Mathematical modeling of Escherichia coli inactivation in orange juice fermented with water kefir microorganisms

Year 2019, Volume: 9 Issue: 2, 297 - 310, 15.12.2019

Selin Kalkan

https://doi.org/10.31466/kfbd.640727

Cited By: 2

Abstract

Water kefir is a homemade fermented beverage based on a sucrose solution with different dried and fresh fruits. The predominant flora in this beverage prepared with water kefir grains is lactic acid bacteria and some yeast species. The aim of study was mathematically express of E.coli inactivation by linear (simple linear, quadratic and cubic) and nonlinear models (Logistics, Gompertz and Brody) in fermented orange juice with water kefir grains and to determine the model suitability. For this purpose, during the storage period for 4 days under refrigerator conditions, E.coli level was determined daily in the control group (orange juice) and orange juice samples fermented with water kefir grains. As a result, it was determined that E.coli inactivation was 4.82 log cfu /mL in control group samples and 5.38 log cfu/mL in fermented orange juice samples. When the model comparison is made based on the calculated determination coefficients (R2) and error squares mean (HKO) of the used models, Cubic model as a linear model was found to be most suitable models with 0.998 R2 and 0.025 HKO; Brody model was found to be the most suitable model from nonlinear models with 0.995 R2 and 0.053 HKO values.

Keywords

Water kefir, orange juice, Escherichia coli, mathematical modeling

Su kefiri mikroorganizmaları ile fermente edilen portakal suyunda Escherichia coli inaktivasyonunun matematiksel modellemesi

Abstract

Su kefiri, farklı taze ve kuru meyvelerden elde edilen, sakkaroz bazlı ev yapımı fermente bir içecektir. Su kefiri taneleri ile hazırlanan bu içecekte baskın florayı laktik asit bakterileri ile bazı maya türleri oluşturmaktadır. Bu çalışmada, su kefiri taneleri ile fermente edilen portakal suyuna inoküle edilen E.coli inaktivasyonunun doğrusal (basit doğrusal, Kuadritik ve Kubik) ve doğrusal olmayan modeller (Lojistik, Gompertz ve Brody) ile matematiksel olarak ifade edilmesi ve model uygunluğunun tespit edilmesi amaçlanmıştır. Bu amaçla buzdolabı koşullarında gerçekleştirilen 4 günlük depolama süresi boyunca, E.coli düzeyi kontrol grup (yalnızca portakal suyu) ve su kefiri ile fermente edilen portakal suyu örneklerinde günlük olarak belirlenmiştir. Sonuç olarak, kontrol grup örneklerde 4.82 log kob/mL, fermente portakal suyu örneklerinde ise 5.38 log kob/mL düzeyinde bir E.coli inaktivasyonu gerçekleştiği tespit edilmiştir. Kullanılan modellerin hesaplanan determinasyon katsayıları (R2) ve hata kareler ortalamaları (HKO) baz alınarak model karşılaştırılması yapıldığında, E.coli inaktivasyonunu 0.998 R2 ve 0.025 HKO değerleri ile doğrusal modellerden kübik modelin; 0.995 R2 ve 0.053 HKO değerleri ile doğrusal olmayan modellerden ise Brody modelin en uygun model olduğu tespit edilmiştir.

Keywords

Su kefiri, portakal suyu, Escherichia coli, matematiksel modelleme

References

• Aslım, B., Yüksekdağ, Z. N., Sarıkaya, E., ve Beyatlı, Y., (2005). Determination of the bacteriocin-like substances produced by some lactic acid bacteria isolated from Turkish dairy products. LWT, 38: 691-694.
• Baranyi, J., ve Roberts, T. A., (1994). A dynamic approach to predicting bacterial growth in food. Int. J. of Food Microbiol, 23 (3–4), 277–29.
• Çon, A. H. ve Gökalp, H. Y., (2000). Laktik Asit Bakterilerinin Antimikrobiyal Metabolitleri ve Etki şekilleri. Turk Mikrobiyol Cem Derg, 30: 180-190.
• Davidović, S. Z., Miljković, M. G., Rajilić-Stojanović, M. D., Dimitrijević-Branković, S. I. Ve Antonović, D. G., (2015). Water Kefir grain as a source of potent dextran producing lactic acid bacteria, Chemical Industry/Hemijska Industrija. 69(6), 595-604.
• Dinçer, E., Kıvanç, M., ve Karaca, H. (2010). Biyokoruyucu Olarak Laktik Asit Bakterileri. Gıda, 35(1), 1-8.
• Erginkaya, Z., Sarıkodal, E., Özkütük, S. T., Konuray, G., & Turhan, E. Ü. (2019). Probiyotik bitter çikolata üretiminde mikroenkapsüle Lactobacıllus rhamnosus kullanımı. Gıda, 44(2), 238-247.
• Evren, M., Albayram, C., ve Apan, M. (2006). Laktik asit bakterilerinin oluşturduğu antimikrobiyel maddeler. Türkiye 9. Gıda Kongresi, 24-26.
• FDA. (1995). Bacteriolological Analytical Manual. Food and Drug Administration 16 th Edition. AOAC Int. Gaithersburg MD.
• Gibson, A. M., Bratchell, N., ve Roberts, T. A. (1998). Predicting microbial growth: Growth responses of salmonellae in a laboratory medium as affected by pH, sodium chloride and storage temperature. Int J of Food Microbiol, 6(2), 155–178.
• Gospavic, R., Kreyenschmidt, J., Bruckner, S., Popov, V., ve Haque, N. (2008). Mathematical modelling for predicting the growth of Pseudomonas spp. in poultry under variable temperature conditions. Int J of Food Microbiol, 127(3), 290–297.
• Gulitz, A., Stadie, J., Ehrmann, M. A., Ludwig, V. ve Vogel, R. F., (2013). Comparative phylobiomic analysis of the bacterial community of water kefir by 16S rRNA gene amplicon sequencing and ARDRA analysis. J Appl Microbiol, 114, 1082-1091.
• Gulitz, A., Stadie, J., Wenning, M., Ehrmann, M. A. ve Vogel, R. F., (2011). The microbial diversity of water kefir. Int J Food Microbiol, 151, 284-288.
• IFST. (1993). Shelf life of food muidelines for its determination and prediction. London: Institute of Food Science and Technology.
• Kalkan, S. (2016). Probiyotik laktik asit bakterilerinin Staphylococcus aureus'a karşı antimikrobiyel etkilerinin farklı matematiksel modeller ile analizi. Sinop Üniv Fen Bil De, 1(2), 150-159.Kalkan, S. (2019). Predicting the antimicrobial effect of probiotic lactic acid bacteria against Staphylococcus aureus in white cheeses, using Fourier series modeling method. J of Food Safety, e12724.
• Kalkan, S. ve Otağ, M. R., (2019). Some of the quality properties and bioactivity of orange juice fermented with water kefir microorganisms. 5th Internatıonal Conference on Engıneerıng and Natural Scıences (ICENS), 12-16 June 2019, Prague, Czech Republıc. pp 31-35.
• Külcü, D. B., Kalkan, S., ve Akben, S. B. (2019). Polynomial surface fitting and artificial neural networks-based analysis of the storage days and garlic extract supplementation dependent microbial growths in minced raw chicken meat. J of Food Processing and Preservation, 43(3), e13882.
• Laureys, D. ve De Vuyst, L., (2014). Microbial species diversity, community dynamics, and metabolite kinetics of water kefir fermentation. Appl. Environ. Microbiol, 80(8), 2564-2572.
• Laureys, D., Cnockaert, M., De Vuyst, L, ve Vandamme, P., (2016). Bifidobacterium aquikefiri sp. nov., isolated from water kefir. Int J of Systematic and Evolutionary Microbiol, 66(3), 1281-1286.
• Leroi, F., Pidoux, M., (1993). Detection of interactions between yeasts and lactic acid bacteria isolated from sugary kefir grains. J of Appl Microbiol, 74(1), 48–53.
• Nataro, J. P., ve Kaper, J. B. (1998). Diarrheagenic escherichia coli. Clinical microbiology reviews, 11(1), 142-201.
• Perez-Rodriguez, F., ve Valero, A. (2013). Predictive microbiology in foods (pp. 1–10). New York, NY: Springer.
• Pidoux, M., 1989. The microbial flora of sugary kefir grain (the gingerbeer plant): biosynthesis of the grain from Lactobacillus hilgardii producing a polysaccharide gel. MIRCEN Journal 5, 223–238.
• Raffellini, S., Guerrero, S., ve Alzamora, S. M. (2008). Effect of hydrogen peroxide concentration and pH on inactivation kinetics of Escherichia coli. J of Food Safety, 28(4), 514-533.
• Sağdıç O., Küçüköner, E., ve Özçelik, S., (2004). Probiyotik ve prebiyotiklerin fonksiyonel özellikleri. Atatürk Üniv. Ziraat Fak. Derg., 35, 221-228.
• Stadie, J., Gulitz, A., Ehrmann, M. A., ve Vogel, R. F. (2013). Metabolic activity and symbiotic interactions of lactic acid bacteria and yeasts isolated from water kefir. Food Microbiol, 35(2), 92-98.
• Taş, E., Erginkaya, Z., Kalkan, S., Turhan, E. Ü. (2017). Determination of Antimicrobial Effects of Probiotic Lactic Acid Bacteria and Garlic Extract Against Some Foodborn Pathogenic Bacteria. Turkish J of Agriculture-Food Sci and Techn, 5(2), 125-131.
• Temelli, S. (2002). Gıda zehirlenmesine neden olan E. coli O157: H7 ve önemi. Uludağ Üni Veteriner Fak Derg. 21, 133-138.Tsujihata, S., Entani, E., Asai, M., Tsukamoto, Y., ve Ohta, M. (1998). Mathematical modeling to predict the bactericidal effect of processed vinegar on Escherichia coli O157: H7. Int J of Food Microbiol, 43(1-2), 135-138.
• Virto, R., Sanz, D., Alvarez, I., Condon, S., ve Raso, J. (2006). Application of the Weibull model to describe inactivation of Listeria monocytogenes and Escherichia coli by citric and lactic acid at different temperatures. J of the Sci of Food and Agriculture, 86(6), 865-870.