Identification of liquors from the same brand based on ultraviolet, near-infrared and fluorescence spectroscopy combined with chemometrics.

Journal: Food chemistry
PMID: 36084593

Abstract

Accurate identification of various liquors from the same brand is of great significance for safeguarding the rights and interests of consumers and the market economy. Here, the spectral properties of liquors were studied based on ultraviolet (UV), near-infrared (NIR) and multi-way fluorescence spectroscopy. Then these liquors were distinguished by integrating their spectral properties with the chemometrics such as Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), and Backpropagation Neural Networks (BPNN). To improve the accuracy, sensitivity, and specificity of the liquor identification, a four-way fluorescence spectrum data array was constructed by adding three acid-sensitive quantum dots (QDs) as an additional dimension. Combined with mid-level data fusion, this strategy can identify liquors from the same brand with the accuracy, sensitivity, and specificity of 99.17%, 99.15%, and 99.96%. In addition, an automated analysis platform based on MATLAB App Designer was developed to improve the efficiency of spectral data modeling.

Authors

  • Miao He
    Department of Ultrasonic Medicine, Fetal Medical Center, First Affiliated Hospital of Sun Yat-sen University, Zhongshan Er Road 58, Guangzhou, 510080, Guangdong, China.
  • Xiaolong Chen
    Department of Orthopedics & Elderly Spinal Surgery, Xuanwu Hospital of Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China.
  • Jing Zhang
    MOEMIL Laboratory, School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu, China.
  • Jiawei Li
    School of Chemistry & Chemical Engineering, College of Guangling, Yangzhou University Yangzhou 225002 PR China zhuxiashi@sina.com.
  • Dong Zhao
    Collaborative Innovation Center of Judicial Civilization, Key Laboratory of Evidence Science, Ministry of Education, China University of Political Science and Law, Beijing 100088, China.
  • Yang Huang
    School of Computer and Electronic Information, Nanjing Normal University, Nanjing 210023, China.
  • Danqun Huo
    Key Laboratory for Biorheological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing 400044, PR China.
  • Xiaogang Luo
    Key Laboratory for Biorheological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing 400044, PR China. Electronic address: luosteel@cqu.edu.cn.
  • Changjun Hou
    Key Laboratory for Biorheological Science and Technology of Ministry of Education, Bioengineering College of Chongqing University, Chongqing 400044, PR China; Chongqing Key Laboratory of Bio-perception & Intelligent Information Processing, School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, PR China. Electronic address: houcj@cqu.edu.cn.

Keywords

External Resources

Popular Topics
Recent Journals