光谱学与光谱分析 |
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Study on the Detection and Pattern Classification of Pesticide Residual on Vegetable Surface by Using Visible/Near-Infrared Spectroscopy |
CHEN Rui, ZHANG Jun*, LI Xiao-long |
Institute of Science and Technology for Optoelectronic Information, Yantai University, Yantai 264005, China |
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Abstract A nondestructive testing based on visible/near-infrared reflectance spectroscopy was put forward for the common high pesticide residues of green plants in the wavelength range from 600 to 1 100 nm. Firstly, spectral features were extracted by wavelet transform from original spectral data. Secondly,the principal component analysis (PCA) was done in the further analysis of spectral characteristics. Thirdly, the two PCs were applied as inputs of artificial neural network, and a multi-neuron perceptron neural network was established. Finally, It was proved that the type of pesticide residues was effectively identified and showed by classification results. In short, the study provides a new approach to the detection of pesticide residues in vegetables and fruits.
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Received: 2011-10-12
Accepted: 2012-01-20
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Corresponding Authors:
ZHANG Jun
E-mail: jzhang@ytu.edu.cn
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[1] LIU Chun-hua,LI Yan-hui(刘春华,李艳辉). Agricultural Science & Techonlogy and Equipment(农业科技与装备),2011,204(6):45. [2] LU Wan-zhen,YUAN Hong-fu,XU Guang-tong(陆婉珍,袁洪福,徐广通). Modern Near Infrared Spectroscopy(现代近红外光谱分析技术),Beijing:China Petrochemical Press(北京:中国石化出版社),2007. [3] XU Chang-fa,LI Guo-kuan(徐长发,李国宽). Practical Wavelet Method(实用小波方法). Wuhan:Huazhong University of Science & Technology Press(武汉:华中科技大学出版社),2001. [4] YUAN Zeng-ren(袁增任). Artificial Network and Its Application(人工神经网络及其应用). Beijing:Tsinghua University Press(北京:清华大学出版社),1999.
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