Discrimination of Transgenic Maize Kernel Using NIR Hyperspectral Imaging and Multivariate Data Analysis

文献类型： 外文期刊

第一作者： Feng, Xuping

作者： Feng, Xuping;Zhao, Yiying;Zhang, Chu;He, Yong;Cheng, Peng

作者机构：

关键词： classification;NIR hyperspectral imaging;chemometrics analysis

期刊名称：SENSORS （ 影响因子：3.576； 五年影响因子：3.735 ）

ISSN： 1424-8220

年卷期： 2017 年 17 卷 8 期

页码：

收录情况： SCI

摘要： There are possible environmental risks related to gene flow from genetically engineered organisms. It is important to find accurate, fast, and inexpensive methods to detect and monitor the presence of geneticallymodified (GM) organisms in crops and derived crop products. In the present study, GM maize kernels containing both cry1Ab/cry2Aj-G10evo proteins and their non-GM parents were examined by using hyperspectral imaging in the near-infrared (NIR) range (874.41-1733.91 nm) combined with chemometric data analysis. The hypercubes data were analyzed by applying principal component analysis (PCA) for exploratory purposes, and support vector machine (SVM) and partial least squares discriminant analysis (PLS-DA) to build the discriminant models to class the GM maize kernels from their contrast. The results indicate that clear differences between GM and non-GM maize kernels can be easily visualized with a nondestructive determination method developed in this study, and excellent classification could be achieved, with calculation and prediction accuracy of almost 100%. This study also demonstrates that SVM and PLS-DA models can obtain good performance with 54 wavelengths, selected by the competitive adaptive reweighted sampling method (CARS), making the classification processing for online application more rapid. Finally, GM maize kernels were visually identified on the prediction maps by predicting the features of each pixel on individual hyperspectral images. It was concluded that hyperspectral imaging together with chemometric data analysis is a promising technique to identify GM maize kernels, since it overcomes some disadvantages of the traditional analytical methods, such as complex and monotonous sampling.

分类号：

  • 相关文献

[1]A Simple and Efficient Method for CRISPR/Cas9-Induced Rice Mutant Screening. Feng Xu-ping,Zhang Chu,Liu Xiao-dan,Shen Ting-ting,He Yong,Feng Xu-ping,Zhang Chu,Liu Xiao-dan,Shen Ting-ting,He Yong,Peng Cheng,Xu Jun-feng. 2018

[2]Visible-near infrared spectrum-based classification of apple chilling injury on cloud computing platform. Xia Ji'An,Yang YuWang,Han Chen,Cao HongXin,Ge DaoKuo,Zhang WenYu. 2018

[3]Classification Methods of Remote Sensing Image Based on Decision Tree Technologies. Jiang, Lihua,Wang, Wensheng,Yang, Xiaorong,Xie, Nengfu,Jiang, Lihua,Wang, Wensheng,Yang, Xiaorong,Xie, Nengfu,Cheng, Youping. 2011

[4]Classification of the urbanization types in the Yangtze River Delta. Xu, Juan,Yang, Li,Zhang, Wei. 2012

[5]Proposal for a unified classification system and nomenclature of lagoviruses. Le Pendu, Jacques,Ruvoen-Clouet, Nathalie,Abrantes, Joana,Lopes, Ana Margarida,Almeida, Tereza,Celio, Alves Paulo,Marques, Sara,Monterroso, Pedro,Silverio, Diogo,Thompson, Gertrudes,Esteves, Pedro,Bertagnoli, Stephane,Guitton, Jean-Sebastien,Marchandeau, Stephane,Almeida, Tereza,Le Gall-Recule, Ghislaine,Alda, Fernando,Celio, Alves Paulo,Goncalves, David,Esteves, Pedro,Celio, Alves Paulo,Barcena, Juan,Blanco, Esther,Burmakina, Galina,Calvete, Carlos,Cavadini, Patrizia,Lavazza, Antonio,Cooke, Brian,Cooke, Brian,Dalton, Kevin,Parra, Francisco,Delibes Mateos, Miguel,Deptula, Wieslaw,Eden, John Sebastian,Eden, John Sebastian,Wang, Fang,Ferreira, Catarina C.,Ferreira, Catarina C.,Ferreira, Paula,Marques, Raquel M.,Ferreira, Paula,Marques, Raquel M.,Foronda, Pilar,Martin-Alonso, Aaron,Gavier-Widen, Dolores,Neimanis, Aleksija,Gavier-Widen, Dolores,Neimanis, Aleksija,Hall, Robin,Strive, Tanja,Hukowska-Szematowicz, Beata,Niedzwiedzka-Rystwej, Paulina,Kerr, Peter,Mah. 2017

[6]Analysis of the Germplasm Resources and Genetic Relationships among Cymbidium tortisepalum Cultivars Using Amplified Fragment Length Polymorphism Markers. Wu, X. Y.,Li, D. M.,Zhu, G. F.. 2013

[7]CAMELLIA (THEACEAE) CLASSIFICATION WITH SUPPORT VECTOR MACHINES BASED ON FRACTAL PARAMETERS AND RED, GREEN, AND BLUE INTENSITY OF LEAVES. Jiang, W.,Tao, Z. M.,Wu, Z. G.,Mantri, N.,Lu, H. F.,Liang, Z. S.,Jiang, W.,Tao, Z. M.,Wu, Z. G.,Mantri, N.. 2017

[8]Primary identifications and palynological observations of Perilla in China. Hu, Yan,Sun, Li-Wei,Neo, Mokgolodi C.,Zhang, Yan-Xia,Liu, Yu-Jun,Hu, Yan,Wen, Chun-Xiu,Xie, Xiao-Liang. 2010

[9]A COMPARATIVE ANALYSIS OF MUTUAL INFORMATION BASED FEATURE SELECTION FOR HYPERSPECTRAL IMAGE CLASSIFICATION. Fu, Yuanyuan,Fu, Yuanyuan,Jia, Xiuping,Huang, Wenjiang,Wang, Jihua. 2014

[10]The Classification of Wheat Varieties Based on Near Infrared Hyperspectral Imaging and Information Fusion. Dong Gao,Guo Jian,Dong Gao,Wang Cheng,Chen Zi-long,Zheng Ling,Zhu Da-zhou,Zhu Da-zhou. 2015

[11]Analysis of Volatiles during Grape Deterioration Using FTIR. Wang Wenzhong,Dong Daming,Zheng Wengang,Jiao Leizi,Zhao Xiande,Wang Wenzhong,Han Junfeng,Ye Song. 2013

[12]Detection and identification of a novel subgroup 16SrII-V phytoplasma associated with Praxelis clematidea phyllody disease. Yang, Yi,Jiang, Lei,Lu, Ying,Zhang, Xin,Yang, Yi,Jiang, Lei,Lu, Ying,Zhang, Xin,Yang, Yi,Jiang, Lei,Lu, Ying,Zhang, Xin,Tian, Qian,Zhao, Wenjun. 2017

[13]Estimation of the Age and Amount of Brown Rice Plant Hoppers Based on Bionic Electronic Nose Use. Xu, Sai,Zhou, Zhiyan,Lu, Huazhong,Luo, Xiwen,Lan, Yubin,Xu, Sai,Zhou, Zhiyan,Lu, Huazhong,Luo, Xiwen,Lan, Yubin,Lan, Yubin,Zhang, Yang,Li, Yanfang,Zhang, Yang,Li, Yanfang. 2014

[14]Non-specific lipid transfer proteins in plants: presenting new advances and an integrated functional analysis. Liu, Fang,Lu, Changming,Zeng, Xinhua,Li, Yunjing,Wu, Gang,Zhang, Xiaobo,Fu, Donghui.

[15]Landscape analysis of wetland plant functional types: The effects of image segmentation scale, vegetation classes and classification methods. Dronova, Iryna,Gong, Peng,Gong, Peng,Wang, Lin,Fu, Wei,Gong, Peng,Wang, Lin,Fu, Wei,Gong, Peng,Clinton, Nicholas E.,Wang, Lin,Qi, Shuhua,Liu, Ying.

[16]Detection of blueberry internal bruising over time using NIR hyperspectral reflectance imaging with optimum wavelengths. Fan, Shuxiang,Huang, Wenqian,Chen, Liping,Fan, Shuxiang,Li, Changying.

[17]Evaluation on Crack Resistance of Watermelon (Citrullus lanatus). Jiang Haikun,Zhang Qian,Fang Lin,Dong Yanxiang,Yan Congsheng,Wang Mingxia,Wang Yan,Yuan Xihan. 2010

[18]The Feasibility and Stability of Distinguishing the Kiwi Fruit Geographical Origin Based on Electronic Nose Analysis. Ma, Yiyan,Guo, Boli,Wei, Yimin,Wei, Shuai,Zhao, Haiyan.

[19]Flavonoid glycosides as floral origin markers to discriminate of unifloral bee pollen by LC-MS/MS. Zhou, Jinhui,Wu, Liming,Li, Yi,Sun, Liping,Zhou, Jinhui,Wu, Liming,Li, Yi,Zhou, Jinhui,Wu, Liming,Li, Yi,Qi, Yitao,Ritho, Joan,Zhang, Yongxin,Zheng, Xiaowei,Sun, Liping.

[20]Differentiation of Chinese robusta coffees according to species, using a combined electronic nose and tongue, with the aid of chemometrics. Dong, Wenjiang,Zhao, Jianping,Hu, Rongsuo,Dong, Yunping,Tan, Lehe,Dong, Wenjiang,Zhao, Jianping,Hu, Rongsuo,Tan, Lehe,Dong, Wenjiang,Zhao, Jianping,Dong, Yunping,Tan, Lehe.

作者其他论文 更多>>

微信小程序