Improving microbial growth prediction by product unit neural networks

Journal of Food Science

Volumn 71, Issue 2, 2006, Pages

  Hervás Martínez, Cesar ^a   García Gimeno, Rosa M ^a   Martínez Estudillo, Alfonso C ^a   Martínez Estudillo, Francisco J ^a   Zurera Cosano, Gonzalo ^a  

^a UNIVERSITY OF CÓRDOBA   (Spain)

Author keywords

Artificial neural networks; Growth model; Leuconostoc mesenteroides; Product units; Spoilage bacteria

Indexed keywords

BACTERIA (MICROORGANISMS); LEUCONOSTOC MESENTEROIDES;

EID: 33645367815     PISSN: 00221147     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1365-2621.2006.tb08904.x     Document Type: Article

References (33)

1. Arinder P, Borch E. 1999. Validation of mathematical models for predicting growth of Pseudomonas spp. Predictive microbiology applied to chilled food preservation. In: Refrigeration Science and Technology Proceedings. p 185-93.
2. Dalgaard P. 2000. Fresh and lightly preserved seafood. In: Man CMD, Jones AA, editors. Shelf life evaluation of foods. 2nd ed, Md.: Aspen Publishing. p 110-39.
3. Durbin R, Rumelhart D. 1989. Product units: a computationally powerful and biologically plausible extension to backpropagation networks. Neural Comput 1:133-42.
4. García-Gimeno RM, Hervás-Martínez C, Barco-Alcalá E, Zurera-Cosano G, Sanz-Tapia E. 2003. An artificial neural network approach to Escherichia cali O157:H7 growth estimation. J Food Sci 68:639-45.
5. García-Gimeno RM, Hervás-Martínez C, de Silóniz MI. 2002. Improving artificial neural networks with a pruning methodology and genetic algorithms for their application in microbial growth prediction in food. Int J Food Microbiol 72:19-30.
6. García-Gimeno RM, Hervás-Martínez C, Rodríguez-Pérez R, Zurera-Cosano G. 2005. Modelling the growth of Leuconostoc mesenteroides by artificial neural networks. Int J Food Microbiol 105:317-32.
7. Geeraerd A, Herremans C, Cenens C, Van Impe J. 1998. Applications of artificial neural networks as a non-linear modular modeling technique to describe bacterial growth in chilled food products. Int J Food Microbiol 44:49-68.
8. Gibson A, Bratchell N, Roberts T. 1988. Predicting microbial growth: growth responses of salmonellae in a laboratory medium affected by pH, sodium chloride and storage temperature. Int J Food Microbiol 6:155-78.
9. Gurney KN. 1992. Training nets of hardware realizable sigma-pi units. Neural Networks 5(2):289-303.
10. Hajmeer M, Basheer I, Najjar Y. 1997. Computational neural networks for predictive microbiology. II. Application to microbial growth. Int J Food Microbiol 34:51-66.
11. Hervás C, Zurera G, García-Gimeno RM, Martínez JA. 2001. Optimisation of computational neural network for its application to the prediction of microbial growth in foods. Food Sci Technol Int 7:159-63.
12. Ismail A, Engelbrecht AP. 1999. Training product units in feedforward neural networks using particle swarm optimization. Development and practice of artificial intelligence techniques. In: Bajic VB, Sha D, editors. Proceedings of the Intl. Conference on Artificial Intelligence; Sept 1999; Durban, South Africa. p 36-40.
13. Ismail AA, Engelbrecht AP. 2000. Global optimisation algorithms for training product unit neural networks. Institute of Electrical and Electronics Engineers (IEEE). International Joint Conference on Neural Networks; July 24-7, 2000; Como, Italy. Paper 032.
14. Janson DJ, Frenzel JF. 1993. Training product unit neural networks with genetic algorithms. Institute of Electrical and Electronics Engineers (IEEE) Intelligent Systems 8(5):26-33.
15. Jeyamkondan S, Jayas D, Holley R. 2001. Microbial growth modeling with artificial neural networks. Int J Food Microbiol 64:343-54.
16. Lebert I, Robles-Olvera V, Lebert A. 2000. Application of polynominal models to predict growth of mixed cultures of Pseudomonas spp. and Listeria in meat. Int J Food Microbiol 61:27-39.
17. Leerink LR, Giles CL, Horne BG, Jabri MA. 1995. Learning with product units. Tesauro G, Touretzky D, editors. In: Advances in neural information processing systems 7. Cambridge, Mass.: MIT Press. p 537-44.
18. Levenberg K. 1944. A method for solution of certain non-linear problems in least squares. Q J Appl Math II 2:164-8.
19. Lou W, Nakai S. 2001. Artificial neural network based predictive model for bacterial growth in a simulated medium of modified-atmosphere-packed cooked meat products. J Agric Food Chem 49:1799-804.
20. Marquardt DW. 1963. An algorithm for least-squares estimation of non-linear parameters. J Soc Ind Appl Math 11(2):431-41.
21. Martínez AC, Martínez FJ, García N, Hervás C. 2002. Modelado de Sistemas mediante modelos híbridos de redes neuronales y computación evolutiva. Garijo F, Riquelme JC, Toro M, editors. Workshop Aprendizaje y minería de datos. Iberamia 2002; Nov 12-5, 2002; Seville, Spain. p 67-76.
22. Martínez-Estudillo AC, Martínez FJ, Estudillo M, Hervás C, García N. 2005. Model fitting by evolutionary computation using product units. Neural Netwoks (Forthcoming).
23. McCann TL, Eifert JD, Gennings C, Schilling MW, Carter WH. 2003. A predictive model with repeated measures analysis of Staphylococcus aureus growth data. Food Microbiol 20:139-47.
24. Nauta MJ, Litman S, Barker GC, Carlin F. 2003. A retail and consumer phase model for exposure assessment of Bacillus cereus. Int J Food Microbiol 83:205-18.
25. Neumeyer K, Ross T, Thomson G, McMeekin TA. 1997. Validation of a model describing the effects of temperature and water activity on the growth of psychrotrophic pseudomonads. Int J Food Microbiol 38:55-63.
26. Robinson TP, Ocio MJ, Kaloti A, Mackey BM. 1998. The effect of the growth environment on the Lag phase of Listeria monocytogenes. Int J Food Microbiol 44:83-92.
27. Ross T. 1996. Indices for performance evaluation of predictive models in food microbiology. J Appl Bacteriol 81:501-8.
28. Ross T, Dalgaard P., Tienungoon S. 2000. Predictive modeling of the growth and survival of Listeria in fishery products. Int J Food Microbiol 62:231-45.
29. Setieno R, Leow WK, Zurada JM. 2002. Extraction of rules from artificial neural networks for nonlinear regression. IEEETrans Neural Networks 13:564-77.
30. Valík L, Pieckova E. 2001. Growth modeling of heat-resistant fungi: the effect of water activity. Int J Food Microbiol 63:11-7.
31. Van Impe JF, Versyck KJ, Geeraerd AH. 1998. Validation of predictive models: definitions and concepts. In: COST 914. Predictive modeling of microbial growth and survival in foods. Brussels: Luxembourg Commission. p 31-8.
32. Zurera-Cosano G, Castillejo-Rodríguez AM, García-Gimeno RM, Rincón-León F. 2004. Response surface vs Davey model for the estimation of Staphylococcus aureus growth under different experimental conditions. J Food Protect 67:1138-45.
33. Zurera-Cosano G, García-Gimeno RM, Rodríguez-Pérez MR, Hervás Martínez C. 2005. Performance of Response Surface model for prediction of Leuconostoc mesenteroides growth parameters under different experimental conditions. Food Control 17:429-38.