Research Article
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Development of prediction models to estimate the total number of mesophilic aerobic and lactic acid bacteria of squid rings that were cooked before marinating

Year 2022, Volume: 39 Issue: 4, 316 - 325, 15.12.2022

Berna Kılınç Fevziye Nihan Bulat Sevcan Demir Atalay

https://doi.org/10.12714/egejfas.39.4.07

Abstract


This study was conducted in order to develop different statistical models for estimating the bacterial count of squid rings marinated with lemon juice and mineral water after cooking. The marination ratios and times were as follows: (10:90; 90:10; 50:50; 100:100/100 g squid ring) and (1, 3, 6, 12, 24, 48 and 72 h), respectively. The effects of marination ratios and times on the microbiological and sensory changes of the cooked squid rings were observed at 4°C. Pathogenic bacteria (Vibrio spp., Staphylococcus aureus and Escherichia coli) were not found in the cooked (C) and cooked marinated (CM) squid rings in the present study. The TMC (total mesophilic aerobic bacteria counts) of all groups were determined as consumable at 72 h, whereas the TMC of C and CM samples (C7, CM7, CM14, CM21, CM28) increased to 5.92, 5.83, 5.71, 5.57 and 5.42 log cfu/g, respectively. Regression models were created to estimate the TMC and lactic acid bacteria count (LBC) of cooked squid rings during the marination process at 4°C to determine the increasing rates of bacterial growth of samples. As a result of this study; when compared with Model I and Model II; both of them can be preferred for predicting the TMC of C and CM samples. The variability in the TMC of C and CM squid samples was obtained as 93% in Model I, whereas the variability in the TMC of these samples was observed as 91% in Model II. So, these two models performed well, and they can be used for predicting the TMC of C and CM samples. Additionally, Model III was also developed for estimating the prediction value of LBC of cooked squid samples during the marination process at 4°C. This model was also determined very good performance (86%) to estimate the predicting values of LBC and it can be very essential together used with Model I or Model II for marinated fishery products to estimate the real shelf-life.

Keywords

Marination prediction models cooked squid ring bacteria counts estimation

Supporting Institution

Ege Üniversitesi Rektörlüğü Bilimsel Araştırma Projeleri Koordinatörlüğü

Project Number

FGA-2019-20561

Thanks

This study was supported by Ege University Scientific Research Projects Coordination Unit. Project Number: FGA-2019-20561.

References

  • Andrighetto, C., Lombardi, A., Ferrati, M., Guidi, A., Corrain, C., & Arcangeli, G. (2009). Lactic acid bacteria biodiversity in Italian marinated seafood salad and their interactions on the growth of Listeria monocytogenes. Food Control, 20, 462-468. DOI: 10.1016/j.foodcont.2008.07.016
  • Anonymous (2000). Food Microbiology and Applications. Ankara University Faculty of Agriculture Department of Food Engineering, Ankara, Türkiye (in Turkish). Baumgart, J., Firnhaber, J., & Spicher, G. (1986). Mikrobiologische Untersuchung von Lebensmitteln. Behr’s Verlag, Hamburg- Germany.
  • Blackburn, C.W. (2000). The Stability and Shelf-life of Food. In: 3-Modelling shelf life. Woodhead Publishing Series in Food Science Technology and Nutrition, 55-78. ISBN:978-0-08-100435-7. DOI: 10.1533/9781855736580.1.55
  • Bongiorno, T., Tulli, F., Comi, G., Sensidoni, A., Andyanto, D., & Lacumin, L., (2018). Sous vide cook-chill mussel (Mytilus galloprovincialis): evaluation of chemical, microbiological and sensory quality during chilled storage (3°C). LWT Food Science and Technology, 91, 117-124. DOI: 10.1016/j.lwt.2017.12.005
  • Bulat, F.N., Kılınç, B., & Atalay, S.D. (2020). Microbial Ecology of Different Sardine Parts Stored at Different Temperatures and The Development of Prediction Models. Food Bioscience, 38, 100770. DOI: 10.1016/j.fbio.2020.100770
  • Collignan, A., & Montet, D. (1998). Tenderizing squid mantle by marination at different pH and Temperature Levels. LWT-Food Science and Technology, 31(7-8), 673-679. DOI: 10.1006/fstl.1998.0423
  • Dalgaard, P. (2002). Safety and Quality Issues in Fish Processing. In: 12-Modelling and predicting the shelf-life of seafood. Woodhead Publishing Series in Food Science, Technology and Nutrition, 191-219. DOI: 10.1533/9781855736788.2.191
  • Dalgaard, P., Mejlholm, O., & Huss, H.H. (1997). Application of an iterative approach for development of a microbial model predicting the shelf-life of packed fish. International Journal of Food Microbiology, 38, 169-179. DOI: 10.1016/s0168-1605(97)00101-3
  • Fu, B., & Labuza, T.P. (1993). Shelf-life prediction: Theory and application. Food Control, 4(3), 125-133. DOI: 10.1016/0956-7135(93)90298-3
  • Gamgam, H., & Altunkaynak, B. (2017). SPSS Applied Nonparametric Methods. Seçkin Press, Ankara, Türkiye (in Turkish). ISBN: 9789750225345
  • Gou, J., Lee, H.Y., & Ahn, J. (2010). Effect of high pressure processing on the quality of squid (Todarodes pacificus) during refrigerated storage. Food Chemistry, 119(2), 471-476. DOI: 10.1016/j.foodchem.2009.06.042
  • Harrigan, W.F., & McCance, M.E. (1976). Laboratory Methods in Food and Dairy Microbiology. In W.F. Harrigan, M.E. McCance (Eds.), Academic Press Inc., London, UK.
  • Hu, Y., Yu, H., Dong, K., Yang, S., Ye, X., & Chen, S. (2014). Analysis of the tenderisation of Jumbo squid (Dosidicus gigas) meat by ultrasonic treatment using response surface methodology. Food Chemistry, 160, 219-225. DOI: 10.1016/j.foodchem.2014.01.085
  • Hyytia, E., Hielm, S., Mokkia, M., Kinnunen, A., & Korkeala, H. (1999). Predicted and observed growth and toxigenesis by Clostridium botulinum type E in vacuum-packaged fishery product challenge tests. International Journal of Food Microbiology, 47, 161-169. DOI: 10.1016/s0168-1605(98)00173-1
  • ICMSF. (1986). Microorganisms in Foods 2: Sampling or microbiological analysis: Principles and specific applications (2nd ed.). In J.A. Ordonez Pereda, M.A. Diaz Hernandez (Eds.), 0802056938, University of Toronto Press, Toronto, ONT, Canada.
  • Jun-Hui, X., Hui-Juan, C., Bin, Z., & Hui, Y. (2020). The mechanistic effect of bromelain and papain on tenderization in Jumbo squid (Dosidicus gigas) muscle. Food Research International, 131, 108991. DOI: 10.1016/j.foodres.2020.108991
  • Keklik, N.M., Işıklı, N.D., & Sur, E.B. (2017). Estimation of the Shelf life of pezik pickles using Weibull Hazard Analysis. Food Science and Technology Campinas, 37(1), 125-130. DOI: 10.1590/1678-457x.33216
  • Kilinc, B., & Cakli, S. (2004). Chemical, Microbiological and Sensory Changes in Thawed Frozen Fillets of Sardine (Sardina pilchardus) During Marination. Food Chemistry, 88, 275-280. DOI: 10.1016/j.foodchem.2004.01.044
  • Kilinc, B., Atalay, S.D., & Bulat, F.N. (2021). Using grey and regression prediction models to estimate the aerobic plate bacteria counts on frozen squid rings (Loligo vulgaris Lamarck, 1798) during the thawing process. Journal of Food Safety and Food Quality, 72(4), 109-138. DOI: 10.2376/0003-925X-72-122
  • Li, D., Xie, H., Liu, Z., Li, A., Li, J., Liu, B., Liu, X., & Zhou, D. (2019). Shelf life prediction and changes in lipid profiles of dried shrimp (Penaeus vannamei) during accelerated storage. Food Chemistry, 297, 124951. DOI: 10.1016/j.foodchem.2019.124951
  • Man, C.M.D. (2004). Understanding and measuring the shelf-life of food. In: 15-Shelf-life testing. Woodhead Publishing Series in Food Science, Technology and Nutrition (pp. 340-356). eBook ISBN: 9781855739024. DOI: 10.1201/9781439823354.ch15
  • McMeekin, T.A., & Ross, T. (1996). Shelf life prediction: Status and future possibilities. International Journal of Food Microbiology, 33(1), 65-83. DOI: 10.1016/0168-1605(96)01138-5
  • McMeekin, T.A., Ross, T., & Olley, J. (1992). Application of predictive microbiology to assure the quality and safety of fish and fish products. International Journal of Food Microbiology, 15(1-2), 13-32. DOI: 10.1016/0168-1605(92)90132-m
  • Montgomery, D.C., & Runger, G.C. (2003). Applied Statistics and Probability For Engineers. 3rd, John Wiley & amp; Sons, Inc. New York. ISBN: 9781118901359
  • Mossel, D.A., Moreno, G.B., & Struijk, C.B. (1985). Microbiologia de Alimentos, Acribia. Zaragoza. España, 214, 272 (in Spanish).
  • Paarup, T., Sanchez, J.A., Palaez, C., & Moral, A. (2002). Sensory, chemical and bacteriological changes in vacumed packed pressurised squid mantle (Todaropsis eblanae) stored at 4°C. International Journal of Food Microbiology, 74(1-2), 1-12. DOI: 10.1016/s0168-1605(01)00701-2
  • Roberts, T.A. (1995). Microbial growth and survival: Developments in predictive modelling. International Biodeterioration & Biodegradation, 297-309. DOI: 10.1016/0964-8305(96)00009-1
  • Schmidt, C.V., Plankensteiner, L., Faxholm, P.L., Olsen, K., Mouritsen, O.G., & Frost, M.B. (2021). Physicochemical characterization of sous vide cooked squid (Loligo forbesii and Loligo vulgaris) and relationship to selected sensory properties and hedonic response. International Journal of Gastronomy and Food Science, 23, 100298. DOI: 10.1016/j.ijgfs.2020.100298
  • Serratore, P., Piano, A., Piraccini, S., Trentini, M., Zavatta, E., Grodzki, M., & Valeri, M.L. (2009). Survey of V. cholerae, V. vulnificus and V. parahaemolyticus, in bivalve molluscs of the Adriatic sea and proposal of an analytical protocol. Italian Journal of Food Science, 1, 33-38. DOI: 10.4081/ijfs.2008.4.33
  • Sharma, M. (2019). How to Assess a Regression’s Predictive Power for Energy Use. kW Engineering Blog 15 February See. https://kw-engineering.com/how-to-assess-a-regressions-predictive-power-energy-use/
  • Stanley, D.W., & Hultin, H.O. (1982). Quality factors in cooked North Atlantic squid. Canadian Institute of Food Science and Technology Journal, 15(4), 277-282. DOI: 10.1111/j.1745-4514.1988.tb00365.x
  • Szymczak, M., Kaminski, P., Felisiak, K., Szymczak, B., Dmytrow, I., & Sawichi, T. (2020). Effect of constant and fluctuating temperatures during frozen storage on quality of marinated fillets from Atlantic and Baltic herrings (Clupea harengus). LWT Food Science and Technology, 133, 109961. DOI: 10.1016/j.lwt.2020.109961
  • Taoukis, P.S., Koutsoumanis, K., & Nychas, G.J.E. (1999). Use of time-temperature integrators and predictive modelling for shelf life control of chilled fish under dynamic storage conditions. International Journal of Food Microbiology, 53, 21-31. DOI: 10.1016/S0168-1605(99)00142-7
  • Tomac, A., Cova, M.C., Narvaiz, P., & Yeannes, M.I. (2017). Sensory acceptability of squid rings gamma irradiated for shelf-life extension. Radiation Physics and Chemistry, 130, 359-361. DOI: 10.1016/j.radphyschem.2016.09.016
  • Tomac, A., Mascheroni, R.H., & Yeannes, M.I. (2013). Modelling the effects of gamma irradiation on the inactivation and growth kinetics of psychrotrophic bacteria in squid rings during refrigerated storage. Shelf life predictions. Journal of Food Engineering, 117, 211-216. DOI: 10.1016/j.jfoodeng.2013.02.021
  • Unluturk, A., & Turantas, F. (2003). Food Microbiology. META Printing Printing Services, Istanbul, Türkiye (in Turkish). ISBN: 975-483-383-4.
  • Wang, H., Zheng, Y., Shi, W., & Wang, X. (2022). Comparison of Arrhenius model and articifial neuronal network for predicting quality changes of frozen Tilapia (Oreochromis niloticus). Food Chemistry. DOI: 10.1016/j.foodchem.2021.131268
  • Xuan, X.T., Fan, Y.F., Ling, J.G., Hu, Y.Q., Liu, D.H., Chen, S.G., Ye, X.Q., & Ding, T. (2017). Preservation of squid by slightly acidic electrolyzed water ice. Food Control, 73, 1483-1489. DOI: 10.1016/j.foodcont.2016.11.013
  • Zavadlav, S., Blazic, M., Velde, F.V., Vignatti, C., Fenoglio, C., Piagentini, A.M., Pirovani, M.E., Perotti, C.M., Kovacevic, D.B., & Putnik, P. (2020). Sous-vide as a technique for preparing healty and high quality vegetable and seafood products. Foods, 9(11), 1537. DOI: 10.3390/foods9111537

Marinasyon öncesinde pişirme işlemi uygulanan kalamar halkalarının toplam mezofilik aerobik ve laktik asit bakteri sayılarını tahmin etmek için modellerin geliştirilmesi

Year 2022, Volume: 39 Issue: 4, 316 - 325, 15.12.2022

Berna Kılınç Fevziye Nihan Bulat Sevcan Demir Atalay

https://doi.org/10.12714/egejfas.39.4.07

Abstract


Bu çalışma, pişirme sonrasında limon ve maden suyu ile marine edilen kalamar halkalarının bakteri sayılarını tahmin etmede farklı istatistiksel modeller geliştirmek amacıyla yapılmıştır. Marinasyon oranları (10:90; 90:10; 50:50; 100:100/100 g kalamar halkası) ve süreleri (1, 3, 6, 12, 24, 48 ve 72 saat) sırasıyla bu şekildedir. Marinasyon oranlarının ve sürelerinin pişmiş kalamar halkalarının 4°C'de depolama aşamasında mikrobiyolojik ve duyusal değişimleri üzerindeki etkileri gözlenmiştir. Bu çalışma sonucunda pişirilmiş marine edilmiş (CM) ve pişirilmiş kalamar halkalarında (C) patojenik olan Vibrio spp., Staphylococcus aureus ve Escherichia coli türü patojenik bakterilere saptanmamıştır. C ve CM örneklerinin (C7, CM7, CM 14, CM21, CM28) toplam mezofil aerobik bakteri sayısı (TMC) 72. saatte sırasıyla 5.92, 5.83, 5.71, 5.57 ve 5.42 log kob/g'a yükselmiştir. Marinasyon işlemi esnasında örneklerin artan bakteri gelişim oranlarının belirlenmesi için; 4°C'de marine işlemi sırasında pişirilmiş kalamar halkalarının TMC ve laktik asit bakteri sayılarının (LBC) tahmini için regresyon modelleri geliştirilmiştir. Bu çalışmanın sonucunda; Model I ve Model II karşılaştırıldığında, C ve CM örneklerinin her ikisi içinde iki modelde TMC sayılarını tahmin etmek için tercih edilebilir olduğu görülmüştür. TMC’deki değişkenliğin %93’ü Model I ile %91’i Model II ile açıklanabilmektedir. Bu nedenle bu iki modelinde C ve ve hem CM örneklerinde TMC sayılarını tahmin etmede çok iyi performans gösterdiği ve kullanılabileceği belirlenmiştir. Buna ek olarak, pişirilmiş kalamar örneklerinin 4°C’de marinasyon işlemi esnasında LBC sayılarını tahmin etmek için Model III geliştirilmiştir. Bu modelinde LBC sayılarının tahmini değerlerinin belirlenmesi için çok iyi performans gösterdiği ve Model III’ün marine edilen su ürünleri için gerçek raf ömrünü tayin etmede Model I veya Model II ile birlikte kullanıldığında çok önemli olabileceği belirlenmiştir.


Keywords

Marinasyon tahmin modelleri pişmiş kalamar halkası bakteri sayısı tahmin

Project Number

FGA-2019-20561

References

  • Andrighetto, C., Lombardi, A., Ferrati, M., Guidi, A., Corrain, C., & Arcangeli, G. (2009). Lactic acid bacteria biodiversity in Italian marinated seafood salad and their interactions on the growth of Listeria monocytogenes. Food Control, 20, 462-468. DOI: 10.1016/j.foodcont.2008.07.016
  • Anonymous (2000). Food Microbiology and Applications. Ankara University Faculty of Agriculture Department of Food Engineering, Ankara, Türkiye (in Turkish). Baumgart, J., Firnhaber, J., & Spicher, G. (1986). Mikrobiologische Untersuchung von Lebensmitteln. Behr’s Verlag, Hamburg- Germany.
  • Blackburn, C.W. (2000). The Stability and Shelf-life of Food. In: 3-Modelling shelf life. Woodhead Publishing Series in Food Science Technology and Nutrition, 55-78. ISBN:978-0-08-100435-7. DOI: 10.1533/9781855736580.1.55
  • Bongiorno, T., Tulli, F., Comi, G., Sensidoni, A., Andyanto, D., & Lacumin, L., (2018). Sous vide cook-chill mussel (Mytilus galloprovincialis): evaluation of chemical, microbiological and sensory quality during chilled storage (3°C). LWT Food Science and Technology, 91, 117-124. DOI: 10.1016/j.lwt.2017.12.005
  • Bulat, F.N., Kılınç, B., & Atalay, S.D. (2020). Microbial Ecology of Different Sardine Parts Stored at Different Temperatures and The Development of Prediction Models. Food Bioscience, 38, 100770. DOI: 10.1016/j.fbio.2020.100770
  • Collignan, A., & Montet, D. (1998). Tenderizing squid mantle by marination at different pH and Temperature Levels. LWT-Food Science and Technology, 31(7-8), 673-679. DOI: 10.1006/fstl.1998.0423
  • Dalgaard, P. (2002). Safety and Quality Issues in Fish Processing. In: 12-Modelling and predicting the shelf-life of seafood. Woodhead Publishing Series in Food Science, Technology and Nutrition, 191-219. DOI: 10.1533/9781855736788.2.191
  • Dalgaard, P., Mejlholm, O., & Huss, H.H. (1997). Application of an iterative approach for development of a microbial model predicting the shelf-life of packed fish. International Journal of Food Microbiology, 38, 169-179. DOI: 10.1016/s0168-1605(97)00101-3
  • Fu, B., & Labuza, T.P. (1993). Shelf-life prediction: Theory and application. Food Control, 4(3), 125-133. DOI: 10.1016/0956-7135(93)90298-3
  • Gamgam, H., & Altunkaynak, B. (2017). SPSS Applied Nonparametric Methods. Seçkin Press, Ankara, Türkiye (in Turkish). ISBN: 9789750225345
  • Gou, J., Lee, H.Y., & Ahn, J. (2010). Effect of high pressure processing on the quality of squid (Todarodes pacificus) during refrigerated storage. Food Chemistry, 119(2), 471-476. DOI: 10.1016/j.foodchem.2009.06.042
  • Harrigan, W.F., & McCance, M.E. (1976). Laboratory Methods in Food and Dairy Microbiology. In W.F. Harrigan, M.E. McCance (Eds.), Academic Press Inc., London, UK.
  • Hu, Y., Yu, H., Dong, K., Yang, S., Ye, X., & Chen, S. (2014). Analysis of the tenderisation of Jumbo squid (Dosidicus gigas) meat by ultrasonic treatment using response surface methodology. Food Chemistry, 160, 219-225. DOI: 10.1016/j.foodchem.2014.01.085
  • Hyytia, E., Hielm, S., Mokkia, M., Kinnunen, A., & Korkeala, H. (1999). Predicted and observed growth and toxigenesis by Clostridium botulinum type E in vacuum-packaged fishery product challenge tests. International Journal of Food Microbiology, 47, 161-169. DOI: 10.1016/s0168-1605(98)00173-1
  • ICMSF. (1986). Microorganisms in Foods 2: Sampling or microbiological analysis: Principles and specific applications (2nd ed.). In J.A. Ordonez Pereda, M.A. Diaz Hernandez (Eds.), 0802056938, University of Toronto Press, Toronto, ONT, Canada.
  • Jun-Hui, X., Hui-Juan, C., Bin, Z., & Hui, Y. (2020). The mechanistic effect of bromelain and papain on tenderization in Jumbo squid (Dosidicus gigas) muscle. Food Research International, 131, 108991. DOI: 10.1016/j.foodres.2020.108991
  • Keklik, N.M., Işıklı, N.D., & Sur, E.B. (2017). Estimation of the Shelf life of pezik pickles using Weibull Hazard Analysis. Food Science and Technology Campinas, 37(1), 125-130. DOI: 10.1590/1678-457x.33216
  • Kilinc, B., & Cakli, S. (2004). Chemical, Microbiological and Sensory Changes in Thawed Frozen Fillets of Sardine (Sardina pilchardus) During Marination. Food Chemistry, 88, 275-280. DOI: 10.1016/j.foodchem.2004.01.044
  • Kilinc, B., Atalay, S.D., & Bulat, F.N. (2021). Using grey and regression prediction models to estimate the aerobic plate bacteria counts on frozen squid rings (Loligo vulgaris Lamarck, 1798) during the thawing process. Journal of Food Safety and Food Quality, 72(4), 109-138. DOI: 10.2376/0003-925X-72-122
  • Li, D., Xie, H., Liu, Z., Li, A., Li, J., Liu, B., Liu, X., & Zhou, D. (2019). Shelf life prediction and changes in lipid profiles of dried shrimp (Penaeus vannamei) during accelerated storage. Food Chemistry, 297, 124951. DOI: 10.1016/j.foodchem.2019.124951
  • Man, C.M.D. (2004). Understanding and measuring the shelf-life of food. In: 15-Shelf-life testing. Woodhead Publishing Series in Food Science, Technology and Nutrition (pp. 340-356). eBook ISBN: 9781855739024. DOI: 10.1201/9781439823354.ch15
  • McMeekin, T.A., & Ross, T. (1996). Shelf life prediction: Status and future possibilities. International Journal of Food Microbiology, 33(1), 65-83. DOI: 10.1016/0168-1605(96)01138-5
  • McMeekin, T.A., Ross, T., & Olley, J. (1992). Application of predictive microbiology to assure the quality and safety of fish and fish products. International Journal of Food Microbiology, 15(1-2), 13-32. DOI: 10.1016/0168-1605(92)90132-m
  • Montgomery, D.C., & Runger, G.C. (2003). Applied Statistics and Probability For Engineers. 3rd, John Wiley & amp; Sons, Inc. New York. ISBN: 9781118901359
  • Mossel, D.A., Moreno, G.B., & Struijk, C.B. (1985). Microbiologia de Alimentos, Acribia. Zaragoza. España, 214, 272 (in Spanish).
  • Paarup, T., Sanchez, J.A., Palaez, C., & Moral, A. (2002). Sensory, chemical and bacteriological changes in vacumed packed pressurised squid mantle (Todaropsis eblanae) stored at 4°C. International Journal of Food Microbiology, 74(1-2), 1-12. DOI: 10.1016/s0168-1605(01)00701-2
  • Roberts, T.A. (1995). Microbial growth and survival: Developments in predictive modelling. International Biodeterioration & Biodegradation, 297-309. DOI: 10.1016/0964-8305(96)00009-1
  • Schmidt, C.V., Plankensteiner, L., Faxholm, P.L., Olsen, K., Mouritsen, O.G., & Frost, M.B. (2021). Physicochemical characterization of sous vide cooked squid (Loligo forbesii and Loligo vulgaris) and relationship to selected sensory properties and hedonic response. International Journal of Gastronomy and Food Science, 23, 100298. DOI: 10.1016/j.ijgfs.2020.100298
  • Serratore, P., Piano, A., Piraccini, S., Trentini, M., Zavatta, E., Grodzki, M., & Valeri, M.L. (2009). Survey of V. cholerae, V. vulnificus and V. parahaemolyticus, in bivalve molluscs of the Adriatic sea and proposal of an analytical protocol. Italian Journal of Food Science, 1, 33-38. DOI: 10.4081/ijfs.2008.4.33
  • Sharma, M. (2019). How to Assess a Regression’s Predictive Power for Energy Use. kW Engineering Blog 15 February See. https://kw-engineering.com/how-to-assess-a-regressions-predictive-power-energy-use/
  • Stanley, D.W., & Hultin, H.O. (1982). Quality factors in cooked North Atlantic squid. Canadian Institute of Food Science and Technology Journal, 15(4), 277-282. DOI: 10.1111/j.1745-4514.1988.tb00365.x
  • Szymczak, M., Kaminski, P., Felisiak, K., Szymczak, B., Dmytrow, I., & Sawichi, T. (2020). Effect of constant and fluctuating temperatures during frozen storage on quality of marinated fillets from Atlantic and Baltic herrings (Clupea harengus). LWT Food Science and Technology, 133, 109961. DOI: 10.1016/j.lwt.2020.109961
  • Taoukis, P.S., Koutsoumanis, K., & Nychas, G.J.E. (1999). Use of time-temperature integrators and predictive modelling for shelf life control of chilled fish under dynamic storage conditions. International Journal of Food Microbiology, 53, 21-31. DOI: 10.1016/S0168-1605(99)00142-7
  • Tomac, A., Cova, M.C., Narvaiz, P., & Yeannes, M.I. (2017). Sensory acceptability of squid rings gamma irradiated for shelf-life extension. Radiation Physics and Chemistry, 130, 359-361. DOI: 10.1016/j.radphyschem.2016.09.016
  • Tomac, A., Mascheroni, R.H., & Yeannes, M.I. (2013). Modelling the effects of gamma irradiation on the inactivation and growth kinetics of psychrotrophic bacteria in squid rings during refrigerated storage. Shelf life predictions. Journal of Food Engineering, 117, 211-216. DOI: 10.1016/j.jfoodeng.2013.02.021
  • Unluturk, A., & Turantas, F. (2003). Food Microbiology. META Printing Printing Services, Istanbul, Türkiye (in Turkish). ISBN: 975-483-383-4.
  • Wang, H., Zheng, Y., Shi, W., & Wang, X. (2022). Comparison of Arrhenius model and articifial neuronal network for predicting quality changes of frozen Tilapia (Oreochromis niloticus). Food Chemistry. DOI: 10.1016/j.foodchem.2021.131268
  • Xuan, X.T., Fan, Y.F., Ling, J.G., Hu, Y.Q., Liu, D.H., Chen, S.G., Ye, X.Q., & Ding, T. (2017). Preservation of squid by slightly acidic electrolyzed water ice. Food Control, 73, 1483-1489. DOI: 10.1016/j.foodcont.2016.11.013
  • Zavadlav, S., Blazic, M., Velde, F.V., Vignatti, C., Fenoglio, C., Piagentini, A.M., Pirovani, M.E., Perotti, C.M., Kovacevic, D.B., & Putnik, P. (2020). Sous-vide as a technique for preparing healty and high quality vegetable and seafood products. Foods, 9(11), 1537. DOI: 10.3390/foods9111537
There are 39 citations in total.

Details

Primary Language English
Subjects Food Engineering
Journal Section Articles
Authors

Berna Kılınç 0000-0002-4663-5082

Fevziye Nihan Bulat 0000-0001-5165-3632

Sevcan Demir Atalay 0000-0002-3117-0825

Project Number FGA-2019-20561
Publication Date December 15, 2022
Submission Date May 6, 2022
Published in Issue Year 2022Volume: 39 Issue: 4

Cite

APA Kılınç, B., Bulat, F. N., & Demir Atalay, S. (2022). Development of prediction models to estimate the total number of mesophilic aerobic and lactic acid bacteria of squid rings that were cooked before marinating. Ege Journal of Fisheries and Aquatic Sciences, 39(4), 316-325. https://doi.org/10.12714/egejfas.39.4.07