DDCR-Db-CW（二阶微分连续谱去除-Daubechies-Choi-Williams）变换，以区分铜和铅污染。结果表明，DDCR-Db可以有效地提取铜和铅胁迫下叶片的弱光谱信息。我们获得了对Cu ²⁺和Pb ²⁺应力特别敏感的光谱范围。DDCR-Db-CW变换可以区分无重金属应力和重金属应力之间的光谱差异，并直观地区分铜和铅应力的类型。