Study on Near Infrared Spectroscopy of Transgenic Soybean Identification Based on Principal Component Analysis and Neural Network

	Study on Near Infrared Spectroscopy of Transgenic Soybean Identification Based on Principal Component Analysis and Neural Network
	Wu J.; Huang F. R.; Huang C. H.; Zhang J.; Chen X. D.
	2013
发表期刊	Spectroscopy and Spectral Analysis
ISSN	ISBN/1000-0593
卷号	33 期号:6
摘要	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 (PGA) 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.
收录类别	SCI
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/40870
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Wu J.,Huang F. R.,Huang C. H.,et al. Study on Near Infrared Spectroscopy of Transgenic Soybean Identification Based on Principal Component Analysis and Neural Network[J]. Spectroscopy and Spectral Analysis,2013,33(6).
APA	Wu J.,Huang F. R.,Huang C. H.,Zhang J.,&Chen X. D..(2013).Study on Near Infrared Spectroscopy of Transgenic Soybean Identification Based on Principal Component Analysis and Neural Network.Spectroscopy and Spectral Analysis,33(6).
MLA	Wu J.,et al."Study on Near Infrared Spectroscopy of Transgenic Soybean Identification Based on Principal Component Analysis and Neural Network".Spectroscopy and Spectral Analysis 33.6(2013).

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
近红外光谱结合主成分分析和BP神经网络的（261KB）			开放获取	CC BY-NC-ND	浏览下载