CN102690860A - Growth prediction model for vibrio parahaemolyticus in penaeus vannawei and constructing method - Google Patents
Growth prediction model for vibrio parahaemolyticus in penaeus vannawei and constructing method Download PDFInfo
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- CN102690860A CN102690860A CN2012101856034A CN201210185603A CN102690860A CN 102690860 A CN102690860 A CN 102690860A CN 2012101856034 A CN2012101856034 A CN 2012101856034A CN 201210185603 A CN201210185603 A CN 201210185603A CN 102690860 A CN102690860 A CN 102690860A
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Abstract
The invention provides a growth prediction model for vibrio parahaemolyticus in penaeus vannawei, which is characterized in that =0.0322*(T-0.739) and R2=0.973, wherein is the maximum specific growth rate (h-1) of the vibrio parahaemolyticus and T is temperature (DEG C). The invention also provides a constructing method for the growth prediction model and an application thereof in prediction for the growth condition of the vibrio parahaemolyticus in the penaeus vannawei. The growth condition of the vibrio parahaemolyticus in the penaeus vannawei can be accurately, objectively and quantitatively reflected by the growth prediction model provided by the invention; the technical support is supplied to the quality control for the penaeus vannawei and the safety eating for the penaeus vannawei; the administrative department can conveniently, timely and accurately know the risk degree of food and make a supervising policy for industry and market; and the growth prediction model has wide application prospects in the aspects of safety evaluation, quality control, quality management, risk warning and risk assessment in the food industry.
Description
Technical field
The present invention relates to the predictive food microbiology technical field, specifically, is growth prediction model and the construction process of a kind of Vibrio parahemolyticus in Penaeus vannamei.
Background technology
Vibrio parahemolyticus (
Vibrio Parahaemolyticus) food poisoning that causes has been in the first place that mikrobe food is poisoned in China.China existing many owing to eat the report that the shrimp that polluted pathogenic Vibrio parahemolyticus causes poisoning by food.Penaeus vannamei (
Litopenaeus vannamei), also claim Environment of Litopenaeus vannamei Low, be one of last three large economy shrimps in the world today, also be the fine quality of " extra large shrimp is light to be supported ".In order to control the food origin disease that is caused by Vibrio parahemolyticus, Chinese scholars has obtained certain achievement in research aspect the predictive model of this bacterium.Yet domestic and international research focuses mostly on and under the condition in pure culture, carries out modeling, seldom has to probe into the growth change rule of pathogenic Vibrio parahemolyticus in food substrate at present.Thereby the growth prediction model of setting up can not react the growing state of Vibrio parahemolyticus in the Penaeus vannamei truly, and is little for the directive significance of safety evaluation, quality control and the management of foodstuffs industry and Risk-warning, risk assessment.
Summary of the invention
The objective of the invention is provides the growth prediction model of a kind of Vibrio parahemolyticus in Penaeus vannamei to deficiency of the prior art.
One purpose more of the present invention is that a kind of establishment method of above-mentioned growth prediction model is provided.
Another purpose of the present invention is that a kind of purposes of above-mentioned growth prediction model is provided.
For realizing above-mentioned purpose, the technical scheme that the present invention takes is:
The growth prediction model of a kind of Vibrio parahemolyticus in Penaeus vannamei:
=0.0322 * (T-0.739), R
2=0.973,
Wherein, μ
Max-Vibrio parahemolyticus maximum specific growth rate (h
-1); T-temperature (℃).
For realizing above-mentioned second purpose, the technical scheme that the present invention takes is: the construction process of the growth prediction model of a kind of aforesaid Vibrio parahemolyticus in Penaeus vannamei, and it may further comprise the steps:
A) activation of Vibrio parahemolyticus bacterial strain and be seeded to Penaeus vannamei;
B) postvaccinal Penaeus vannamei is put under the differing temps and preserves, and measures the strain growth curve;
C) foundation of one-level model: adopt in the Penaeus vannamei under the different reserve temperatures of linear modeling of three stages the Vibrio parahemolyticus number over time, three stage linear models are following:
Wherein, t-time (h); Bacterium number (log during y-t
10CFU/g); A-maximum bacterium number (log
10CFU/g); μ
Max-maximum specific growth rate (h
-1); The lag phase of λ-microorganism growth (h);
D) foundation of second-level model: the μ that obtains the one-level Model Calculation
MaxValue substitution square root model with corresponding temperature T:
=a
μ* (T-T
Min),
Wherein, μ
Max-Vibrio parahemolyticus maximum specific growth rate (h
-1); a
μ-μ
MaxThe slope of linear regression; T
Min-in theory the minimum temperature of microorganism growth (℃);
Obtain a
μAnd T
Min
Described method also comprises the following steps: the one-level model is combined with second-level model, comes prediction steps b) aerobic bacteria number under the described differing temps in the Vibrio parahemolyticus, and compare with actual measured value, with the accuracy of evaluation model.
For realizing above-mentioned the 3rd purpose, the technical scheme that the present invention takes is:
Aforesaid growth prediction model is the application in the Vibrio parahemolyticus growing state in the prediction Penaeus vannamei.
The invention has the advantages that: the present invention provides the growth prediction model of a kind of Vibrio parahemolyticus in Penaeus vannamei; And confirmed that through modelling verification this model can reflect the growing state of Vibrio parahemolyticus in Penaeus vannamei accurate, objective, quantitatively, for the quality control and the safe edible Penaeus vannamei of Penaeus vannamei provides technical support; This predictive model can be convenient to administrative authority and know the food degree of risk timely and accurately simultaneously; Formulate the Regulation Policy in industry and market; Be beneficial to the accurate instruction human consumer and carry out safe diet, having broad application prospects aspect safety evaluation, quality control and the management of foodstuffs industry and Risk-warning, the risk assessment.
Description of drawings
Accompanying drawing 1 is the growth curve chart of Vibrio parahemolyticus in Penaeus vannamei.
Embodiment
Below in conjunction with accompanying drawing embodiment provided by the invention is elaborated.
1. materials and methods
1.1 test strain and starting material
Vibrio parahemolyticus, in-80 ℃, 25% glycerine is preserved.
Penaeus vannamei: purchase the plant in the Pudong New Area, Shanghai in October, 2011, oxygenation is transported to the laboratory, is sub-packed in the sterile bag, and-80 ℃ of freezer storages are subsequent use.
1.2 test drug, consumptive material and equipment
Pancreas peptone soybean broth (TSB), 3% basic peptone water (3% APW), sulphur lemon courage sugarcane agar (TCBS), sampler bag, band filter membrane homogeneous bag is all purchased the overpass Technical responsibilities ltd in Beijing.
MIR-154 high precision low temperature incubator (SANYO GS SANYO company); Interscience Patting type homogenizer (French Interscience company); Biohazard Safety Equipment (giving birth to fork company); Quantitative pipettor (German Eppendorf company); MILLI-Q ultrapure water purification system (U.S. MILLIPORE company); Pressure steam sterilizer (SANYO GS); Electronic balance (Mei Tele company).
1.3 TP
1.3.1 the activation of bacterial strain and inoculation
The activation of bacterial strain: with-80 ℃; The Vibrio parahemolyticus that 25% glycerine is preserved lines the TCBS flat board; Picking is green behind 37 ℃ of cultivation 18h, the edge is smooth, and single colony inoculation of diameter 2-3mm is in 3% TSB substratum, 37 ℃; 150rpm cultivates 18h, with this initial inoculation liquid as Vibrio parahemolyticus.
The preparation of Penaeus vannamei: with frozen Penaeus vannamei in-80 ℃ of refrigerators in the high precision low temperature incubator 4 ℃ spend the night and thaw; Penaeus vannamei boiled in the deionized water that contains 3% NaCl boil 30min; Be transferred to Biohazard Safety Equipment, cool off 1.5h under the room temperature, the shrimp that selects 13 ± 2g is subsequent use.
The inoculation of bacterial strain: above-mentioned inoculation liquid is diluted to about 10
6CFU/ml is inoculated in the shrimp, makes the initial inoculation concentration of Penaeus vannamei be about 10
4CFU/ml at room temperature places 30min with the shrimp of the last bacterium liquid of inoculation and makes Vibrio parahemolyticus can fully be attached to the surface of Penaeus vannamei in Biohazard Safety Equipment, guarantee the homogeneity of initial bacterium amount in the sample as far as possible.
1.3.2 storage test and strain growth curve determination
Postvaccinal Penaeus vannamei is put into the aseptic sampler bag that seals, respectively at 12,15,20; 25,30,35; 40 ℃ and two groups of fluctuating temperatures (f1:30 ℃/2h ~ 18 ℃/2h, f2:37 ℃/1h ~ 18 ℃/1h ~ 28 ℃/1h) store, as the initial growth point; After this take a sample at interval in appropriate time, adopt colony counting method (TCBS) counting, each time point do 3 parallel.
1.4 the foundation of model
1.4.1 one-level model
Adopt three classical stage linear models to simulate in the Penaeus vannamei under the different reserve temperatures Vibrio parahemolyticus bacterium number over time, three stage linear models are following:
Wherein, t is time (h), the bacterium number (log when y is t
10CFU/g), A is maximum bacterium number (log
10CFU/g), μ
MaxBe maximum specific growth rate (h
-1), λ is the lag phase (h) of microorganism growth.
1.4.2 second-level model
This paper selects for use the square root model to describe the influence of temperature to the maximum specific growth rate of Vibrio parahemolyticus, and expression formula is following:
A wherein
μBe μ
MaxThe slope of linear regression; T
MinBe the notion of a hypothesis, be meant in theory temperature when microorganism growth does not have Metabolic activity (℃).The μ that the one-level model is tried to achieve
MaxCan draw a with the above-mentioned square root model of the temperature substitution of correspondence
μAnd T
Min
1.4.3 the checking under constant temperature and the fluctuating temperature
Deviation factors (Bias factor, B
f) and the accurate factor (Accuracy factor, A
f) two parameters are used to show the predictor of model and the degree of closeness between the experiment measured value, and verify the accuracy of institute's established model with this.This paper adopts B
fAnd A
fCome the accuracy of descriptive model under constant temperature and fluctuating temperature.B wherein
fAnd A
fExpression formula following:
Above data processing is all used the DMFit on-line prediction modeling tool (http://modelling.combase.cc/DMFitDB.aspx ComBaseID=CbpCool_40_1) of software Microsoft Excel 2003 and the exploitation of Something English institute and is accomplished.
2. result
2.1 the growth curve of Vibrio parahemolyticus in Penaeus vannamei
The growth curve of Vibrio parahemolyticus in Penaeus vannamei is as shown in Figure 1.Can find out that on scheming under 12-40 ℃ of holding conditions, along with the increase of time, the quantity of Vibrio parahemolyticus increases thereupon, along with increasing of temperature, the speed of growth of Vibrio parahemolyticus is accelerated thereupon.
2.2 one-level model
| |
12 ℃ | 15 |
20 ℃ | 25 |
30 ℃ | 35 |
40 ℃ |
| λ | 0 | 1.02199 | 0 | 0.16269 | 0.11563 | 0.75304 | 1.41818 |
| μ max | 0.107222 | 0.17262 | 0.46223 | 0.71304 | 0.82333 | 1.32911 | 1.44493 |
| A | 9.309936 | 9.25993 | 9.63995 | 9.06 | 9.22 | 9.44997 | 9.02995 |
Wherein, the MV of λ is 0.496h, and the MV of A is 9.281 log
10CFU/g is in the calculating below the value substitution of λ and A.
2.3 second-level model
With the influence of square root model-fitting temperature to the maximum specific growth rate of Vibrio parahemolyticus in Penaeus vannamei, equation does
=0.0322 * (T-0.739), R
2=0.973.
2.4 verification of model
The present invention combines the one-level model of being set up with second-level model, predict under three groups of steady temperatures and the two groups of fluctuating temperatures Vibrio parahemolyticus bacterium number in the Penaeus vannamei, and compares with actual measured value, with the accuracy of evaluation model.
The research proof, accurately factor prediction effect of representation model between 0.9-1.05 is good.This shows that the predictive model of these research and development can be predicted Vibrio parahemolyticus growing state in Penaeus vannamei under constant temperature and the fluctuating temperature condition accurately, objectively.
The above only is a preferred implementation of the present invention; Should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the inventive method; Can also make some improvement and replenish, these improvement and replenish and also should be regarded as protection scope of the present invention.
Claims (5)
1. the growth prediction model of a Vibrio parahemolyticus in Penaeus vannamei is characterized in that,
=0.0322 * (T-0.739), R
2=0.973,
Wherein, μ
Max-Vibrio parahemolyticus maximum specific growth rate (h
-1); T-temperature (℃).
2. the construction process of the growth prediction model of a Vibrio parahemolyticus as claimed in claim 1 in Penaeus vannamei is characterized in that it may further comprise the steps:
A) activation of Vibrio parahemolyticus bacterial strain and be seeded to Penaeus vannamei;
B) postvaccinal Penaeus vannamei is put under the differing temps and preserves, and measures the growth curve of bacterial strain;
C) foundation of one-level model: adopt in the Penaeus vannamei under the different reserve temperatures of linear modeling of three stages Vibrio parahemolyticus over time:
Wherein, t-time (h); Bacterium number (log during y-t
10CFU/g); A-maximum bacterium number (log
10CFU/g); μ
Max-maximum specific growth rate (h
-1); The lag phase of λ-microorganism growth (h);
D) foundation of second-level model: the μ that obtains the one-level Model Calculation
MaxValue substitution square root model with corresponding temperature T:
=a
μ* (T-T
Min),
Wherein, μ
Max-Vibrio parahemolyticus maximum specific growth rate (h
-1); a
μ-μ
MaxThe slope of linear regression; T
Min-in theory the minimum temperature of microorganism growth (℃);
Obtain a
μAnd T
Min
3. construction process according to claim 2; It is characterized in that; Described method also comprises the following steps: the one-level model is combined with second-level model; Come prediction steps b) Vibrio parahemolyticus number under the described differing temps in the Penaeus vannamei, and compare with actual measured value, with the accuracy of evaluation model.
4. according to claim 2 or 3 described construction processs, it is characterized in that, be transferred to Biohazard Safety Equipment after the described Penaeus vannamei inoculation, cool off 1.5h under the room temperature.
5. growth prediction model as claimed in claim 1 is the application in the Vibrio parahemolyticus growing state in the prediction Penaeus vannamei.
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Cited By (5)
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| CN104278072A (en) * | 2013-07-05 | 2015-01-14 | 徐州工程学院 | Method for bacteriostatic effect evaluation by inoculation of Vibrio parahaemolyticus in shrimps |
| CN105331700A (en) * | 2015-11-10 | 2016-02-17 | 上海海洋大学 | Construction method of molecular predication model of vibrio parahaemolyticus in litopenaeus vannamei |
| CN106022516A (en) * | 2016-05-16 | 2016-10-12 | 浙江大学 | Model and method for predicting cross contamination of vibrio parahaemolyticus at link of removing shell of prawn |
| CN110718266A (en) * | 2019-09-26 | 2020-01-21 | 青岛蔚蓝生物股份有限公司 | Establishment and application method of prediction model for evaluating safety of lactobacillus fermented food |
| CN111127239A (en) * | 2020-01-13 | 2020-05-08 | 吉林大学 | Method for establishing staphylococcus aureus growth prediction model in spinach juice |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104278072A (en) * | 2013-07-05 | 2015-01-14 | 徐州工程学院 | Method for bacteriostatic effect evaluation by inoculation of Vibrio parahaemolyticus in shrimps |
| CN105331700A (en) * | 2015-11-10 | 2016-02-17 | 上海海洋大学 | Construction method of molecular predication model of vibrio parahaemolyticus in litopenaeus vannamei |
| CN106022516A (en) * | 2016-05-16 | 2016-10-12 | 浙江大学 | Model and method for predicting cross contamination of vibrio parahaemolyticus at link of removing shell of prawn |
| CN106022516B (en) * | 2016-05-16 | 2020-09-18 | 浙江大学 | Method for predicting cross contamination of vibrio parahaemolyticus in prawn shelling link |
| CN110718266A (en) * | 2019-09-26 | 2020-01-21 | 青岛蔚蓝生物股份有限公司 | Establishment and application method of prediction model for evaluating safety of lactobacillus fermented food |
| CN110718266B (en) * | 2019-09-26 | 2023-07-14 | 青岛蔚蓝生物股份有限公司 | Establishment and application method of prediction model for evaluating safety of lactobacillus fermented food |
| CN111127239A (en) * | 2020-01-13 | 2020-05-08 | 吉林大学 | Method for establishing staphylococcus aureus growth prediction model in spinach juice |
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