您好，欢迎访问北京市农林科学院 机构知识库！
北京市农林科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Rapid determination of biogenic amines in cooked beef using hyperspectral imaging with sparse representation algorithm

文献类型： 外文期刊

作者： Yang, Dong 1 ; Lu, Anxiang 1 ; Ren, Dong 3 ; Wang, Jihua 1 ;

作者机构： 1.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Agr Stand & Testing, Beijing 100097, Peoples R China

2.Shenyang Agr Univ, Coll Informat & Elect Engn, Shenyang 110866, Liaoning, Peoples R China

3.Collaborat Innovat Ctr Key Technol Smart Irrigat, Yichang 443002, Hubei, Peoples R China

4.Beijing Municipal Key Lab Agr Environm Monitoring, Beijing 100097, Peoples R China

关键词： Hyperspectral imaging;Cooked beef;Sparse representation;Biogenic amine;PCA

期刊名称：INFRARED PHYSICS & TECHNOLOGY （ 影响因子：2.638； 五年影响因子：2.581 ）

ISSN： 1350-4495

年卷期： 2017 年 86 卷

页码：

收录情况： SCI

摘要： This study explored the feasibility of rapid detection of biogenic amines (BAs) in cooked beef during the storage process using hyperspectral imaging technique combined with sparse representation (SR) algorithm. The hyperspectral images of samples were collected in the two spectral ranges of 400-1000 nm and 1000-1800 nm, separately. The spectral data were reduced dimensionality by SR and principal component analysis (PCA) algorithms, and then integrated the least square support vector machine (LS-SVM) to build the SR-LS-SVM and PC-LS-SVM models for the prediction of BAs values in cooked beef. The results showed that the SR-LS-SVM model exhibited the best predictive ability with determination coefficients R-P(2),) of 0.943 and root mean square errors (RMSEP) of 1.206 in the range of 400-1000 nm of prediction set. The SR and PCA algorithms were further combined to establish the best SR-PC-LS-SVM model for BAs prediction, which had high R-P(2), of 0.969 and low RMSEP of 1.039 in the region of 400-1000 nm. The visual map of the BAs was generated using the best SR-PC-LS-SVM model with imaging process algorithms, which could be used to observe the changes of BAs in cooked beef more intuitively. The study demonstrated that hyperspectral imaging technique combined with sparse representation were able to detect effectively the BAs values in cooked beef during storage and the built SR-PC-LS-SVM model had a potential for rapid and accurate determination of freshness indexes in other meat and meat products. (C) 2017 Elsevier B.V. All rights reserved.

  • 相关文献

[1]Combination of spectral and textural information of hyperspectral imaging for the prediction of the moisture content and storage time of cooked beef. Yang, Dong,Lu, Anxiang,Wang, Jihua,Yang, Dong,Wang, Jihua,He, Dandan,Lu, Anxiang,Ren, Dong,Wang, Jihua,Lu, Anxiang,Wang, Jihua. 2017

[2]Detection of the Freshness State of Cooked Beef During Storage Using Hyperspectral Imaging. Yang, Dong,Wang, Jihua,He, Dandan,Lu, Anxiang,Ren, Dong,Wang, Jihua,Lu, Anxiang,Wang, Jihua,Lu, Anxiang,Wang, Jihua.

[3]8个草莓品种(系)果实特征香气成分比较分析. 王娟,孙瑞,王桂霞,常琳琳,孙健,钟传飞,董静,张运涛,Detlef.ULRICH. 2018

[4]AN IDENTIFICATION OF THE GROWING AREA OF LONGJING TEA BASED ON THE FISHER'S DISCRIMINANT ANALYSIS WITH THE COMBINATION OF PRINCIPAL COMPONENTS ANALYSIS. Jia, Wenshen,Wu, Wenfu,Wang, Jihua,Jia, Wenshen,Ma, Zhihong,Wang, Dong,Wang, Jihua,Jia, Wenshen,Lan, Yubin. 2013

[5]Application of Fourier Transform Infrared Spectroscopy in Identification of Wine Spoilage. Zhao Xian-de,Dong Da-ming,Zheng Wen-gang,Jiao Lei-zi,Lang Yun. 2014

[6]AN IMPROVED PCA FUSION METHOD BASED ON GENERALIZED INTENSITY-HUE-SATURATION FUSION TECHNIQUE. Ren, Dong,Liu, Yanmei,Yu, Haiyang,Liu, Yanmei,Yang, Xiaodong,Wang, Jihua,Yu, Haiyang. 2012

[7]Characterization of Free, Conjugated, and Bound Phenolic Acids in Seven Commonly Consumed Vegetables. Gao, Yuan,Ma, Shuai,Wang, Meng,Feng, Xiao-Yuan,Gao, Yuan,Ma, Shuai,Wang, Meng,Feng, Xiao-Yuan. 2017

[8]Volatile characteristics of 50 peaches and nectarines evaluated by HP-SPME with GC-MS. Wang, Yiju,Li, Shaohua,Wang, Yiju,Yang, Chunxiang,Yang, Liu,Wang, Younian,Zhao, Jianbo,Jiang, Quan,Wang, Yiju.

[9]Detection of Pesticide (Chlorpyrifos) Residues on Fruit Peels Through Spectra of Volatiles by FTIR. Xiao, Guangdong,Dong, Daming,Zheng, Ling,Zhao, Chunjiang,Xiao, Guangdong,Liao, Tongqing,Zhang, Dongyan,Li, Yang.

[10]Detection of Early Rottenness on Apples by Using Hyperspectral Imaging Combined with Spectral Analysis and Image Processing. Zhang, Baohua,Fan, Shuxiang,Li, Jiangbo,Huang, Wenqian,Zhao, Chunjiang,Qian, Man,Zheng, Ling,Zhang, Baohua,Zhao, Chunjiang.

[11]Prediction of soluble solids content of apple using the combination of spectra and textural features of hyperspectral reflectance imaging data. Fan, Shuxiang,Zhang, Baohua,Li, Jiangbo,Liu, Chen,Huang, Wenqian,Tian, Xi,Fan, Shuxiang,Zhang, Baohua,Li, Jiangbo,Liu, Chen,Huang, Wenqian,Tian, Xi,Fan, Shuxiang,Zhang, Baohua,Li, Jiangbo,Liu, Chen,Huang, Wenqian,Tian, Xi,Fan, Shuxiang,Zhang, Baohua,Li, Jiangbo,Liu, Chen,Huang, Wenqian,Tian, Xi.

[12]Multispectral detection of skin defects of bi-colored peaches based on vis-NIR hyperspectral imaging. Li, Jiangbo,Chen, Liping,Huang, Wenqian,Wang, Qingyan,Zhang, Baohua,Tian, Xi,Li, Bin,Li, Jiangbo,Chen, Liping,Huang, Wenqian,Wang, Qingyan,Tian, Xi,Fan, Shuxiang,Li, Bin,Li, Jiangbo,Chen, Liping,Huang, Wenqian,Li, Jiangbo,Chen, Liping,Huang, Wenqian.

[13]Development of a multispectral imaging system for online detection of bruises on apples. Huang, Wenqian,Li, Jiangbo,Wang, Qingyan,Chen, Liping.

[14]Prediction of Soluble Solids Content and Firmness of Pears Using Hyperspectral Reflectance Imaging. Fan, Shuxiang,Huang, Wenqian,Guo, Zhiming,Zhang, Baohua,Zhao, Chunjiang,Fan, Shuxiang,Zhao, Chunjiang.

[15]Hyperspectral classification for identifying decayed oranges infected by fungi. Yin, Shiyang,Gu, Xiaomin,Xiao, Yong,Bi, Xiaoqing,Niu, Yong. 2017

[16]Vertical features of yellow rust infestation on winter wheat using hyperspectral imaging measurements. Zhao, Jinling,Zhang, Dongyan,Huang, Linsheng,Zhang, Qing,Liu, Wenjing,Yang, Hao. 2016

[17]Detection of Wheat Powdery Mildew by Differentiating Background Factors using Hyperspectral Imaging. Zhang, Dongyan,Zhang, Lifu,Zhang, Dongyan,Wang, Xiu,Zhang, Dongyan,Wang, Xiu,Lin, Fenfang,Huang, Yanbo. 2016

[18]Geographical classification of apple based on hyperspectral imaging. Guo, Zhiming,Huang, Wenqian,Chen, Liping,Zhao, Chunjiang. 2013

[19]Recognition of wheat preharvest sprouting based on hyperspectral imaging. Wu, Qiong,Wang, Jihua,Wu, Qiong,Zhu, Dazhou,Wang, Cheng,Ma, Zhihong,Wang, Jihua. 2012

[20]Identification of seedling cabbages and weeds using hyperspectral imaging. Wei, Deng,Zhao Chunjiang,Xiu, Wang,Huang, Yanbo,Wei, Deng,Zhao Chunjiang,Xiu, Wang,Wei, Deng,Zhao Chunjiang,Xiu, Wang,Wei, Deng,Zhao Chunjiang,Xiu, Wang. 2015

作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：北京市农林科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台