저장온도에 따른 마른김(Pyropia pseudolinearis)의 Bacillus cereus 성장예측모델 개발
Predictive Growth Models of Bacillus cereus on Dried Laver Pyropia pseudolinearis as Function of Storage Temperature
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Predictive models in food microbiology are used for predicting microbial growth or death rates using mathematical and statistical tools considering the intrinsic and extrinsic factors of food. This study developed predictive growth models for Bacillus cereus on dried laver Pyropia pseudolinearis stored at different temperatures (5, 10, 15, 20, and 25°C). Primary models developed for specific growth rate (SGR), lag time (LT), and maximum population density (MPD) indicated a good fit (R2≥0.98) with the Gompertz equation. The SGR values were 0.03, 0.08, and 0.12, and the LT values were 12.64, 4.01, and 2.17 h, at the storage temperatures of 15, 20, and 25°C, respectively. Secondary models for the same parameters were determined via nonlinear regression as follows: SGR=0.0228- 0.0069*T1+0.0005*T1 2; LT=113.0685-9.6256*T1+0.2079*T1 2; MPD=1.6630+0.4284*T1-0.0080*T1 2 (where T1 is the storage temperature). The appropriateness of the secondary models was validated using statistical indices, such as mean squared error (MSE<0.01), bias factor (0.99≤Bf ≤1.07), and accuracy factor (1.01≤Af ≤1.14). External validation was performed at three random temperatures, and the results were consistent with each other. Thus, these models may be useful for predicting the growth of B. cereus on dried laver.
Abstract
Predictive models in food microbiology are used for predicting microbial growth or death rates using mathematical and statistical tools considering the intrinsic and extrinsic factors of food. This study developed predictive growth models for Bacillus cereus on dried laver Pyropia pseudolinearis stored at different temperatures (5, 10, 15, 20, and 25°C). Primary models developed for specific growth rate (SGR), lag time (LT), and maximum population density (MPD) indicated a good fit (R2≥0.98) with the Gompertz equation. The SGR values were 0.03, 0.08, and 0.12, and the LT values were 12.64, 4.01, and 2.17 h, at the storage temperatures of 15, 20, and 25°C, respectively. Secondary models for the same parameters were determined via nonlinear regression as follows: SGR=0.0228- 0.0069*T1+0.0005*T1 2; LT=113.0685-9.6256*T1+0.2079*T1 2; MPD=1.6630+0.4284*T1-0.0080*T1 2 (where T1 is the storage temperature). The appropriateness of the secondary models was validated using statistical indices, such as mean squared error (MSE<0.01), bias factor (0.99≤Bf ≤1.07), and accuracy factor (1.01≤Af ≤1.14). External validation was performed at three random temperatures, and the results were consistent with each other. Thus, these models may be useful for predicting the growth of B. cereus on dried laver.
참고문헌 (36)
- 박경진, "김밥에서의 Staphylococcus aureus에 대한 정량적 미생물위해평가 모델 개발", 한국식품과학회지, 37(3), pp.484~491 (2005), 한국식품과학회
- E. Carrasco, "Predictive Model of Listeria Monocytogenes’ Growth Rate Under Different Temperatures and Acids", Food Science and Technology International, 12(1), pp.47~56 (2016), SAGE Publications[DOI]
- Haiqiang Chen, "Use of linear, Weibull, and log-logistic functions to model pressure inactivation of seven foodborne pathogens in milk", Food Microbiology, 24(3), pp.197~204 (2007), Elsevier BV[DOI]
- Ultan P. Cronin, "The growth, physiology and toxigenic potential of Bacillus cereus in cooked rice during storage temperature abuse", Food Control, 20(9), pp.822~828 (2009), Elsevier BV[DOI]
- L.L. Duffy, "Growth of Listeria monocytogenes on vacuum-packed cooked meats: effects of pH, aw, nitrite and ascorbate", International Journal of Food Microbiology, 23(3-4), pp.377~390 (1994), Elsevier BV[DOI]
- 엔크자갈 라왁사르나이, "전처리 나물류 및 구근류에서 병원성 미생물의 성장예측모델 개발 및 검증", 한국식품영양과학회지, 42(10), pp.1690~1700 (2013), 한국식품영양과학회
- Principles and guidelines for incorporating microbiological risk assessment in the development of food safety standards, guidelines and related textes. Report of a Joint FAO, "WHO Consultation ANNEX III", FAO, 2002, pp.18~22
- 조아현, "약수터 음용도구의 Bacillus cereus 분포 및 독소 특성", 한국식품위생안전성학회지, 32(1), pp.50~56 (2017), 한국식품위생안전성학회[DOI]
- Vijay K. Juneja, "Predictive model for growth of Bacillus cereus during cooling of cooked rice", International Journal of Food Microbiology, 290, pp.49~58 (2019), Elsevier BV[DOI]
- 강경아, "Development of Predictive Growth Models for Staphylococcus aureus and Bacillus cereus on Various Food Matrices Consisting of Ready-to-Eat (RTE) Foods", 한국축산식품학회지, 30(5), pp.730~738 (2010), 한국축산식품학회
- "Current state of exports and imports of laver in the last 5 years in Korea" (2019)[URL]
- 김애진, "회분식 광펄스 처리에 의한 마른 김의 비가열 살균", 한국식품과학회지, 46(6), pp.778~781 (2014), 한국식품과학회[DOI]
- 김기웅, "시판 건조김의 주요 영양성분", Food Science and Preservation, 21(5), pp.702~709 (2014), 한국식품저장유통학회
- 김수환, "비가공 농수산 식품소재의 미생물 오염분석", 한국식품과학회지, 38(4), pp.594~598 (2006), 한국식품과학회
- 김선영, "미산성 차아염소산수와 초음파를 처리한 당근에서 저장 중 Bacillus cereus 균의 생육 예측모델", 한국식품영양과학회지, 43(8), pp.1296~1303 (2014), 한국식품영양과학회
- Koseki S, "Prediction of pathogen growth on iceberg lettuce under real temperature history during distribution from farm to table", Int J Food Microbiol, 104, pp.239~248 (2007)[DOI]
- 권기언, "마른김(Pyropia spp.) 가공 공정 경과에 따른 미생물 오염도 분석", 한국수산과학회지, 51(1), pp.8~14 (2018), 한국수산과학회[DOI]
- 이춘수, "A Study on Laver Industry’s Global Export Competitiveness", 무역금융보험연구, 19(4), pp.175~192 (2018), 한국무역보험학회[DOI]
- 이은진, "시판 유통 김의 미생물 오염도, 사전 살균처리 및 전자선 조사 여부 확인", 한국식품과학회지, 49(1), pp.20~27 (2017), 한국식품과학회[DOI]
- 임영언, "한류(韓流)문화를 통한 한국이미지 변용에 관한 연구", 일어일문학연구, 84(2), pp.449~471 (2013), 한국일어일문학회[DOI]
- "Food code regulations in Korea" (2019)[URL]
- Microbial risk profile. MFDS Food Risk Assessment Department Report, "MFDS", MFDS, 3~38 (2016)
- "Current state of marine products exports in 2019" (2020)[URL]
- 문성양, "수학적 정량평가모델을 이용한 Listeria monocytogenes의 성장 예측모델의 개발", 한국식품과학회지, 37(2), pp.194~198 (2005), 한국식품과학회
- M Nauta, "A retail and consumer phase model for exposure assessment of Bacillus cereus", International Journal of Food Microbiology, 83(2), pp.205~218 (2003), Elsevier BV[DOI]
- Risk assessment of Bacillus cereus in pastes. NIFDS Food Risk Assessment Report, "NIFDS", NIFDS, 1~33 (2019)
- 박형수, "수육에서의 Staphylococcus aureus 성장 예측모델", 한국축산식품학회지, 30(3), pp.487~494 (2010), 한국축산식품학회
- Shin Young Park, "Predictive Modeling for the Growth of Aeromonas hydrophila on Lettuce as a Function of Combined Storage Temperature and Relative Humidity", Foodborne Pathogens and Disease, 16(6), pp.376~383 (2019), Mary Ann Liebert Inc[DOI]
- 박신영, "Predictive Modeling for the Growth of Salmonella Enterica Serovar Typhimurium on Lettuce Washed with Combined Chlorine and Ultrasound During Storage", 한국식품위생안전성학회지, 34(4), pp.374~379 (2019), 한국식품위생안전성학회[DOI]
- T. Ross, "Indices for performance evaluation of predictive models in food microbiology", Journal of Applied Bacteriology, 81(5), pp.501~508 (1996), Wiley[DOI]
- T Ross, "Predictive modelling of the growth and survival of Listeria in fishery products", International Journal of Food Microbiology, 62(3), pp.231~245 (2000), Elsevier BV[DOI]
- JEAN L. SCHOENI, "Bacillus cereus Food Poisoning and Its Toxins", Journal of Food Protection, 68(3), pp.636~648 (2005), International Association for Food Protection[DOI]
- ISABEL WALLS, "Validation of Predictive Mathematical Models Describing the Growth of Escherichia coli O157:H7 in Raw Ground Beef", Journal of Food Protection, 59(12), pp.1331~1335 (1996), International Association for Food Protection[DOI]
- Sungdae Yang, "A predictive growth model of Aeromonas hydrophila on chicken breasts under various storage temperatures", LWT - Food Science and Technology, 69, pp.98~103 (2016), Elsevier BV[DOI]
- 윤양호, "수질환경과 식물플랑크톤 군집 변화에 의한 압해도김 양식장의 해양환경과 생산", 환경생물, 32(3), pp.159~167 (2014), 한국환경생물학회
- Mohammed Ziane, "A quantitative microbiological exposure assessment of Bacillus cereus group IV in couscous semolina, Algeria", Microbial Risk Analysis, 11, pp.11~22 (2019), Elsevier BV[DOI]