Determination of Odour Interactions of Three-Component Gas Mixtures Using an Electronic Nose

被引:45
|
作者
Szulczynski, Bartosz [1 ]
Namiesnik, Jacek [2 ]
Gebicki, Jacek [1 ]
机构
[1] Gdansk Univ Technol, Dept Chem & Proc Engn, Fac Chem, 11-12 G Narutowicza Str, PL-80233 Gdansk, Poland
[2] Gdansk Univ Technol, Dept Analyt Chem, Fac Chem, 11-12 G Narutowicza Str, PL-80233 Gdansk, Poland
关键词
electronic nose; odour interactions; principal component regression; odour intensity; hedonic tone; PREDICTING ORGANOLEPTIC SCORES; PPM FLAVOR NOTES; INTENSITY; CLASSIFICATION; BIOFILTRATION; COMPOSTS; TONGUES; SENSORS; ARRAY; MS;
D O I
10.3390/s17102380
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The paper presents an application of an electronic nose prototype comprised of six TGS-type sensors and one PID-type sensor to identify odour interaction phenomena in odorous three-component mixtures. The investigation encompassed eight odorous mixturestoluene-acetone-triethylamine and formaldehyde-butyric acid-pinenecharacterized by different odour intensity and hedonic tone. A principal component regression (PCR) calibration model was used for evaluation of predicted odour intensity and hedonic tone. Correctness of identification of odour interactions in the odorous three-component mixtures was determined based on the results obtained with the electronic nose. The results indicated a level of 75-80% for odour intensity and 57-73% for hedonic tone. The average root mean square error of prediction amounted to 0.03-0.06 for odour intensity determination and 0.07-0.34 for hedonic tone evaluation of the odorous three-component mixtures.
引用
收藏
页数:18
相关论文
共 50 条
  • [41] Towards Gas Identification in Unknown Mixtures Using an Electronic Nose with One-Class Learning
    Fan, Han
    Jonsson, Daniel
    Schaffernicht, Erik
    Lilienthal, Achim J.
    2022 IEEE INTERNATIONAL SYMPOSIUM ON OLFACTION AND ELECTRONIC NOSE (ISOEN 2022), 2022,
  • [42] Detection of Hazardous Gas Mixtures in the Smart Kitchen Using an Electronic Nose with Support Vector Machine
    Zhang, Junyu
    Xue, Yingying
    Zhang, Tao
    Chen, Yuantao
    Wei, Xinwei
    Wan, Hao
    Wang, Ping
    JOURNAL OF THE ELECTROCHEMICAL SOCIETY, 2020, 167 (14)
  • [43] Structure and effective interactions in three-component hard sphere liquids
    König, Anja
    Ashcroft, N.W.
    Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 2001, 63 (4 I): : 412031 - 412039
  • [44] MONITORING ODOUR EMISSSIONS FROM AN OIL & GAS PLANT: ELECTRONIC NOSE PERFORMANCE TESTING IN THE FIELD
    Capelli, Laura
    Sironi, Selena
    2017 ICOCS/IEEE INTERNATIONAL SYMPOSIUM ON OLFACTION AND ELECTRONIC NOSE (ISOEN 2017), 2017,
  • [45] Two-Dimensional Melting of Two- and Three-Component Mixtures
    Li, Yan-Wei
    Yao, Yugui
    Ciamarra, Massimo Pica
    PHYSICAL REVIEW LETTERS, 2023, 130 (25)
  • [46] GRAPHICAL INTERPOLATION METHOD FOR KINETIC-ANALYSIS OF THREE-COMPONENT MIXTURES
    CONNORS, KA
    ANALYTICAL CHEMISTRY, 1977, 49 (12) : 1650 - 1655
  • [47] Subsurface stress field determination using multiplets in downhole three-component microseismic measurement
    Moriya, H
    Niitsuma, H
    Rutledge, JT
    Kaieda, H
    ROCK MECHANICS TOOLS AND TECHNIQUES, VOLS 1 AND 2, 1996, : 853 - 858
  • [48] A novel algorithm for resolution of three-component mixtures of fluorophores by fluorescence quenching
    Witek, Lukasz J.
    Turek, Andrzej M.
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2017, 160 : 77 - 90
  • [49] Magnetic ordering of three-component ultracold fermionic mixtures in optical lattices
    Sotnikov, Andrii
    Hofstetter, Walter
    PHYSICAL REVIEW A, 2014, 89 (06):
  • [50] Heat-conduction microsensor based on silicon technology for the analysis of two- and three-component gas mixtures
    Pollak-Diener, Gerhard
    Obermeier, E.
    Sensors and Actuators, B: Chemical, 1993, B13 (1 -3 pt 1) : 345 - 347