Establishment of growth probability model for Pseudomonas spp. in chilled pork with modified atmosphere package

Qiu Jing; Dong Qingli; Cheng Fei

Volume 28 Issue 13

Jun. 2012

Turn off MathJax

Article Contents

Abstract

References

Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE) > 2012 > 28(13): 257-262.

Qiu Jing, Dong Qingli, Cheng Fei. Establishment of growth probability model for Pseudomonas spp. in chilled pork with modified atmosphere package[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012, 28(13): 257-262.

Citation:

PDF (435 KB)

Establishment of growth probability model for Pseudomonas spp. in chilled pork with modified atmosphere package

More Information

Received Date: August 26, 2011
Revised Date: June 04, 2012
Published Date: June 30, 2012

Graphical Abstract

Abstract

Abstract

In order to extend the shelf life of chilled pock and to provide reference for the choice of atmosphere package, this study simulated the real production, and established the growth probability model of Pseudomonas spp. in chilled pork with atmosphere modified packaged at (4±1)℃. Logistic model was used to establish the growth/non-growth boundary of Pseudomonas spp. in different percentage of CO2. The disinfected pock was inoculated with Pseudomonas spp., which is one kind of specific spoilage organisms of the chilled pock. The results indicated that without CO2 or with low percentage of CO2, the growth probability of Pseudomonas spp. increased with the increase of percentage of O2 or the initial inoculation. With high percentage of CO2, the growth probability of Pseudomonas spp. was low, and not sensitive to the percentage of O2, and initial inoculation. The Logistic model performed well, which determination coefficient (r2) of the model was higher than 0.85, the determination coefficient (R2) of observed data and predicted data were all higher than 0.95, and the predicted accuracy was higher than 93.3%. Four predicted conditions of the probability model were defined as "effective-safe", "effective-dangerous", "ineffective-safe", "ineffective-dangerous" in this paper, which were used to evaluate the validity of the model and to ensure the safe choice of the atmosphere condition. The results can provide technological references for the choice of atmosphere condition in the chilled pock production.
- packaging,
- models,
- carbon dioxide,
- modified atmosphere,
- chilled pork,
- growth probability,
- Pseudomonas spp.

FullText(HTML)

References (31)

References

[1]	Ercolini D, Russo F, Torrieri E, et al. Changes in the spoilage-related microbiota of beef during refrigerated storage under different packaging conditions[J]. Applied and Environmental Microbiology, 2006, 72(7): 4371－4663.
[2]	McMillin K W. Where is MAP Going? A review and future potential of modified atmosphere packaging for meat[J]. Meat Science, 2008, 80(1): 43－65.
[3]	Bórnez R, Linares M B, Vergara H. Effect of different gas stunning methods on Manchega suckling lamb meat packed under different modified atmospheres[J]. Meat Science, 2010, 84(4): 727－734.
[4]	Marsh K, Bugusu B. Food packaging-Roles, materials, and environmental issues[J]. Food Science, 2007, 72(3): R39－R55.
[5]	Mcdonald K, Sun D W. Predictive food microbiology for the meat industry: a review [J]. International Journal of Food Microbiology, 1999, 52(1/2): 1－27.
[6]	Mejlholm O, Gunvig A, Borggaard C, et al. Predicting growth rates and growth boundary of Listeria monocytogenes- An international validation study with focus on processed and ready-to-eat meat and seafood[J]. International Journal of Food Microbiology, 2010, 141(3): 137－150.
[7]	Geysen S, Geeraerd A H, Verlinden BE, et al. Predictive modelling and validation of Pseudomonas fluorescens growth at at superatmospheric oxygen and carbon dioxide concentrations[J]. Food Microbiology, 2005, 22(2/3): 149－158.
[8]	Sutherland J P, Bayliss A J, Braxton D S. Predictive modeling of growth of Escherichia coli O157:H7: the effects of temperature, pH and sodium chloride[J]. International Journal of Food Microbiology, 1995(25): 29－49.
[9]	Neumeyer K, Ross T, McMeekin T A. Development of a predictive model to describe the effects of temperature and water activity on the growth of spoilage pseudomonads[J].International Journal of Food Microbiology, 1997, 38(1): 45－54.
[10]	Valero A, Podríguez M, Carrasco E, et al. Studying the growth boundary and subsequent time to growth of pathogenic Escherichia coli serotypes by turbidity measurements[J]. Food Microbiology, 2010, 27(6): 819－828.
[11]	Couvert O, Pinon A, Bergis H, et al. Validation of a stochastic modelling approach for Listeria monocytogenes growth in refrigerated foods[J]. International Journal of Food Microbiology, 2010(144): 236－242.
[12]	Souza Sant′Ana A, Dantigny P, Tahara A C, et al. Use of a logistic model to assess spoilage by Byssochlamys fulva in clarified apple juice[J]. International Journal of Food Microbiology, 2010, 137(2/3): 299－302.
[13]	Hwang C. The probability of growth of Listeria monocytogenes in cooked salmon and tryptic soy broth as affected by salt, smoke compound, and storage temperature[J]. Food Microbiology, 2009, 26(3): 253－258.
[14]	陈天寿. 微生物培养基的制造与应用[M].北京：中国农业出版社，1995，250－579.
[15]	李学英，杨宪时，郭全友，等. 大黄鱼腐败菌腐败能力的初步分析[J]. 食品工业科技，2009，30(6)：316－319.Li Xueying, Yang Xianshi, Guo Quanyou, et al. Preliminary analysis on the ability to spoilage of Pseudosciaena crocea' spoilage bacteria[J]. Science and Technology of Food Industry, 2009, 30(6): 316－319. (in Chinese with English Abstract)
[16]	董庆利，曾静，丁甜，等. 猪肉中气单胞菌生长与失活的Gompertz模型构建[J]. 食品科学，2011，32(11)：118－122.Dong QingLi, Zeng Jing, Ding Tian, et al. Establishment of Gompertz Model for the Growth and Inactivation of Aeromonas spp. in Pork[J]. Food Science, 2011, 32(11): 118－122. (in Chinese with English Abstract)
[17]	GB/4789.2-2008，食品卫生微生物学检验菌落总数测定[S]. 北京：中国标准出版社，2009-3-1.GB/4789.2-2008, Microbiological determination of total colonies numbers in food and hygiene[S]. Beijing: The Publishing House of the Chinese standard, 2009-3-1. (in Chinese with English Abstract)
[18]	Le Marc Y, Pin C, Baranyi J. Methods to determine the growth domain in a multidimensional environmental space[J]. International Journal of Food Microbiology, 2005, 100(1/2/3): 3－12.
[19]	Dang T D T, Mertens L, Vermeulen A, et al. Modelling the growth/no growth boundary of Zygosaccharomyces bailii in acidic conditions : A contribution to the alternative method to preserve foods without using chemical preservatives[J]. International Journal of Food Microbiology, 2010, 137(1): 1－12.
[20]	McKellar R C, Lu X, Delaquis P J. A probability model describing the interface between survival and death of Escherichia coli O157: H7 in a mayonnaise model system[J]. Food Microbiology, 2002, 19(2/3): 235－247.
[21]	Ratkowsky D A, Ross T. Modelling the bacterial growth/no growth interface[J]. Letters in Applied Microbiology, 1995, 20(1): 29－33.
[22]	LopezMalo A, Palou E. Modeling the growth/no-grwoth interface of Zygosaccharomyces bailii in mango puree[J]. Food Science, 2000(65): 516－520.
[23]	马丽珍，南庆贤，戴瑞彤. 不同气调包装方式的冷却猪肉在冷藏过程中的微生物变化[J]. 农业工程学报，2004，20(4)：160－164.Ma Lizhen, Nan Qingxian, Dai Ruitong. Microflora changes of chilled pork packaged in different modified atmosphere packages[J]. Transactions of The Chinese Society of Agricultural Engineering, 2004, 20(4): 160－164. (in Chinese with English Abstract)
[24]	Koutsoumanis K P, Stamatiou A P, Drosinos E H. Control of spoilage microorganisms in minced pork by a self developed modified atmosphere induced by the respiratory activity of meat flora[J]. Food Microbiology, 2008, 25(7): 915－921.
[25]	Soldatou N, Nerantzaki A, Kontominas M G, et al. Physicochemical and microbiological changes of 'Souvlaki'-A Greek delicacy lamb meat product : Evaluation of shelf-life using microbial, color and lipid oxidation parameters[J]. Food Chemistry, 2009, 113(1): 36－42.
[26]	Ravi Sankar C N, Lalitha K V, Jose L, et al. Effect of packaging atmosphere on the microbial attributes of pearlspot (Etroplus suratensis Bloch) stored at 0~2℃[J]. Food Microbiology,2009, 25(3): 518－528.
[27]	Vermeulen A, Gysemans K P M, Bernaerts K, et al. Modelling the influence of the inoculation level on the growth/no growth interface of Listeria monocytogenes as a function of pH, aw and acetic acid[J]. International Journal of Food Microbiology, 2009, 135(2): 83－89.
[28]	Skandamis P N, Stopforth J D, Kendall P A, et al. Modeling the effect of inoculum size and acid adaptation on growth/no growth interface of Escherichia coli O157:H7[J]. International Journal of Food Microbiology, 2007, 120(3): 237－249.
[29]	Bidlas E, Du T, Lambert R J W, et al. An explanation for the effect of inoculum size on MIC and the growth/no growth interface[J]. International Journal of Food Microbiology, 2008, 126(1/2):140－152.
[30]	Zhao L, Montville T J, Schaffner D W. Inoculum size of Clostridium botulinum 56A spores influence time-to-detection and percent growth-positive sample[J]. Food Science, 2000, 65(8): 1360－1375.
[31]	Valero A, Pérez-Rodríguez F, Carrasco E, et al. Modelling the growth boundaries of Staphylococcus aureus: Effect of temperature, pH and water activity[J]. International Journal of Food Microbiology, 2009, 133(1/2): 186－194.