镉污染油菜叶片的反射光谱响应与镉含量估计模型
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摘要
植物中镉含量是指示土壤受镉污染程度的重要指标。以市场上主栽的常规油菜品种为材料,采用盆栽试验研究油菜叶片在6个不同浓度梯度镉污染处理下的光谱响应,初步建成叶片中镉含量的预测模型。以光谱角描述油菜叶片反射光谱受镉污染水平变异,结果显示叶片反射光谱敏感波段分布在全波段350～2 500nm,其中表征色素区间的350～716nm和叶片结构区间的717～975nm受镉污染水平变异更明显;利用导数光谱技术和三边参数与叶片镉含量相关性分析,确定光谱特征参数,建立叶片镉含量与光谱特征参数之间的多元回归模型,结果显示,以一阶微分导数筛选的光谱特征参数为自变量建立的模型拟合度R2和RMSE效果最佳,分别达到0. 899和7. 532。本研究建立的通过高光谱技术快速、准确、无损地检测油菜叶片镉含量的估计模型,为油菜高光谱遥感数据分析及镉污染估测提供了科学依据。
Usinga common Brassica napus L. variety as materials,a pot experiment was carried out to study the spectral response of Brassica napus L. leaves tocadmium pollutionwithsix cadmium pollution treatments( cadmium concentration gradient),and a preliminary prediction model forcadmium content in leaves was established. The variation of the reflectance spectra of leaves was described by spectral angle,the results showed that sensitive bands of the reflected spectra were distributed in the whole-band 350-2 500 nm,and the variation of the pigment 350-716 nm and leaves structure 717-975 nm were more obvious than others. After correlation analysis between derivative spectral data,trilateral parameters and cadmium content,the sensitive bands were decided. According to these sensitive parameters,multivariable linear regression models to estimate the cadmium content in leaves were established. The results of the model precision test showed that cadmium content estimation model established by first derivative spectral data were better than others,whose R2 and RMSE were 0. 899 and 7. 532,respectively. The results indicated that Brassica napus L. could be used as an indicator crop of cadmium pollution,which provided a scientific basis for rapid,accurate and nondestructive detection of cadmium pollution in leaves by hyperspectral technique.
Usinga common Brassica napus L. variety as materials,a pot experiment was carried out to study the spectral response of Brassica napus L. leaves tocadmium pollutionwithsix cadmium pollution treatments( cadmium concentration gradient),and a preliminary prediction model forcadmium content in leaves was established. The variation of the reflectance spectra of leaves was described by spectral angle,the results showed that sensitive bands of the reflected spectra were distributed in the whole-band 350-2 500 nm,and the variation of the pigment 350-716 nm and leaves structure 717-975 nm were more obvious than others. After correlation analysis between derivative spectral data,trilateral parameters and cadmium content,the sensitive bands were decided. According to these sensitive parameters,multivariable linear regression models to estimate the cadmium content in leaves were established. The results of the model precision test showed that cadmium content estimation model established by first derivative spectral data were better than others,whose R2 and RMSE were 0. 899 and 7. 532,respectively. The results indicated that Brassica napus L. could be used as an indicator crop of cadmium pollution,which provided a scientific basis for rapid,accurate and nondestructive detection of cadmium pollution in leaves by hyperspectral technique.
引文
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[9]迟光宇,刘新会,刘素红,等. Cu污染与小麦特征光谱相关关系研究[J].光谱学与光谱分析,2006(7):1 272-1 276.
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[11]顾艳文,李帅,高伟,等.基于光谱参数对小白菜叶片镉含量的高光谱估算[J].生态学报,2015,35(13):4 445-4 453.
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[15] Schuerger A C,Capelle G A,Benedetto J A D,et al.Comparison of two hyperspectral imaging and two laser-induced fluorescence instruments for the detection ofzinc stress and chlorophyll concentration in bahia grass(Paspalumnotatum flugge)[J]. Remote Sens Environ,2003,84:572-588.
[16]张义贤.汞、镉、铅污染对油菜的毒害效应[J].山西大学学报:自然科学版,2004(4):410-413.
[17]杨金凤,卜玉山,邓红艳.镉、铅及其复合污染对油菜部分生理指标的影响[J].生态学杂志,2009,28(7):1 284-1 287.
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[19]王一兴.镉对甘蓝型油菜苗期生长的影响[D].南京:南京农业大学,2011.
[20]王凯荣.我国农田镉污染现状及其治理利用对策[J].农业环境科学学报,1997(6):274-278.
[21]韦妮玉,张新英.桂西北矿区农田土壤镉污染评价[J].绿色科技,2016(18):31-33.
[22]周超.植被重金属含量高光谱遥感反演方法研究[D].吉林:吉林大学,2016.
[23]朱叶青,屈永华,刘素红.重金属铜污染植被光谱响应特征研究[J].遥感学报,2014,18(2):335-352.
[24] Dennison P E,Halligan K Q,Roberts D A. A compari-son of error metrics and constraints for multiple endmem-ber spectral mixture analysis and spectral angle mapper[J]. Remote Sens Environ,2004,93(3):359-367.
[25] Demetriades-Shah T H,Steven M D,Clark J A. Highresolution derivatives spectra in remote sensing[J]. Re-mote Sens Environ,1990,33(1):55-64.
[26]胡军杰.铀矿区植物的光谱特征分析[D].南昌:东华理工大学,2012.
[27]张飞,塔西甫拉提·特依拜,丁建丽,等.塔里木河中游绿洲盐漠带典型盐生植物光谱特征[J].植物生态学报,2012,36(7):607-617.
[28] Zhao C. Studies on the red edge parameters of spectrumin winter wheat under different varieties,fertilizer andwater treatments[J]. Sci Agr Sinica,2002,8.
[29] Zhang B,Niu T,Fang S F,et al. Research on the spectralcharacteristic of typical vegetation in Desert-OasisCrisscross zone[J]. Spectroscopy&Spectral Analysis,2016,36(4).
[30]刘克,赵文吉,郭逍宇,等.野鸭湖典型湿地植物光谱特征[J].生态学报,2010,30(21):5 853-5 861.
[31] Haboudane D,Miller J R,Pattey E,et al. Hyperspectralvegetation indices and novel algorithms for predictinggreen LAI of crop canopies:Modeling and validation inthe context of precision agriculture[J]. Remote Sens En-viron,2004,90(3):337-352.
[32]刘厚田,张维平,于亚平,等.土壤镉污染对水稻叶片光谱反射特性的影响[J].生态学报,1986(2):89-100.
[33]高伟.镉胁迫下两种叶菜类蔬菜的叶片高光谱特征及生理参数模拟[D].重庆:西南大学,2012.
[34]叶蓝韩.重金属胁迫下油菜生理指标变化和金属元素快速检测方法研究[D].杭州:浙江大学,2018.
[35]方慧,宋海燕,曹芳,等.油菜叶片的光谱特征与叶绿素含量之间的关系研究[J].光谱学与光谱分析,2007(9):1 731-1 734.
[36]张永贺,陈文惠,郭乔影,等.桉树叶片光合色素含量高光谱估算模型[J].生态学报,2013,33(3):876-887.
[2]李娜,吕建升,Altermann W,等.光谱分析在植被重金属污染监测中的应用[J].光谱学与光谱分析,2010,30(9):2 508-2 511.
[3] Govender K,Chetty M,Bulcock H. A review of hyper-spectral remote sensing and its application in vegetationand water resource studies[J]. Water SA,2007,33(2):145-151.
[4] Kulaeva O A,Tsyganov V E. Molecular-genetic basis ofcadmium tolerance and accumulation in higher plants[J].Russ J Genet Appl Res,2011,1(5):349.
[5]崔玉静,赵中秋,刘文菊,等.镉在土壤-植物-人体系统中迁移积累及其影响因子[J].生态学报,2003(10):2 133-2 143.
[6] Plaza G Nalecz-Jawecki. The application of bioassays asindicators of petroleum-contaminated soil remediation[J]. Chemosphere,2005,59(2):289-296.
[7] Eisentraeger A,Hund-Rinke K,Roembke J. Assess-ment of ecotoxicity of contaminated soil using bioassays[A]. Monitoring and assessing soil bioremediation[M].Soil Biology. Springer,Berlin,Heidelberg. 2005,5:321-360.
[8]孙彤彤.玉米光谱小波奇异熵的铜污染监测研究[J].环境科学学报,2017,37(11):4 360-4 365.
[9]迟光宇,刘新会,刘素红,等. Cu污染与小麦特征光谱相关关系研究[J].光谱学与光谱分析,2006(7):1 272-1 276.
[10]田国良,包佩丽,李建军,等.土壤中镉、铜伤害对水稻光谱特性的影响[J].环境遥感,1990(2):140-164.
[11]顾艳文,李帅,高伟,等.基于光谱参数对小白菜叶片镉含量的高光谱估算[J].生态学报,2015,35(13):4 445-4 453.
[12] Chi G,Huang B Chen X,et al. Effects of cadmium onvisible and near-infrared reflectance spectra of rice(Oryza sativa L)[J]. Fresenius Environ Bull,2011,20(2):391-397.
[13] Shi R J,Pan X Z,Wang C K,et al. Prediction of cadmi-um content in the leaves of navel orange in heavy metalcontaminated soil using VIS-NIR reflectance spectros-copy[J]. Spectroscopy&Spectral Analysis,2015,35(11):3 140.
[14] Curran P J,Windham W R,Gholz H L. Exploring therelationship between reflectance red edge and chloro-phyll content in Slashpine[J]. Tree Physiol,1995,15(1/4):33-48.
[15] Schuerger A C,Capelle G A,Benedetto J A D,et al.Comparison of two hyperspectral imaging and two laser-induced fluorescence instruments for the detection ofzinc stress and chlorophyll concentration in bahia grass(Paspalumnotatum flugge)[J]. Remote Sens Environ,2003,84:572-588.
[16]张义贤.汞、镉、铅污染对油菜的毒害效应[J].山西大学学报:自然科学版,2004(4):410-413.
[17]杨金凤,卜玉山,邓红艳.镉、铅及其复合污染对油菜部分生理指标的影响[J].生态学杂志,2009,28(7):1 284-1 287.
[18]史新杰,李卓,庄文化,等.油菜对土壤重金属Cd抗性的研究进展[J].中国农学通报,2017,33(14):81-86.
[19]王一兴.镉对甘蓝型油菜苗期生长的影响[D].南京:南京农业大学,2011.
[20]王凯荣.我国农田镉污染现状及其治理利用对策[J].农业环境科学学报,1997(6):274-278.
[21]韦妮玉,张新英.桂西北矿区农田土壤镉污染评价[J].绿色科技,2016(18):31-33.
[22]周超.植被重金属含量高光谱遥感反演方法研究[D].吉林:吉林大学,2016.
[23]朱叶青,屈永华,刘素红.重金属铜污染植被光谱响应特征研究[J].遥感学报,2014,18(2):335-352.
[24] Dennison P E,Halligan K Q,Roberts D A. A compari-son of error metrics and constraints for multiple endmem-ber spectral mixture analysis and spectral angle mapper[J]. Remote Sens Environ,2004,93(3):359-367.
[25] Demetriades-Shah T H,Steven M D,Clark J A. Highresolution derivatives spectra in remote sensing[J]. Re-mote Sens Environ,1990,33(1):55-64.
[26]胡军杰.铀矿区植物的光谱特征分析[D].南昌:东华理工大学,2012.
[27]张飞,塔西甫拉提·特依拜,丁建丽,等.塔里木河中游绿洲盐漠带典型盐生植物光谱特征[J].植物生态学报,2012,36(7):607-617.
[28] Zhao C. Studies on the red edge parameters of spectrumin winter wheat under different varieties,fertilizer andwater treatments[J]. Sci Agr Sinica,2002,8.
[29] Zhang B,Niu T,Fang S F,et al. Research on the spectralcharacteristic of typical vegetation in Desert-OasisCrisscross zone[J]. Spectroscopy&Spectral Analysis,2016,36(4).
[30]刘克,赵文吉,郭逍宇,等.野鸭湖典型湿地植物光谱特征[J].生态学报,2010,30(21):5 853-5 861.
[31] Haboudane D,Miller J R,Pattey E,et al. Hyperspectralvegetation indices and novel algorithms for predictinggreen LAI of crop canopies:Modeling and validation inthe context of precision agriculture[J]. Remote Sens En-viron,2004,90(3):337-352.
[32]刘厚田,张维平,于亚平,等.土壤镉污染对水稻叶片光谱反射特性的影响[J].生态学报,1986(2):89-100.
[33]高伟.镉胁迫下两种叶菜类蔬菜的叶片高光谱特征及生理参数模拟[D].重庆:西南大学,2012.
[34]叶蓝韩.重金属胁迫下油菜生理指标变化和金属元素快速检测方法研究[D].杭州:浙江大学,2018.
[35]方慧,宋海燕,曹芳,等.油菜叶片的光谱特征与叶绿素含量之间的关系研究[J].光谱学与光谱分析,2007(9):1 731-1 734.
[36]张永贺,陈文惠,郭乔影,等.桉树叶片光合色素含量高光谱估算模型[J].生态学报,2013,33(3):876-887.
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