近红外光谱结合主成分分析和BP神经网络的转基因大豆无损鉴别研究

doi:10.3964/j.issn.1000-0593(2013)06-1537-05

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摘要：为探究无损鉴别转基因大豆的可行性，利用近红外光谱分析仪对大豆扫描得到反射光谱，应用主成分分析结合BP神经网络方法进行分析鉴别。首先应用主成分分析法，得到包含大豆99.03%的光谱信息的6个主成分，再将其作为BP神经网络的输入，对应的大豆种类作为输出，建立一个三层BP神经网络模型。该模型对于转基因大豆的正确识别率为100%，说明近红外光谱结合主成分分析和BP神经网络的方法能无损快速准确地鉴别转基因大豆。

关键词：近红外光谱;转基因大豆;主成分分析;BP神经网络

Abstract：In order to explore a rapid identification method for transgenic soybeans, non-transgenic and transgenic soybeans were tested as the experimental samples via near infrared spectroscopy (NIR) and principal component analysis (PCA) combined with back propagation artificial neural network (BP-ANN) model. The spectrum data was collected after NIRS scanning the samples, and then analyzed by PCA plus BP-ANN model. The accumulative reliabilities of the six components were 99. 03% through the PCA. Then BP-ANN model was used to further test these six components and a three-layer BP-ANN model was developed. The final result achieved a 100% recognition rate of all 22 test samples respectively. In conclusion, the measure of NIRS and PCA combined with BP-ANN model has proved to be a rapid and accurate method to detect transgenic soybean nondestructively.

Key words：NIR;Transgenic soybean;PCA;ANN-BP

收稿日期: 2012-07-05 修订日期: 2012-10-07

中图分类号:

O433.4

通讯作者: 黄富荣 E-mail: furong_huang@163.com

引用本文:

吴江¹，黄富荣^1*，黄才欢²，张军¹，陈星旦^1，3 . 近红外光谱结合主成分分析和BP神经网络的转基因大豆无损鉴别研究 [J]. 光谱学与光谱分析, 2013, 33(06): 1537-1541.
WU Jiang¹, HUANG Fu-rong^1*, HUANG Cai-huan², ZHANG Jun¹, CHEN Xing-dan^{1, 3} . Study on Near Infrared Spectroscopy of Transgenic Soybean Identification Based on Principal Component Analysis and Neural Network . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2013, 33(06): 1537-1541.

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