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污染土壤对脐橙叶片镉含量影响的光谱预测
引用本文:石荣杰,潘贤章,王昌昆,刘 娅,李燕丽,李志婷.污染土壤对脐橙叶片镉含量影响的光谱预测[J].光谱学与光谱分析,2015,35(11):3140-3145.
作者姓名:石荣杰  潘贤章  王昌昆  刘 娅  李燕丽  李志婷
作者单位:1. 中国科学院土壤环境与污染修复重点实验室(南京土壤研究所),江苏 南京 210008
2. 中国科学院大学,北京 100049
摘    要:近年来可见-近红外光谱技术在农业污染监测中应用越来越广泛,但在果树的重金属污染研究中应用较少。本文以纽荷尔脐橙(Citrus sinensisL.]Osbeck cv. Newhall)为研究对象,采用盆栽方法,通过添加镉(Cd)形成不同污染程度的土壤,然后定期监测叶片中Cd含量及其光谱,分别建立了基于光谱指数的线性回归预测模型,以及基于偏最小二乘回归(PLSR)的Cd含量高光谱预测模型。结果表明:Cd更容易向新叶迁移和聚集,在高Cd污染的土壤中这种现象更加明显;新叶光谱在700~730 nm之间反射率升高,发生红边蓝移现象,老叶光谱没有显著变化;基于光谱指数建立的线性回归模型的R2达到0.8左右,而利用PLSR方法建立的预测模型精度普遍高于线性回归模型,其R2达到0.9左右,并且标准归一化(SNV)的光谱预处理方法可以显著提高PLSR模型的预测精度。研究显示,可见-近红外光谱技术在脐橙重金属污染监测上有很好的潜力。

关 键 词:  光谱指数  脐橙  重金属污染  PLSR    
收稿时间:2014-08-17

Prediction of Cadmium Content in the Leaves of Navel Orange in Heavy Metal Contaminated Soil Using VIS-NIR Reflectance Spectroscopy
SHI Rong-jie,PAN Xian-zhang,WANG Chang-kun,LIU Ya,LI Yan-li,LI Zhi-ting.Prediction of Cadmium Content in the Leaves of Navel Orange in Heavy Metal Contaminated Soil Using VIS-NIR Reflectance Spectroscopy[J].Spectroscopy and Spectral Analysis,2015,35(11):3140-3145.
Authors:SHI Rong-jie  PAN Xian-zhang  WANG Chang-kun  LIU Ya  LI Yan-li  LI Zhi-ting
Institution:1. Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China2. University of Chinese Academy of Sciences,Beijing 100049,China
Abstract:Visual and Near-infrared (VIS-NIR) reflectance spectroscopy had been used widely in monitoring agricultural pollution in recent years, however, it was rarely applied in monitoring the contamination of heavy metal in orchards. In the present paper, Newhall navel orange (Citrus sinensis L.] Osbeck cv. Newhall) were cultivated in the potted soil contaminated with cadmium(Cd) at different levels, and the spectral reflectance and Cd content in the leaves were measured simultaneously at different growing seasons, which then were used to establish the prediction model by partial least squares regression (PLSR) based on spectral reflectance and by linear regression based on spectral index. The results showed that Cd was more easily transferred to and cumulated in the new leaves, and this phenomenon was more obvious in heavily contaminated soils with Cd. Blue shift in red edge was found in the band of 700~730 nm in the new leaves, however, no such phenomenon was found in the old leaves. The coefficient of determination (R2) of linear regression model based on spectral index was nearly 0.8, while the PLSR model had a better result in predicting Cd content in the new leaves than the linear regression with R2CV of approximately 0.9. Furthermore, the standard normal variate transformation(SNV)in spectral preprocessing can improve the precision significantly in PLSR model. These results suggest that the VIS-NIR method has a great potential in monitoring heavy metal pollution in the navel orange.
Keywords:Cadmium  Spectral index  Navel orange  Heavy metal contamination  PLSR  
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