Evaluation of macro and micronutrient elements content from soft drinks using principal component analysis and Kohonen self-organizing maps

被引:23
|
作者
Silva, Emanuela dos Santos [1 ]
Paranhos da Silva, Erik Galvao [2 ]
Silva, Danielen dos Santos [1 ]
Novaes, Cleber Galvao [1 ]
Carqueija Amorim, Fabio Alan [2 ]
Silva dos Santos, Marcio Jose [1 ]
Bezerra, Marcos Almeida [1 ]
机构
[1] Univ Estadual Sudoeste Bahia, Dept Ciencias & Tecnol, Campus Jequie,Rua Jose Moreira Sobrinho S-N, BR-45208091 Jequie, BA, Brazil
[2] Univ Estadual Santa Cruz, Dept Ciencias Exatas & Tecnol, Campus Soane Nazare de Andrade,Km 16 BR 415, BR-45662900 Ilheus, BA, Brazil
关键词
Soft drinks; Kohonen maps; Neural network; Principal component analysis; Elemental analysis; ICP OES; SPME-GC-MS; CLASSIFICATION; CHEMOMETRICS; OILS; SPECTROSCOPY; VARIETIES; BEVERAGES; SPECTRA; METALS;
D O I
10.1016/j.foodchem.2018.06.021
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
This study approaches the determination of nine elements from Brazilian carbonated soft drinks of several flavors and manufactures using inductively coupled plasma optical emission spectrometry (ICP OES). The concentrations of the elements varied as follows: (in mu g L-1: Cu: 4.00-78.0; Fe: 74.0-506; Mn: 20.0-66.0; Zn: 104-584) and (in mg L-1: Ca: 4.81-16.2; K: 6.73-260; Na: 26.0-175; S: 1.43-5.41; P: 0.186-219). Principal component analysis has shown some tendencies to form two groups according to the drink flavor (orange and cola), but only cola presented a clear and complete separation. Using Kohonen maps, it was observed a tendency to form three flavor groups: (i) cola, (ii) orange and lemon, and (iii) guarana. However, this last tool proved to be more accurate in the groups' formation.
引用
收藏
页码:9 / 14
页数:6
相关论文
共 50 条
  • [31] The influence function of principal component analysis by self-organizing rule
    Higuchi, I
    Eguchi, S
    [J]. NEURAL COMPUTATION, 1998, 10 (06) : 1434 - 1444
  • [32] Influence function of principal component analysis by self-organizing rule
    Higuchi, Isao
    Eguchi, Shinto
    [J]. Neural Computation, 1998, 10 (06):
  • [33] Regional analysis using self-organizing maps
    Chudy, L
    Farkas, I
    [J]. POLITICKA EKONOMIE, 2000, 48 (05) : 685 - 697
  • [34] Clustering of participants in the MaxBonus loyalty system using Kohonen's self-organizing maps
    Dorrer, M. G.
    Fomin, A., V
    Loginov, D. A.
    [J]. II INTERNATIONAL SCIENTIFIC CONFERENCE ON APPLIED PHYSICS, INFORMATION TECHNOLOGIES AND ENGINEERING 25, PTS 1-5, 2020, 1679
  • [35] CONNECTED COMPONENT LABELING USING SELF-ORGANIZING FEATURE MAPS
    BARAGHIMIAN, GA
    [J]. PROCEEDINGS : THE THIRTEENTH ANNUAL INTERNATIONAL COMPUTER SOFTWARE & APPLICATIONS CONFERENCE, 1989, : 680 - 684
  • [36] Regionalization of the Onset and Offset of the Rainy Season in Senegal Using Kohonen Self-Organizing Maps
    Faye, Dioumacor
    Kaly, Francois
    Dieng, Abdou Lahat
    Wane, Dahirou
    Fall, Cheikh Modou Noreyni
    Mignot, Juliette
    Gaye, Amadou Thierno
    [J]. ATMOSPHERE, 2024, 15 (03)
  • [37] Clustering of volcanic ash arising from different fragmentation mechanisms using Kohonen self-organizing maps
    Ersoy, Orkun
    Aydar, Erkan
    Gourgaud, Alain
    Artuner, Harun
    Bayhan, Hasan
    [J]. COMPUTERS & GEOSCIENCES, 2007, 33 (06) : 821 - 828
  • [38] Map matching Using De-Noise Interpolation Kohonen Self-Organizing Maps
    Du, Zhanwei
    Yang, Yongjian
    Sun, Yongxiong
    Zhang, Chijun
    [J]. COMPONENTS, PACKAGING AND MANUFACTURING TECHNOLOGY, 2011, 460-461 : 680 - 686
  • [39] Mapping energy sustainability using the Kohonen self-organizing maps-Case study
    Vlaovic, Zeljko D.
    Stepanov, Borivoj Lj.
    Andelkovic, Aleksandar S.
    Rajs, Vladimir M.
    Cepic, Zoran M.
    Tomic, Mladen A.
    [J]. JOURNAL OF CLEANER PRODUCTION, 2023, 412
  • [40] Evaluation of principal component analysis for seismic attribute selection and self-organizing maps for seismic facies discrimination in the presence of gas hydrates
    Lubo-Robles, David
    Bedle, Heather
    Marfurt, Kurt J.
    Pranter, Matthew J.
    [J]. MARINE AND PETROLEUM GEOLOGY, 2023, 150