Optimization of operating conditions in rice heat blast process for Chinese rice wine production by combinational utilization of neural network and genetic algorithms

Journal of the Institute of Brewing

Volumn 110, Issue 2, 2004, Pages 117-123

  Zhu, Yibo ^a   Zhang, Jianhua ^a   Shi, Zhongping ^a   Mao, Zhonggui ^a  

^a JIANGNAN UNIVERSITY   (China)

Author keywords

Artificial neural network; Genetic algorithm; Optimization; Quality control; Rice heat blast process

Indexed keywords

GENETIC ALGORITHMS; HEAT TREATMENT; NEURAL NETWORKS; OPTIMIZATION; QUALITY CONTROL; WINE;

DENATURALIZATION; NUTRIENTS; RICE HEAT BLAST PROCESS;

CROPS;

EID: 3142721922     PISSN: 00469750     EISSN: None     Source Type: Journal    
DOI: 10.1002/j.2050-0416.2004.tb00190.x     Document Type: Article

References (22)

1. Aikiyama, H., Japanese sake, 12th ed., Iwanami Publishing Co., Ltd: Tokyo, Japan, 1996, pp. 148.
2. Chaudhuri, B. and Modak, J.M., Optimization of fed-batch bioreactor using neural network. Bioprocess Eng., 1998, 19, 71-79.
3. Goldberg, D.E., Genetic algorithms in searching, optimizations, and machine learning. Addison-Wesley: Boston MA, 1989.
4. Hanai, T., Honda, H., Ohkusu, E., Tohyama, H., Muramatsu, T. and Kobayashi, T., Application of an artificial neural network and genetic algorithm for determination of process orbits in the Koji making process. J. Biosci. Bioeng., 1999, 87(4), 507-512.
5. Huang, J., Shimizu, H. and Shioya, S., Data preprocessing and output evaluation of an autoassociative neural network model for on-line fault detection in virginiamycin production. J. Biosci. Bioeng., 2002, 94(1), 70-77.
6. Ishihara, N., Shimada, M., Hirai, N., Oya, S., Naito M. and Takayama, T., Heat blast treatment of rice by moisture-bearing method (Japanese). Public patent of Japan, 1991, 292878.
7. Matsuura, K., Shiba, K., Hirotsune, M. and Hamachi, M., Optimizing control of sensory evaluation in the sake mashing process by decentralized learning of fuzzy inferences using a genetic algorithm. J. Biosci. Bioeng., 1995, 80(1), 251-258.
8. McKee, T. and McKee J.R., Biochemistry an introduction, 2nd ed., McGraw-Hill: Columbus, OH, 1999, pp. 93-106.
9. Na, J.G., Chang, Y.K., Chung, B.H. and Lim, H.C., Adaptive optimization of fed-batch culture of yeast by using genetic algorithms. Bioprocess Eng., 2004, 24, 299-308.
10. Nagata, Y. and Chu, K.H., Optimization of a fermentation medium using neural network and genetic algorithms. Biotechnol. Lett., 2003, 25(21), 1834-1842.
11. Nielsen, S., Introduction to the chemical analysis of foods. Jones and Bartlett: Boston, 1994, pp. 183-191.
12. Oishi, K., Tominaga, M., Kawato, A. and Imayasu, S., Analysis of the state characteristics of sake brewing with a neural network. J. Biosci. Bioeng., 1992, 73 1), 153-158.
13. Ramanakoppa, H., Nagaraj and Shipanova I.N., Faust, F.M., Protein cross-linking by the Maillard reaction, J. Biol. Chem., 1996, 271(32), 19338-19345.
14. Ranganath, M., Rengannathan, S. and Gokulnath, C., Identification of bioprocess using genetic algorithms. Bioprocess Eng., 2002, 24, 123-127.
15. Riha, W.E., Izzo, H.V., Zhang, J. and Ho, C.T., Nonenzymatic deamidation of food proteins. Crit. Rev. Food Sci., 1996, 36(3), 225-255.
16. Rumelhart, D.E., Hinton, G.E. and Williams, R.J., Learning representation by back-propagation errors. Nature, 1986, 323, 533-536.
17. Shi, Z. and Shimizu, K., Neuro-fuzzy control of bioreactor system with pattern recognition. J. Biosci. Bioeng., 1992, 74(1), 39-45.
18. Shimizu, K., Bioprocess systems analysis method - the principle of systems analysis method and its application. Corona Publishing Co., Ltd: Tokyo, Japan, 1997, pp. 225.
19. Steyer, J.P., Pelayo-Ortiz, C., Gonzalez-Alvarez, V., Bonnet, B. and Bones, A., Neural network modeling of a depollution process. Bioprocess Eng., 2000, 23, 727-730.
20. Syu, M.J. and Hou, C.L., Neural network predictive control by MIMIS monitored 2,3-butanediol fermentation by Klebsiella oxytoca. Bioprocess Eng., 1999, 21, 141-149.
21. Takayama, T., Sake brewed with polished rice treated by heat blast (Japanese), Nippon Jozo Kyokai Kaishi, 1992, 87(12), 849-857.
22. Tominaga, O., Ito, F., Hanai, H., Honda, H., and Kobayashi T., Sensory modeling of coffee with a fuzzy neural network, J. Food Sci., 2001, 67(1), 363-368.