CN102650632B - Method for evaluating shelf life of cooling pork at fluctuating temperature - Google Patents
Method for evaluating shelf life of cooling pork at fluctuating temperature Download PDFInfo
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Abstract
The invention relates to a method for evaluating the shelf life of cooling pork at fluctuating temperature. The method comprises the following steps of: (1) sample microorganism and sensory analysis; (2) microorganism growth prediction models; and (3) application and verification of the prediction models at the fluctuating temperature. The method has the advantages that a predictive microbiology method is applied to analyze the growth situations of aerobic bacteria in the cooling pork at different time points under different temperature conditions and establish the microorganism prediction models of the cooling pork at different storage temperatures so as to evaluate the edible safety of the cooling pork; the established prediction microorganism dynamical-models can effectively predict the shelf life of the cooling pork at the temperature of 4-15 DEG C; and a strong technical support is provided for monitoring and tracking the shelf life of the cooling pork under the environment condition with the fluctuating temperature in real time.
Description
Technical field
The present invention relates to meat products storage field, specifically, is a kind of method of evaluating chilled pork shelf life under fluctuating temperature that is applied to.
Background technology
Chilled pork is subject to consumers in general's welcome because of its good mouthfeel and security, and as the main consumption of meat food of Chinese Consumer's, the security of pork product has been subject to paying attention to widely and paying close attention to.So exploitation can be evaluated the technical method of chilled pork shelf life and security quickly and efficiently, not only for food consumption person, be all vital for retailer and meat industry.
In the situation that temperature control is proper, chilled pork in the low temperature of 0 ~ 4 DEG C, makes microbial growth in meat be subject to certain inhibition all the time.But if cold chain system is perfect not, it is improper to occur controlling in the processes such as storage, transport and sale, cause the variation of temperature control system or unsuccessfully elevate the temperature, microbes is bred rapidly, accelerates spoilage of fresh meat, thereby can form potential threat to public health.So, grasp the growth rhythm of microorganism under condition of different temperatures in meat, thereby its Changing Pattern is predicted, can reach the object of evaluating meat shelf life.It is that meat is surveyed sample that traditional product detects, not only waste time and energy, and result need to could judge to have certain hysteresis quality after 24 or 48 hours, do not have the effect of precognition, use mathematical model prediction can overcome these restrictions and be conducive to take effective preventive measure.
At production, transport, storage, the consumer phase of actual meat industrial chain, often occur that the situation of fluctuation occurs the residing environment temperature of chilled pork product, and residing environment temperature is higher, in chilled pork, the growth rate of microorganism can be faster, may make the security of chilled pork reduce, shelf life shortens, and brings food security hidden danger to consumer, brings economic loss to operator.
It is the new technology that developed recently gets up that food predictive microbiology is learned, its feature is not carry out under the prerequisite of microbiological analysis, if the temperature course that food experiences is known, can use microbiology prediction model to calculate the quantity of this microorganism in food, and estimate shelf life and the security of food as index.Although, microbiology prediction model is convenient, practical, but initial stage process of establishing needs a large amount of element tasks, need to carry out a large amount of microbiological analysiss and set up mathematical model, but model set up and verify its feasible after, the quality monitoring that just can be food provides strong technical support.
Chinese patent literature CN101576553A discloses a kind of shelf life forecasting model of chilled pork, from sense organ and physics and chemistry aspect, the pork being housed in 0 DEG C, 5 DEG C, 10 DEG C and 20 DEG C is carried out to experimental study, by the Functional Analysis of corresponding quality energy level, establishing the total volatile basic nitrogen order of reaction is 1 grade, based on the good correspondence of itself and sense organ value, be established as the index of fish freshness of pork, and according to this Index Establishment chilled pork shelf life prediction model.Chinese patent literature CN101949870A discloses a kind of method for predicting refrigerated carp freshness quality, by the research to refrigeration cultivation carp sense organ, chemistry and microbiology quality, determine the product shelf phase, adopt the relation of index relatively corrupt rate equation model description temperature and fish products freshness.But yet there are no report about a kind of microbiology prediction model of evaluating chilled pork shelf life under fluctuating temperature that is applied to.
Summary of the invention
The object of the invention is for deficiency of the prior art, a kind of method of evaluating chilled pork shelf life under fluctuating temperature that is applied to is provided.
For achieving the above object, the technical scheme that the present invention takes is: a kind of method of evaluating chilled pork shelf life under fluctuating temperature that is applied to, comprises the following steps:
(1) sample microorganism and organoleptic analysis: by chilled pork in 4 DEG C, 7 DEG C, 10 DEG C, 15 DEG C and two fluctuating temperatures, under 4 DEG C/12h ~ 7 DEG C/12h and 4 DEG C/12h ~ 10 DEG C/6h ~ 15 DEG C/6h, preserve, through reasonable time interval, carry out respectively microbe quantity quantitative determination and subjective appreciation;
(2) Microbiology Growth Prediction Model: 1. first-order model, adopts quantity that three stage linear models describe aerobic bacteria in the chilled pork under different reserve temperatures over time; 2. second-level model, selects respectively linear equation to describe μ
maxvariation with temperature and A variation with temperature, select power equation to describe λ variation with temperature;
(3) application of forecast model and checking under fluctuating temperature: set up first-order model is combined with second-level model, predict the aerobic bacteria number in chilled pork under two groups of fluctuating temperatures, and compare with actual measured value, with the accuracy of evaluation model.
In described step (1), micro organism quantity method for measuring is by the sample being housed under different temperatures, and sampling respectively adopts plate count agar to measure total aerobic bacteria.
Three stage linear models in described step (2) are:
Wherein, t is time (h), bacterium number (log when y is t
10cFU/g), A is maximum bacterium number (log
10cFU/g), μ
maxfor maximum specific growth rate (h
-1), λ is the lag phase (h) of growth of microorganism.
Second-level model in described step (2) is:
| Kinetic parameter | Regression equation |
| μ max (1/h) | y = 0.0082*t - 0.019 |
| λ (h) | y = 97*t ^ (-1.5) |
| A (log 10CFU/g) | A = 0.03*t +8.4 |
Wherein, t is time (h), bacterium number (log when y is t
10cFU/g), A is maximum bacterium number (log
10cFU/g), μ
maxfor maximum specific growth rate (h
-1), λ is the lag phase (h) of growth of microorganism.
The invention has the advantages that:
The microbiological method of applied forcasting of the present invention, by analyzing the growth pattern of the aerobic bacteria in different time points chilled pork under condition of different temperatures, set up the microbiology prediction model of chilled pork under different reserve temperatures, evaluate the edible safety of chilled pork with this, the predictive microbiology kinetic model of setting up can be predicted the shelf life of chilled pork under 4 ~ 15 DEG C of conditions effectively, for the shelf life of the chilled pork under the environmental baseline of Real-Time Monitoring and tracking temperature change provides strong technical support.
Brief description of the drawings
Accompanying drawing 1 is that under different reserve temperatures, in chilled pork, aerobic bacteria number is over time.
Embodiment
Below in conjunction with accompanying drawing, embodiment provided by the invention is elaborated.
The object of the invention is to, the microbiological method of applied forcasting, by analyzing the growth pattern of the aerobic bacteria in different time points chilled pork under condition of different temperatures, set up the microbiology prediction model of chilled pork under different reserve temperatures, evaluate the edible safety of chilled pork with this.
Embodiment
1 materials and methods
1.1 test material
Chilled pork: certain brand is killed rear 12h chilled pork (round).Purchase is placed on the interior laboratory of transporting back in 2h of heat barrier foam box that ice bag is housed.
1.2 test method
1.2.1 sample pretreatment
Microorganism and organoleptic analysis: sterile working is gone the chilled pork of buying after tendon degrease, be divided into 25g, the tissue block of thick approximately 2 ~ 3cm, after preservative film pallet packing, put into High Precision Low Temperature incubator, in (4 DEG C/12h ~ 7 DEG C/12h of 4 DEG C, 7 DEG C, 10 DEG C, 15 DEG C and two fluctuating temperatures, 4 DEG C/12h ~ 10 DEG C/6h ~ 15 DEG C/6h) lower storage, through reasonable time interval, carry out respectively microbe quantity quantitative determination and subjective appreciation.
1.2.2 total aerobic bacteria is measured
By the sample being housed under different temperatures, respectively at 0,1,2,3,4,5,6 d samplings (in 15 DEG C of storage experiments, sampling in every 0.5 day), according to GB/T 4789.2-2003 operations, adopt plate count agar to measure the total aerobic bacteria in chilled pork.
1.2.3 subjective appreciation
Press GB 2707-2005 standard, set up six people's subjective appreciation groups, in advance it is carried out to simple training.For each sample, group member will be to the color of raw meat and cold cuts, smell, structural state, surface state, local flavor, pliability, organize juice, meat soup color to mark, and every must be divided into the mean value of sense organ number that group member marks.The evaluation criterion of subjective appreciation is in table 1.If comprehensive grading (comprises 6) below 6, show that chilled pork has arrived sense organ refusal point.
Table 1 chilled pork subjective appreciation table
1.3 Microbiology Growth Prediction Model
1.3.1 first-order model
Over time, three stage linear models are as follows to adopt three classical stage linear models to simulate in the chilled pork under different reserve temperatures aerobic bacteria number:
Wherein, t is time (h), bacterium number (log when y is t
10cFU/g), A is maximum bacterium number (log
10cFU/g), μ
maxfor maximum specific growth rate (h
-1), λ is the lag phase (h) of growth of microorganism.
1.3.2 second-level model
For relation between evaluation temperature and growth parameter(s), μ
max, the relation between λ and A, selects respectively linear equation to describe μ
maxvariation with temperature and A variation with temperature, select power equation to describe λ variation with temperature.
1.3.3 the application of forecast model and checking under fluctuating temperature
The present invention combines set up first-order model with second-level model, predict the aerobic bacteria number in chilled pork under two groups of fluctuating temperatures, and compare with actual measured value, with the accuracy of evaluation model.The equal application software Microsoft Excel 2003 of above data processing and Origin7.5 complete.
2 interpretations of result
The sense organ shelf life of chilled pork under 2.1 constant and fluctuating temperatures
According to the sensory evaluation scores of chilled pork under different reserve temperatures over time, carry out linear regression, result is as following table, and in the time that sensory evaluation scores is 6, chilled pork reaches sense organ terminal.
The sense organ shelf life of chilled pork under table 2 constant temperature and fluctuating temperature
| Reserve temperature (DEG C) | Equation of linear regression | Sense organ shelf life (my god) |
| 4℃ | y = 8.07425 - 0.018*x | 4.80 |
| 7℃ | y = 8.52186 - 0.02666*x | 3.94 |
| 10℃ | y = 7.64881 - 0.02158*x | 3.18 |
| 15℃ | y = 7.9626 - 0.07352*x | 1.11 |
| 4℃/12h ~ 7℃/12h | y = 7.95575 - 0.02031*x | 4.01 |
| 4℃/12h~10℃/6h~15℃/h | y = 7.51246 - 0.01992*x | 3.16 |
The shelf life of chilled pork under the constant and fluctuating temperature of 2.2 applied forcasting model predictions
By microbiological analysis, can learn the total aerobic bacteria of different time points chilled pork under 4,7,10,15 DEG C of holding conditions.In microorganism count, chilled pork is carried out to subjective appreciation.In the time that sensory evaluation scores reaches 6, be sense organ refusal point, chilled pork reaches sense organ shelf life terminal.Bring respectively this time into set up predictive microbiology first-order model, get final product in the time of sense organ shelf life terminal, the corrupt level of the minimum of total aerobic bacteria in chilled pork: when aerobic bacteria number is about 10
7cFU/g(10
6.89cFU/g) time, chilled pork reaches sense organ terminal, so the microbiological indicator that the present invention sets chilled pork shelf life terminal is log
107CFU/g.
2.2.1 the first-order model of microorganism and second-level model
Shown by the storage experiment result under constant temperature, the microbial kinetics equation of setting up can be described in the impact of temperature on total aerobic bacteria growth in chilled pork within the scope of 4 ~ 15 DEG C well.In order to evaluate the reliability of set up model, need to be applied to predict the shelf life of chilled pork under 4 ~ 15 DEG C of fluctuating temperature conditions.And carry out the prediction effect (Fig. 1) of evaluation model by statistical analysis.
Table 3 second-level model
| Kinetic parameter | Regression equation |
| μ max (1/h) | y = 0.0082*t - 0.019 |
| λ (h) | y = 97*t ^ (-1.5) |
| A (log 10CFU/g) | A = 0.03*t +8.4 |
The verification method of the model under fluctuating temperature condition is as follows: Initial microorganisms quantity is to test obtained measured value by plate count, and maximum growth rate, lag phase and maximum bacterium number are to pass through set up second-level model gained.If temperature variation occurs in the lag phase of microorganism, bacterium is counted the first stage equation of three stage of computing application linear model, if temperature variation occurs in the exponential phase of microorganism, bacterium is counted the subordinate phase equation of three stage of computing application linear model, in the time that the maximum bacterium of micro organism quantity growth arrival is counted, reach stationary phase, bacterium number calculates with the phase III equation of three stage linear models.Predict the shelf life of chilled pork under four groups of steady temperatures and two groups of fluctuating temperatures in conjunction with set up first-order model and second-level model, and compare with sense organ shelf life, the prediction effect of model is evaluated, and result is as follows:
The sense organ shelf life of chilled pork and the comparison of model prediction shelf life under the constant and fluctuating temperature of table 4
| Reserve temperature/DEG C | Sense organ shelf life (my god) | Microbiology prediction model shelf life (my god) |
| 4℃ | 4.80 | 8.92 |
| 7℃ | 3.94 | 2.92 |
| 10℃ | 3.18 | 2.56 |
| 15℃ | 1.11 | 1.51 |
| 4℃/12h ~ 7℃/12h | 4.01 | 4.77 |
| 4℃/12h~10℃/6h~15℃/h | 3.16 | 2.84 |
The variance analysis of the sense organ shelf life of table 5 chilled pork and the comparison of model prediction shelf life
| Source | Degree of freedom | Quadratic sum | All sides | F value | P value |
| Model | 1 | 0.918533333 | 0.918533333 | 0.21109 | 0.65574 |
| |
10 | 43.5137333 | 4.35137333 | ? | ? |
Result demonstration, two kinds of methods of evaluating chilled pork shelf lifes are at 0.05 horizontal there was no significant difference.
3 conclusions
The predictive microbiology kinetic model that the present invention sets up can be predicted the shelf life of chilled pork under 4 ~ 15 DEG C of conditions effectively, for the shelf life of the chilled pork under the environmental baseline of Real-Time Monitoring and tracking temperature change provides strong technical support.
The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, do not departing under the prerequisite of the inventive method; can also make some improvement and supplement, these improvement and the supplementary protection scope of the present invention that also should be considered as.
Claims (1)
1. be applied to a method of evaluating chilled pork shelf life under fluctuating temperature, it is characterized in that, comprise the following steps:
(1) sample microorganism and organoleptic analysis: by chilled pork in 4 DEG C, 7 DEG C, 10 DEG C, 15 DEG C and two fluctuating temperatures, under 4 DEG C/12h ~ 7 DEG C/12h and 4 DEG C/12h ~ 10 DEG C/6h ~ 15 DEG C/6h, preserve, through reasonable time interval, carry out respectively microbe quantity quantitative determination and subjective appreciation;
(2) Microbiology Growth Prediction Model: 1. first-order model, adopts quantity that three stage linear models describe aerobic bacteria in the chilled pork under different reserve temperatures over time; 2. second-level model, selects respectively linear equation to describe μ
maxvariation with temperature and A variation with temperature, select power equation to describe λ variation with temperature;
(3) application of forecast model and checking under fluctuating temperature: set up first-order model is combined with second-level model, predict the aerobic bacteria number in chilled pork under two groups of fluctuating temperatures, and compare with actual measured value, with the accuracy of evaluation model,
In described step (1), micro organism quantity method for measuring is by the sample being housed under different temperatures, and sampling respectively adopts plate count agar to measure total aerobic bacteria,
Three stage linear models in described step (2) are:
Wherein, t is time (h), bacterium number (log when y is t
10cFU/g), A is maximum bacterium number (log
10cFU/g), μ
maxfor maximum specific growth rate (h
-1), λ is the lag phase (h) of growth of microorganism,
Second-level model in described step (2) is:
Wherein, t is time (h), bacterium number (log when y is t
10cFU/g), A is maximum bacterium number (log
10cFU/g), μ
maxfor maximum specific growth rate (h
-1), λ is the lag phase (h) of growth of microorganism.
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| CN103995965B (en) * | 2014-05-14 | 2017-02-22 | 东南大学 | Shelf life early-warning system and method based on microorganism predication model |
| CN104330539A (en) * | 2014-10-28 | 2015-02-04 | 浙江大学 | Chilled fresh pork shelf life span forecasting method based on internet of things architecture |
| CN108254513B (en) * | 2017-12-22 | 2020-12-29 | 北京农业信息技术研究中心 | Method and device for judging shelf life of fishes |
| CN108344841A (en) * | 2018-02-08 | 2018-07-31 | 杭州汇健科技有限公司 | A method of prediction refrigeration pasteurize fresh milk shelf life |
| CN109738600A (en) * | 2018-12-22 | 2019-05-10 | 河南农业大学 | A kind of construction method of cold chain meat products microorganism intermittent dynamic prediction model |
| CN111027784B (en) * | 2019-12-26 | 2023-04-18 | 上海市农业科学院 | Method for predicting shelf life of cold fresh chicken |
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| CN111257234A (en) * | 2020-03-25 | 2020-06-09 | 杭州御佳金属材料有限公司 | Microorganism concentration measuring method |
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