利用叶片光谱的作物铜铅污染判别  

Discriminating copper and lead contamination in crops using leaves spectra

作　　者：高伟 杨可明[1] 陈改英[2] 赵恒谦[1] 张超[1] 姚树一 王剑 石晓宇 Gao Wei;Yang Keming※;Chen Gaiying;Zhao Hengqian;Zhang Chao;Yao Shuyi;Wang Jian;Shi Xiaoyu(College of Geoscience and Surveying Engineering,China University of Mining&Technology(Beijing),Beijing 100083,China;College of Landscape Architecture,Beijing University of Agriculture,Beijing 102206,China)

机构地区：[1]中国矿业大学(北京)地球科学与测绘工程学院,北京100083 [2]北京农学院园林学院,北京102206

出　　处：《农业工程学报》2021年第3期173-178,共6页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家自然科学基金资助项目(No.41971401);中央高校基本科研业务费专项资金资助项目(No.2020YJSDC02)。

摘　　要：重金属污染种类的判别是作物生长环境监测的重要组成部分。该研究旨在提出一种由叶片光谱构建的铜铅污染判别特征(Copper and Lead Contamination Discriminating Features,CLCDF),以实现作物铜、铅污染判别。以典型作物玉米为试验对象,运用包络线去除与导数处理叶片光谱,基于该研究提出的归一化铜铅污染指数(NormalizedDifference Copper and Lead Contamination Index,NDCLCI)构建叶片CLCDF,在CLCDF分布域内建立判别平面(Discriminating Plane,DP)。依据CLCDF与DP的位置关系,得出直观的污染种类判别规则,并利用判别距离(Discriminating Distance,DD)对判别规则进行量化。基于训练集数据进行试验,提取到189种用于判别铜、铅污染的DP,同时获取了对应的污染种类判别规则,判别正确率为100%。使用验证集数据进行验证,189种DP中的88种判别效果较好,判别正确率为78.22%。该研究结果证明,基于CLCDF的铜铅污染判别方法效果良好且稳定。Discrimination on the type of heavy metal contamination can contribute to the detection of diseases that caused by heavy metals,thereby to protect human health.This study aims to propose a Copper and Lead Contamination Discriminating Features(CLCDF)that constructed from leaf spectra to discriminate between copper and lead contamination in crops.Firstly,a typical agricultural corn was taken as an experiment object,and then to cultivate in soils that were contaminated with copper or lead.The soil-based contamination levels were set:50,100,150,200,300,400,600,and 800 mg/kg.Secondly,an ASD FieldSpec 4 spectrometer was used to measure the spectral reflectance data of plant leaves.The continuum removal(CR)and derivative(D)were selected for spectral preprocessing(in this study,D processing with derivation window radius of 1,2 and 3 nm was performed respectively),and obtained CRD1,CRD2 and CRD3 spectra.The Normalized Difference Copper and Lead Contamination index(NDCLCI)was finally extracted using CRD1,CRD2 and CRD3 spectra,respectively.There was a high correlation between the NDCLCI and the types of heavy metal contamination from the leaves.The CLCDF of leaves was also constructed using NDCLCI.There were significant differences in the location of CLCDF when the types of heavy metal contamination were different.A Discriminating Plane(DP)was established in the domain of CLCDF distribution area for partitioning the domain of copper and lead contaminated.According to the relationship between the position of CLCDF and DP,the rules were obtained for the visual discrimination of copper and lead contamination types.The Discriminating Distance(DD)was used to quantify the discriminating.Using the training set data,a total of 189 DPs were obtained with the discriminating correct rate of 100%.The visual discriminating rules were:the left DP was the copper contamination domain,where the domain of CLCDF corresponding to the blade contaminated with copper,while,the right DP was the lead contamination domain,where the domain of CLCDF c

关 键 词：作物 叶片 重金属 铜铅污染 判别特征 污染指数 

分 类 号：P23[天文地球—摄影测量与遥感]