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     Advance Journal of Food Science and Technology


The Study on Food Sensory Evaluation based on Particle Swarm Optimization Algorithm

Hairong Wang and Huijuan Xu
Huanghuai University, Henan, China
Advance Journal of Food Science and Technology  2015  11:772-776
http://dx.doi.org/10.19026/ajfst.8.1605  |  © The Author(s) 2015
Received: November ‎21, ‎2014  |  Accepted: March ‎4, ‎2015  |  Published: July 15, 2015

Abstract

In this study, it explores the procedures and methods of the system for establishing food sensory evaluation based on particle swarm optimization algorithm, by means of explaining the interpretation of sensory evaluation and sensory analysis, combined with the applying situation of sensory evaluation in food industry.

Keywords:

Food industry, food sensory evaluation, particle swarm optimization algorithm,


References

  1. Ampuero, S. and J.O. Bosset, 2003. The electronic nose applied to dairy products: A review. Sensor. Actuat. B-Chem., 94: 1-12.
    CrossRef    
  2. Cai, L.S., J.A. Koziel, Y.C. Lo and S.J. Hoff, 2006. Characterization of volatile organic compounds and odorants associated with swine barn particulate matter using solid-phase microextraction and gas chromatography-mass. J. Chromatogr. A, 1102: 60-72.
    CrossRef    PMid:16297922    
  3. Das, A.K., A.S.R. Anjaneyulu, A.K. Verma and N. Kondaiah, 2008. Physicochemical, textural, sensory characteristics and storage stability of goat meat patties extended with full-fat soy paste and soy granules. Int. J. Food Sci. Technol., 43: 383-392.
    CrossRef    
  4. Foley, D.M., K. Pickett, J. Varon, J. Lee, D.B. Mln and et al., 2002. Pasteurization of fresh orange juice using gamma irradiation: Microbiological, flavor, and sensory analyses. J. Food Sci., 67: 1495-1501.
    CrossRef    
  5. Kennedy, J. and R. Eberhart, 1995. Particle swarm optimization. Proceeding of IEEE International Conference on Neural Network. Perth, Australia, IEEE Service Center, Piscataway, NJ, pp: 1942-1948.
    CrossRef    
  6. Matín, Y.G., J.L.P. Pavón, B.M. Coreno and C.G. Pinto, 1999. Classication of vegetable oils by linear discriminant analysis of electronic nose data. Anal. Chim. Acta, 384: 83-94.
    CrossRef    
  7. Toko, K., 2000. Taste sensor. Sensor. Actuat. B-Chem., 64(3): 205-215.

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2042-4876
ISSN (Print):   2042-4868
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