Comparison of Arrhenius model and artificial neuronal network for the quality prediction of rainbow trout (Oncorhynchus mykiss) fillets during storage at different temperatures

LWT

Volumn 60, Issue 1, 2015, Pages 142-147

  Liu, Xiaochang ^a   Jiang, Yan ^a   Shen, Song ^a   Luo, Yongkang ^a   Gao, Liang ^b  

^a CHINA AGRICULTURAL UNIVERSITY   (China)

^b Beijing Fisheries Research Institute   (China)

Author keywords

Arrhenius model; Artificial neuronal network; Quality changes; Rainbow trout fillets

Indexed keywords

FORECASTING; NEURONS;

ARRHENIUS MODELS; ARTIFICIAL NEURONAL NETWORK; COMPARATIVE STUDIES; ELECTRICAL CONDUCTIVITY; EXPERIMENTAL VALUES; QUALITY CHANGE; RAINBOW TROUT; RAINBOW TROUTS (ONCORHYNCHUS MYKISS);

NEURAL NETWORKS;

ONCORHYNCHUS MYKISS;

EID: 84921949203     PISSN: 00236438     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.lwt.2014.09.030     Document Type: Article

References (33)

1. Arashisar Ş., Hisar O., Kaya M., Yanik T. Effects of modified atmosphere and vacuum packaging on microbiological and chemical properties of rainbow trout (Oncorynchus mykiss) fillets. International Journal of Food Microbiology 2004, 97(2):209-214.
2. Bao Y., Zhou Z., Lu H., Luo Y., Shen H. Modelling quality changes in Songpu mirror carp (Cyprinus carpio) fillets stored at chilled temperatures: comparison between Arrhenius model and log-logistic model. International Journal of Food Science & Technology 2013, 48(2):387-393.
3. Boekel M. Statistical aspects of kinetic modeling for food science problems. Journal of Food Science 1996, 61(3):477-486.
4. Byrne C., Troy D., Buckley D. Postmortem changes in muscle electrical properties of bovine M.longissimus dorsi and their relationship to meat quality attributes and pH fall. Meat Science 2000, 54(1):23-34.
5. Cakli S., Kilinc B., Dincer T., Tolasa S. Comparison of the shelf lifes of map and vacuum packaged hot smoked rainbow trout (Onchoryncus mykiss). European Food Research and Technology 2006, 224(1):19-26.
6. Christiansen R., Struksnæs G., Estermann R., Torrissen O. Assessment of flesh colour in Atlantic salmon, Salmo salar L. Aquaculture Research 1995, 26(5):311-321.
7. Chytiri S., Chouliara I., Savvaidis I., Kontominas M. Microbiological, chemical and sensory assessment of iced whole and filleted aquacultured rainbow trout. Food Microbiology 2004, 21(2):157-165.
8. Corzo O., Bracho N., Marjal J. Color change kinetics of sardine sheets during vacuum pulse osmotic dehydration. Journal of Food Engineering 2006, 75(1):21-26.
9. Ekanem E., Achinewhu S. Effects of shucking method on opening, meat yield and selected quality parameters of West African clam, Galatea paradoxa (born). Journal of Food Processing and Preservation 2000, 24(5):365-377.
10. Erenturk S., Erenturk K. Comparison of genetic algorithm and neural network approaches for the drying process of carrot. Journal of Food Engineering 2007, 78(3):905-912.
11. Guizani N., Al-Busaidy M.A., Al-Belushi I.M., Mothershaw A., Rahman M.S. The effect of storage temperature on histamine production and the freshness of yellowfin tuna (Thunnus albacares). Food Research International 2005, 38(2):215-222.
12. Hansen L.T., Gill T., Røntved S.D., Huss H.H. Importance of autolysis and microbiological activity on quality of cold-smoked salmon. Food Research International 1996, 29(2):181-188.
13. Hultmann L., Rustad T. Iced storage of Atlantic salmon (Salmo salar) - effects on endogenous enzymes and their impact on muscle proteins and texture. Food Chemistry 2004, 87(1):31-41.
14. Kaymak-Ertekin F., Gedik A. Kinetic modelling of quality deterioration in onions during drying and storage. Journal of Food Engineering 2005, 68(4):443-453.
15. Kerdpiboon S., Kerr W.L., Devahastin S. Neural network prediction of physical property changes of dried carrot as a function of fractal dimension and moisture content. Food Research International 2006, 39(10):1110-1118.
16. Lepetit J., Sale P., Favier R., Dalle R. Electrical impedance and tenderisation in bovine meat. Meat Science 2002, 60(1):51-62.
17. Llave Y.A., Hagiwara T., Sakiyama T. Artificial neural network model for prediction of cold spot temperature in retort sterilization of starch-based foods. Journal of Food Engineering 2012, 109(3):553-560.
18. Lu H., Zheng H., Lou H., Jiang L., Chen Y., Fang S. Using neural networks to estimate the losses of ascorbic acid, total phenols, flavonoid, and antioxidant activity in asparagus during thermal treatments. Journal of Agricultural and Food Chemistry 2010, 58(5):2995-3001.
19. Lyhs U., Lahtinen J., Fredriksson-Ahomaa M., Hyytiä-Trees E., Elfing K., Korkeala H. Microbiological quality and shelf-life of vacuum-packaged 'gravad' rainbow trout stored at 3 and 8 C. International Journal of Food Microbiology 2001, 70(3):221-230.
20. Marini F. Artificial neural networks in foodstuff analyses: trends and perspectives a review. Analytica Chimica Acta 2009, 635(2):121-131.
21. Mørkøre T., Rødbotten M., Vogt G., Fjæra S.O., Kristiansen I.Ø., Manseth E. Relevance of season and nucleotide catabolism on changes in fillet quality during chilled storage of raw Atlantic salmon (Salmo salar L.). Food Chemistry 2010, 119(4):1417-1425.
22. Ojagh S.M., Rezaei M., Razavi S.H., Hosseini S.M.H. Effect of chitosan coatings enriched with cinnamon oil on the quality of refrigerated rainbow trout. Food Chemistry 2010, 120(1):193-198.
23. Olafsdottir G., Martinsdóttir E., Oehlenschläger J., Dalgaard P., Jensen B., Undeland I., et al. Methods to evaluate fish freshness in research and industry. Trends in Food Science & Technology 1997, 8(8):258-265.
24. Özogul F., Taylor K., Quantick P., Özogul Y. Chemical, microbiological and sensory evaluation of Atlantic herring (Clupea harengus) stored in ice, modified atmosphere and vacuum pack. Food Chemistry 2000, 71(2):267-273.
25. Ratkowsky D., Olley J., McMeekin T., Ball A. Relationship between temperature and growth rate of bacterial cultures. Journal of Bacteriology 1982, 149(1):1-5.
26. Saito T., Arai K., Matsuyoshi M. Anew method for estimating the freshness of fish. Bulletin of the Japanese Society of Scientific Fisheries 1959, 24(9):749-750.
27. Sofu A., Ekinci F. Estimation of storage time of yogurt with artificial neural network modeling. Journal of Dairy Science 2007, 90(7):3118-3125.
28. Song Y., Liu L., Shen H., You J., Luo Y. Effect of sodium alginate-based edible coating containing different anti-oxidants on quality and shelf life of refrigerated bream (Megalobrama amblycephala). Food Control 2011, 22(3):608-615.
29. Tsironi T., Dermesonlouoglou E., Giannakourou M., Taoukis P. Shelf life modelling of frozen shrimp at variable temperature conditions. LWT - Food Science and Technology 2009, 42(2):664-671.
30. Tsironi T., Salapa I., Taoukis P. Shelf life modelling of osmotically treated chilled gilthead seabream fillets. Innovative Food Science & Emerging Technologies 2009, 10(1):23-31.
31. Yao L., Luo Y., Sun Y., Shen H. Establishment of kinetic models based on electrical conductivity and freshness indictors for the forecasting of cruciancarp (Carassius carassius) freshness. Journal of Food Engineering 2011, 107(2):147-151.
32. Zhang L., Li X., Lu W., Shen H., Luo Y. Quality predictive models of grass carp (Ctenopharyngodon idellus) at different temperatures during storage. Food Control 2011, 22(8):1197-1202.
33. Zhu S., Luo Y., Hong H., Feng L., Shen H. Correlation between electrical conductivity of the gutted fish body and the quality of bighead carp (Aristichthys nobilis) heads stored at 0 and 3°C. Food and Bioprocess Technology 2013, 6(11):3068-3075.