CN102768711A - Microbiological risk assessment method for meat product processing procedure - Google Patents
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Abstract
The invention discloses a microbiological risk assessment method for the meat product processing procedure. The technical scheme is as follows: carding and processing; selecting proper modules; collecting risk data; giving the initial probability distribution of a specific batch of processed products, running the Bayesian forward inference to obtain the prevalence rate of the microbiological hazards at each node of a model as well as the bacterial colony quantity, and conducting the comprehensive assessment for the risk during the whole meat product processing procedure; collecting data in the production procedure at an end product or a certain link of the processing procedure, taking the microbe quantity at a node corresponding to the link in the model as known information so as to obtain the posterior probability at a node before the node, and positioning a link where the microbiological hazards are introduced or a link where the control measure looses efficacy. The invention has the benefits that the method can quantitatively assess the probability distribution of the microbe content in the food, so that the hazards can be discovered timely during the production process, the hazard links can be traced to the source and positioned, and the hazard scope is reduced.
Description
Technical field
The present invention relates to the risk assessment technology field, especially relate to the method for microorganism risk in a kind of qualitative assessment meat products process.
Background technology
Along with developing rapidly of economic globalization, the especially continuous expansion of food trade, the safety problem of food also just more and more internationalizes, and becomes the public health problem in the whole world.Food-safety problem is the human had rehemorrhage of direct relation not only, but also is having a strong impact on development economic and society.Food safety risk is mainly from the harm of physical property, chemical and three kinds of character such as biological.Biohazard comprises harmful bacterium, virus, parasite and insect.In China, the food-safety problem that is caused by microorganism harm reaches 40% of total amount, and invasive organism also is that present global food security endangers the most significantly.In the process of microorganism venture analysis, risk assessment is the core and the basis of whole analysis system.How more effectively to carry out the microorganism Quantitative Risk Assessment, be the focus and the forward position of current domestic and international research.
1998, the international food code council provided the principle and the guide of microorganism risk assessment in standard C AC/GL30-1999.It roughly is divided into qualitative risk assessment and Quantitative Risk Assessment two big classes with the microorganism risk assessment technology.Qualitative risk assessment is artificially risk to be divided into classifications such as basic, normal, high; To weigh the size of harm influence; Quantitative Risk Assessment then confirms the intake of hazardous material and human body produced the probability of ill-effect, and the relation between them is carried out mathematical description, and its result provides very big facility for risk management; But, modeling method is not provided in this standard.
In the prior art, adopt the Monte Carlo (Monte Carlo, MC) the microorganism risk evaluation model of analogy method, this model description the path in whole " from the farmland to the dining table ", and microorganism is to the risk of health.Each parameter in the MC model (for example pollution condition, consuming frequency, growth rate, period of storage) is represented by its distribution situation in numerical range; Therefore model the got data that must depend on parameter could be set up; Do not have modular structure, be difficult to as general microorganism Quantitative Risk Assessment model framework.
Summary of the invention
The objective of the invention is to overcome the existing middle defective that exists, a kind of method that can quantitatively carry out the microorganism risk assessment is provided, this kind method combines scenario analysis with the microorganism prediction, can be used for the Quantitative Risk Assessment of meat products processing microorganism.It through model, can assess the influence to food security of risk slowly-releasing strategy specific in food processing and the consumer behaviour or supposition scene through the prevalence rate of microorganism harm in each treatment step of description and the variation of concentration.The technical scheme that adopts is: a kind of meat products process microorganism methods of risk assessment, and it is characterized in that: said methods of risk assessment may further comprise the steps:
1) combing work flow, understand fully material mixing, split the processing parameter of relation and each operation link, understand the risk factors that influence the microorganism dynamic growth in the process;
2) select appropriate module, set up the risk path of microorganism in the meat products process, tentatively confirm the network structure of Bayes' risk assessment models;
3) collect risk data; Confirm the prior probability distribution and the conditional probability of each node in the Bayes' risk assessment models through the statistical study of risk data; The microbial numbers that is input as the output of its father node of node, harm are transferred to the amount of this node by other pollution source, are output as the microbial numbers of this node;
4) to a certain concrete batch converted products; Provide the initial probability distribution of each father node in the Bayes' risk assessment models; Operation Bayes forward reasoning; Obtain the prevalence rate and the colony counts of the microorganism harm generation of each node in the model, the risk of whole meat products process is done comprehensive assessment, also can carry out risk assessment certain the part process that begins from supplementary material reception link;
5) gather the data in the production run in the terminal point product or a certain link of process; Utilize the Bayes' risk assessment models; With in the model to the micro organism quantity of node that should link as Given information, operation Bayes backward reasoning draws the posterior probability on the node before this node; Be the prevalence rate and the colony counts of microorganism harm in the product on the node, locate the link that link that microorganism harm is introduced into or control measure lost efficacy thus.
Technical characterictic of the present invention also has: module comprises step 2):
Microorganism dynamic module, said microorganism dynamic module are described growth of microorganism, are received to suppress, be eliminated three kinds of situations, and its mathematical function expression formula is F (N
j)=F (N
J-1)+f
j, operation steps j wherein, f when microorganism is in growth conditions
jBe positive function, microorganism is in f when perhaps be eliminated by holddown
jIt is negative function;
The material processing module; Said material processing module is described the variation of microbial biomass in the meat products that material causes; Material is handled mixing and the fractionation comprise material, mixing be in the various raw material sources microbial profile with, fractionation is that the microorganism on the product is divided into many parts;
The harm shift module, said harm shift module is described frequency and the probability distribution thereof that risk factors are polluted meat products, mathematical description be if (0,0, P), expression, if risk does not exist, the probability distribution of microbial biomass is 0; If risk exists, the probability distribution of microbial biomass is P, and P can be a Discrete Distribution, also can continuous distribution; Microorganism is transferred to the ratio of the amount on the food and representes that with function g g is relevant with factors such as running time, temperature, contacts area.
Technical characterictic of the present invention also has: processing parameter described in the step 1) comprises that running time, temperature, operating personnel contact the mode of meat products, use the disinfection way of equipment utensil and the frequency of sterilizing.
Technical characterictic of the present invention also has: risk factors described in the step 1) comprise temperature, environmental health situation, operating personnel's sanitary conditions, use the sanitary conditions of establishing utensil.
Technical characterictic of the present invention also has: said microorganism is not produce ectotoxic food borne bacteria, cause human infection through the absorption to viable bacteria, comprises salmonella.
Technical characterictic of the present invention also has: said salmonella is present in the round ham, and production procedure described in the step 1) comprises:
11) raw material receives: the round ham raw material is generally freezing pork; Go into the library storage certain hour after the buying, storing temperature-18 ℃, the risk factors that this link need be considered comprise the bacterial bearing rate and the content of molds of raw meat; The storage temperature of raw material and time, the growth of salmonella is suppressed in the storing process;
12) thaw: this link need be considered the environment that thaws of raw meat, and major risk factors is the temperature variation when thawing, and the temperature rising can cause Salmonella growth in this link, to be lower than 12 ℃ as a reference;
13) add auxiliary material: auxiliary material itself may be by salmonella-polluted; Therefore need to consider the bacterial bearing rate and the content of molds of auxiliary material; Add auxiliary material simultaneously and changed the inventory of goods in process; Have material mixed process, this link need use harm to shift and two process risk module of mixing of materials are described;
14) tumbling: this link is supplementary material to be put into the tumbling machine handle, and mainly considers the time of tumbling, and because the tumbling machine sterilization thoroughly possibly not introduced the pollution of salmonella, the workshop temperature is not higher than 12 ℃;
15) can: the risk factors that this link need be considered comprise that meat stuffing enters to the intact required time of can and the temperature of product, and maybe be because bottle placer introducing salmonella-polluted; The sausage that is filled into casing is at this link merogenesis, so this link need comprise that material splits module, and the workshop temperature is not higher than 12 ℃;
16) boiling and drying: this link operation can suppress microbial growth in the product, and the risk factors that need to consider comprise temperature and duration, and steaming temperature is 82～83 ℃, and the time is more than 30 minutes; The food deep temperature must reach 80 ℃, and salmonella could be dead; Come out of the stove when reducing to product temperature below 38 ℃ after the boiling, carry out putting into chilling room after the cooling of cold water spray, between airing, dry up surperficial steam;
17) packing: this link need consider that the workshop temperature remains on below 12 ℃ because wrappage are introduced the risk of harm;
18) vanning warehouse-in: this link need be considered duration and the warehouse temperature of product in the warehouse storage, and the finished product storing temperature is at 0～4 ℃.
Technical characterictic of the present invention also has: said microorganism is the monocyte hyperplasia listeria spp.
Technical characterictic of the present invention also has: said monocyte hyperplasia listeria spp is present in the low temperature sandwich ham, and production procedure described in the step 1) comprises:
11) raw meat thaws: about 0 ℃ of meat central temperature, surface temperature are below 8 ℃, and the operation room temperature is below 15 ℃, and the cube meat of choosing weighs 0.7～1.0 kilogram;
12) pickle: amount on the rocks is no less than 1/3 of the salt water yield during butcher's meat, and phosphate will thoroughly dissolve with warm water, and the brine temp for preparing is lower than 5 ℃, and injection volume should be controlled at more than 35%; Pressure, speed will be stablized, and when injector breaks down, should stop charging at once; And between the meat of choosing pushed refrigerator or pickle, injection back temperature was not higher than 8 ℃, and pickling a temperature should be at-2～4 ℃; The tumbling revolution is no less than 1080 circles when pickling, and goes out jar temperature at 5～8 ℃, and salting period is no less than 16 hours;
13) batching: the secondary tumbling number of turns be no less than 1440 the circle, go out jar temperature at 5～8 ℃, go out jar after; With the meat grinder in 25 millimeters apertures strand system, the filling temperature should be about 8 ℃ after the strand with material, from the secondary tumbling to filling; Should carry out as early as possible, undesired like equipment, should with the filling for preparing in time push pickle between in;
14) record: semi-manufacture are the storage period before sterilization, is no more than 20 minutes summer, is no more than 40 minutes winter, if overstock too much, in time with semi-manufacture push pickle between, and stop to record;
15) sterilization: the sterilization water changes weekly once winter, and change once 2 days summers, and to guarantee clean water quality, especially pressure should keep stable during back-pressure, and product fully cools off the retorts planted agent, and central temperature can take the dish out of the pot below 25 ℃;
16) refrigeration: the product that will take the dish out of the pot is rinsed well, dries, and is labelled, is stored in the refrigerator, and the refrigerator temperature should be at 0～4 ℃, and the principle by FIFO during outbound is carried out.
Beneficial effect of the present invention is: 1) the invention provides a kind of qualitative assessment method of microorganism risk in the meat products after processing; Can provide pollution frequency and level through microorganism harm in the meat products of processing back; Be applicable to batch being the process that unit carries out; Through microorganism dynamic growth, material are handled, the risk factors modularization; Set up the risk path of microorganism in process, the microorganism risk assessment solution of process is provided, realize assessment microorganism harm contamination probability and level in the food after processing.
2) the invention discloses the process risk assessment procedures, the probability distribution of content of microorganisms in the ability qualitative assessment food is convenient among production run, in time find harm; Trace to the source and locate the harm link; In time realize the adjustment of production line, reduce damaging range, reduced loss; Practice thrift cost, improved microorganism risk ability in enterprise's prevention and the control food processing process.
Description of drawings
Accompanying drawing 1 is embodiment one work flow and microorganism risk module map, and accompanying drawing 2 is embodiment two work flows and microorganism risk module map.
Embodiment
Below in conjunction with embodiment, the present invention is specified.The microorganism risk assessment be intended to obtain in the food pathogen or toxin in supply chain dynamically, approach and produce all real informations such as source, comprise raw-material background, the producer and equipment characteristic and consumer's use etc.Risk assessment also will provide information of forecasting to help the influence in management new raw material source; The composition of product; The change of consumer groups and control measure comprise the evaluation of human degree of exposure actual or prediction, in addition; Also to pay close attention to content and the toxic degree of microorganism in the starting material, estimate the influence and the change in each stage in the supply chain.
For microbiological factor, risk assessment is the basis with food by the potential degree of microorganism or endotoxin contamination and meals information, hopes the bacterial bearing rate of route of exposure different phase; The data of being reported should provide the full details of research method, comprises sampling spot/time, the relation of sample and total number, and employed micro-biological process; Encouragement obtains quantitative data, if such data have been arranged, just can carry out sufficient risk assessment, with the effect (like chlorination in chilled water) of investigation reduction risk policy, and perhaps relatively other optional measures (cooling is cooled off immersion liquid like air).
At occurring in nature, mathematical model can enough static state or is dynamically described.A process is described on full-time ground of dynamic model, and the static model consideration is a stage of certain process on the particular point in time.Dynamic model is generally constructed by the differential equation, and this equation is used in the speed of full-time interior descriptive model variable change.What static model were considered is the possibility that incident takes place in special time; The possibility that for example infects by the consumption of fryer product; Or over a period to come, in 1 year, infect the possibility of introducing, but the secondary model of many assessments also can be included into dynamic model on some degree.
The level of microorganism cause of disease bacterium is dynamic; Even when its level is very low; If reasonable time and temperature are arranged; It also can be bred very soon, so risk assessment will describe from producing to the whole approach of consuming, and the evaluation personnel will predict the scope that possibly expose so that it can react the influence of processing link to food.Aspects such as for example health design, cleaning-sterilizing, time and temperature and consumption mode.
To the risk assessment of different link microorganism, can set up a plurality of models or single model, each model all has the unit module of oneself.
Risk assessment is under certain confidence level, estimates the possibility that microorganism cause of disease bacterium and microbial toxin take place in consumption.Need to consider whether component helps the pathogen growth in the food, whether in the following process process, adopt incorrect processing; Influence growth of microorganism and dead processing, packing, storage environmental baseline; These conditions mainly comprise the gas composition of storage temperature, envionmental humidity and environment etc.; Also have other correlative factors in addition, such as the existence of pH value, moisture, water activity, nutrient content, antibacterial material and the existence of competition microorganism etc.; Pathogen contamination frequency and level in these food, for example these influence factors have that microbial ecological, starting material initially pollute in pathogen characteristic, the food; Consumption mode, relevant with consumption mode have social economy, culture background, religious belief, seasonality, age differences, areal variation and consumer taste and a behavior.
Each pathogen or the toxin information that produces, increase and reduce of main Collection and analysis in the risk assessment process in stage, and estimate its influence to product.
1) harmful microorganism in the raw material: the frequency of contamination of raw material and level; The contamination of raw material scope; Data Source (sample analysis or predictability); The uncertainty and the changeability of assessment.
2) influence of processing and depollution: results before the raw material processing, the influence of handling and storing, all processing and decontamination steps are to the level affects of pathogen after production; The uncertainty and the changeability of assessment.
3) generation of pathogen toxin: the possibility of microorganisms toxin in raw material and the product; The changeability and the uncertainty of assessment.
4) process or depollute after pollution again: pollute frequency in the finished product again; The level of pollution again takes place in the processing and the back of depolluting; The changeability and the uncertainty of assessment.
Does 5) primary package: the back product that depollutes have primary package? How it to stoping the validity polluted again before consumption if having? Frequency and the quantity polluted again after the packing; The changeability and the uncertainty of assessment.
The influence of 6) storing and selling: storage and the environment of selling reach the influence to the harm level generation of product; Influence for toxin producing microorganism storage condition; The changeability and the uncertainty of assessment.
7) influence of the food preparation or the cooking: food in the preparation or the cooking to the influence of microorganism level and toxin level; The changeability and the uncertainty of assessment.
8) consumer uses: pollute in the product consumption again; The changeability and the uncertainty of assessment.
9) food intake: certain scenarios or the level of food consumption after the regular period; The changeability and the uncertainty of assessment.
10) expose evaluation: harm is in the possible level of a certain consuming point; The changeability and the uncertainty of assessment.
As the present invention; The invention discloses a kind of meat products process microorganism methods of risk assessment; Meat products is meant and uses livestock and poultry meat to be primary raw material; Through cold cuts manufactured goods or semi-manufacture that seasoning is made, like sausage, ham, Baconic, sauce halogen meat, barbecue meat etc., this kind methods of risk assessment may further comprise the steps:
1) combing work flow; Understand fully the processing parameter of mixing, fractionation relation and each operation link of material; This processing parameter can be mode, the disinfection way that uses the equipment utensil and the sterilization frequency etc. that running time, temperature, operating personnel contact meat products; Understand the risk factors that influence the microorganism dynamic growth in the process, risk factors can be temperature, environmental health situation, operating personnel's sanitary conditions, use the sanitary conditions of equipment utensil;
2) select appropriate module, set up microorganism harm risk path in the meat products process, tentatively confirm the network structure of Bayes' risk assessment models, module comprises:
Microorganism dynamic module, said microorganism dynamic module are described growth of microorganism, are received to suppress, be eliminated three kinds of situations, and its mathematical function expression formula is F (N
j)=F (N
J-1)+f
j, operation steps j wherein, f when microorganism is in growth conditions
jBe positive function, microorganism is in f when perhaps be eliminated by holddown
jIt is negative function;
The material processing module; Said material processing module is described the module of the variation of microbial biomass in the meat products that material causes; Material is handled mixing and the fractionation comprise material, mixing be in the various raw material sources microbial profile with, fractionation is that the microorganism on the product is divided into many parts;
The harm shift module, said harm shift module is described frequency and the probability distribution thereof that risk factors are polluted meat products, mathematical description be if (0,0, P), expression, if risk does not exist, the probability distribution of microbial biomass is 0; If risk exists, the probability distribution of microbial biomass is P, and P can be a Discrete Distribution, also can continuous distribution; Microorganism is transferred to the ratio of the amount on the food and representes that with function g g is relevant with factors such as running time, temperature, contacts area;
3) collect risk data; Confirm the prior probability distribution and the conditional probability of each node in the Bayes' risk assessment models through the statistical study of risk data; The microbial numbers that is input as the output of its father node of node, harm are transferred to the amount of this node by other pollution source, are output as the microbial numbers of this node;
4) to a certain concrete batch converted products; Provide the initial probability distribution of each father node in the Bayesian network risk evaluation model; Operation Bayes forward reasoning; Obtain the prevalence rate and the colony counts of the microorganism harm generation of each node in the model, the risk of whole meat products process is done comprehensive assessment, also can carry out risk assessment certain the part process that begins from supplementary material reception link;
5) gather the data in the production run in the terminal point product or a certain link of process; Utilize the Bayesian network risk evaluation model; In model to the micro organism quantity of node that should link as Given information, operation Bayes backward reasoning draws the posterior probability on this node node until then; Be the prevalence rate and the colony counts of microorganism harm in the product on the node, locate the link that link that microorganism harm is introduced into or control measure lost efficacy thus.
This kind methods of risk assessment and conventional analogue appraisal procedure are compared, see table 1.
Table 1: disclosed methods of risk assessment and conventional analogue methods of risk assessment are relatively among the present invention
Embodiment one: round ham process salmonella methods of risk assessment.
Salmonella is had a liking for warm nature, 37 ℃ of optimum growth temperatures, but also can growth and breeding in the time of 18～20 ℃, and suitable winter resistance is arranged.Brine tolerance is very strong, in the salted fish of saliferous 10%～15%, butcher's meat, can survive 2～3 months.Well-grown under the high-moisture activity, growth is suppressed below 0.94 when water activity is lower than, and heat impedance is poor, just can be killed in 20～30 minutes at 60 ℃ of warps.
Step 1: combing production procedure, investigation various risks factor.
1) raw material receives: the raw material of round ham is generally freezing pork, goes into the library storage regular hour after the buying, storing temperature-18 ℃.The risk factors that this link need be considered comprise the bacterial bearing rate and the content of molds of raw meat, and the storage temperature of raw material and time, the growth of salmonella is suppressed in the storing process;
2) thaw: this link need be considered the environment that thaws of raw meat, and major risk factors is the temperature variation when thawing, and the temperature rising can cause Salmonella growth in this link, to be lower than 12 ℃ as a reference;
3) add auxiliary material: therefore auxiliary material itself may be needed to consider the bacterial bearing rate and the content of molds of auxiliary material by salmonella-polluted; Add auxiliary material simultaneously and changed the inventory of goods in process, have material mixed process; Therefore this link need use harm to shift and two process risk module descriptions of mixing of materials;
4) tumbling: this link is supplementary material to be put into the tumbling machine handle, and mainly considers the time of tumbling, and because the tumbling machine sterilization thoroughly possibly not introduced the pollution of salmonella, the workshop temperature is not higher than 12 ℃;
5) can: the risk factors that this link need be considered comprise that meat stuffing enters to the intact required time of can and the temperature of product, and maybe be because bottle placer introducing salmonella-polluted; The sausage that is filled into casing is at this link merogenesis, so this link need comprise that material splits module,, the workshop temperature is not higher than 12 ℃;
6) boiling and drying: this link operation can suppress microbial growth in the product, and the risk factors that need to consider comprise temperature and duration, and steaming temperature is 82～83 ℃, and the time is more than 30 minutes; The food deep temperature must reach 80 ℃, and salmonella could be dead; Come out of the stove when reducing to product temperature below 38 ℃ after the boiling, carry out putting into chilling room after the cooling of cold water spray, between airing, dry up surperficial steam;
7) packing: this link need consider that the workshop temperature remains on below 12 ℃ because wrappage are introduced the risk of harm;
8) vanning warehouse-in: this link need be considered duration and the warehouse temperature of product in the warehouse storage, and the finished product storing temperature is at 0～4 ℃.
Step 2: set up risk path salmonella-polluted in the round ham process, the corresponding process risk module of each link of identification processing is seen Fig. 1.
The pollution source of salmonella roughly can be decomposed into raw material, auxiliary material, tumbler, bottle placer, five sources of wrappage, so above-mentioned five harm shift modules are arranged in the model;
In process, the processing parameter of each operation link is understood the dynamic growth that influence salmonella like thaw point, tumbling temperature, can temperature, steaming temperature, storage temperature etc., describes with the microorganism dynamic module accordingly in the model; Particularly, the link of thawing, tumbling link, can link are the growth of microorganism module, and steaming and put in storage the storage link is that microorganism suppresses module;
In the tumbling link, because the mixing that the adding of auxiliary material has produced material is described with the material processing module; In the packing link, the lot product is packaged as the pouch product by branch, splits with the material in the material processing module and describes.
Step 3: collect risk data, confirm the prior probability distribution and the conditional probability of node in the model through the statistical study of risk data, node variable depends on conditional probability, and table 2 has provided example with table 3.Node variable Y depends on X, and conditional probability P (Y|X)=P (X, Y)/P (X).
Table 2: risk data table
| N | N 1 | N 2 | N 3 | N 4 | N 5 | N 6 | N 7 | N 8 | N 9 |
| 1 | Very | 0.01 | 1.0233 | Very | 1.04 | 1.0965 | 2.1365 | 1.53 | 0.32 |
| 2 | Very | 0.20 | 1.5849 | False | 0 | 0 | 1.5849 | 0.24 | 0.06 |
| 3 | Very | 0.15 | 1.4125 | Very | 1.06 | 1.1482 | 2.2082 | 1.86 | 0.49 |
| 4 | Very | 0.08 | 1.2023 | Very | 1.02 | 1.0471 | 2.0671 | 1.72 | 0.43 |
| … | … | … | … | … | … | … | … | … | … |
Table 3: node/variable/probability distribution table
Step 4: according to the conditional probability rational formula, operation Bayes forward reasoning, the microorganism that obtains each node in the model endangers prevalence rate and the colony counts that takes place, and the risk of meat products process is done assessment.
Step 5: to a certain concrete batch converted products; Terminal point product or a certain link in process are gathered the data in the production run; Microorganism harm or the harm quantity for example on production line, utilizing the fast detecting appearance to detect can not to occur exceed standard, and utilize the Bayesian network risk evaluation model, in model with the micro organism quantity of this link corresponding nodes as Given information; Utilize formula P (Y|X)=P (X; Y) (X Y) moves Bayes's backward reasoning to P (X)/∑ xP, draws the posterior probability on this link node before; Be the prevalence rate and the colony counts of microorganism harm in the product on the node, locate the link that link that microorganism harm is introduced into or control measure lost efficacy thus.
Embodiment two: Listeria monocytogenes methods of risk assessment in the low temperature sandwich ham.
The monocyte hyperplasia listeria spp all can be grown at 5～45 ℃, at 5 ℃ of low-temperature epitaxies, is the characteristic of this bacterium.This bacterium can kill through 58～59 ℃ in 10 minutes, can survive 1 year at-20 ℃.This bacterium is alkaline-resisting not acidproof, is still can grow in 9.6 o'clock in the pH value, in 10%NaC l, can grow.20%NaC l at 4 ℃ can be survived for 8 weeks, and 63 ℃ of heating are dead more than 10 minutes.Do not influence this bacterium survival in the common cure foods, can resist repeatedly freezing, ultraviolet ray irradiation.
Step 1: combing production procedure, investigation various risks factor.
1) raw meat thaws: about 0 ℃ of meat central temperature, surface temperature are below 8 ℃, and the operation room temperature is below 15 ℃, and the cube meat of choosing weighs the 0.75-1.0 kilogram;
2) pickle: amount on the rocks is no less than 1/3 of the salt water yield during butcher's meat, and phosphate will thoroughly dissolve with warm water, and the brine temp for preparing is lower than 5 ℃, and injection volume should be controlled at more than 35%, and pressure, speed will be stablized.If injector breaks down, should stop charging at once, and the meat of choosing is pushed away people's refrigerator (between pickling).Injection back temperature is not higher than 8 ℃, and pickling a temperature should be at-2～4 ℃.The tumbling revolution is no less than 1080 circles when pickling, and goes out jar temperature at 5～8 ℃, and salting period is no less than 16 hours;
3) batching: the secondary tumbling number of turns is no less than 1440 circles, goes out jar temperature at 5～8 ℃, go out jar after, with the meat grinder in 25 millimeters apertures strand system, the filling temperature should be about 8 ℃ after the strand with material., should carry out as early as possible to filling from the secondary tumbling, if chance equipment is undesired, should with the filling for preparing in time push pickle between in;
4) record: semi-manufacture are the storage period before sterilization, is no more than 20 minutes summer, is no more than 40 minutes winter, if overstock too much, in time with semi-manufacture push pickle between, and stop to record;
5) sterilization: the sterilization water changes weekly once winter, and change once 2 days summers, to guarantee clean water quality.Especially pressure should keep stable during back-pressure.Product fully cools off the retorts planted agent, and central temperature can take the dish out of the pot below 25 ℃;
6) refrigeration: the product that will take the dish out of the pot is rinsed well, dries, and is labelled, is stored in the refrigerator.The refrigerator temperature should be at 0～4 ℃; Principle by FIFO during outbound is carried out.
Step 2: set up the risk path that the monocyte hyperplasia listeria spp pollutes in the low temperature sandwich ham process, the corresponding process risk module of each link of identification processing is seen Fig. 2.
Step 3: collect risk data, confirm the prior probability distribution and the conditional probability of node in the model through the statistical study of risk data, table 2 has provided example with table 3.
Step 4: according to the conditional probability rational formula, operation Bayes forward reasoning, the microorganism that obtains each node in the model endangers prevalence rate and the colony counts that takes place, and the risk of meat products process is done assessment,
Step 5: to a certain concrete batch converted products; Terminal point product or a certain link in process are gathered the data in the production run; Microorganism harm or the harm quantity for example on production line, utilizing the fast detecting appearance to detect can not to occur exceed standard, and utilize the Bayesian network risk evaluation model, in model with the micro organism quantity of this link corresponding nodes as Given information; Utilize formula P (Y|X)=P (X; Y) (X Y) moves Bayes's backward reasoning to P (X)/∑ x P, draws the posterior probability on this link node before; Be the prevalence rate and the colony counts of microorganism harm in the product on the node, locate the link that link that microorganism harm is introduced into or control measure lost efficacy thus.
Certainly, above-mentioned explanation is not a limitation of the present invention, and the present invention also is not limited only to above-mentioned giving an example, and variation, remodeling, interpolation or replacement that those skilled in the art are made in essential scope of the present invention also belong to protection scope of the present invention.
Claims (8)
1. meat products process microorganism methods of risk assessment, it is characterized in that: said methods of risk assessment may further comprise the steps:
1) combing work flow, understand fully material mixing, split the processing parameter of relation and each operation link, understand the risk factors that influence the microorganism dynamic growth in the process;
2) select appropriate module, set up the risk path of microorganism in the meat products process, tentatively confirm the network structure of Bayes' risk assessment models;
3) collect risk data; Confirm the prior probability distribution and the conditional probability of each node in the Bayes' risk assessment models through the statistical study of risk data; The microbial numbers that is input as the output of its father node of node, harm are transferred to the amount of this node by other pollution source, are output as the microbial numbers of this node;
4) to a certain concrete batch converted products; Provide the initial probability distribution of each father node in the Bayes' risk assessment models; Operation Bayes forward reasoning; Obtain the prevalence rate and the colony counts of the microorganism harm generation of each node in the model, the risk of whole meat products process is done comprehensive assessment, also can carry out risk assessment certain the part process that begins from supplementary material reception link;
5) gather the data in the production run in the terminal point product or a certain link of process; Utilize the Bayes' risk assessment models; With in the model to the micro organism quantity of node that should link as Given information, operation Bayes backward reasoning draws the posterior probability on the node before this node; Be the prevalence rate and the colony counts of microorganism harm in the product on the node, locate the link that link that microorganism harm is introduced into or control measure lost efficacy thus.
2. according to the described meat products process of claim 1 microorganism methods of risk assessment, it is characterized in that: step 2) described in module comprise:
Microorganism dynamic module, said microorganism dynamic module are described growth of microorganism, are received to suppress, be eliminated three kinds of situations, and its mathematical function expression formula is F (N
j)=F (N
J-1)+f
j, operation steps j wherein, f when microorganism is in growth conditions
jBe positive function, microorganism is in f when perhaps be eliminated by holddown
jIt is negative function;
The material processing module; Said material processing module is described the variation of microbial biomass in the meat products that material causes; Material is handled mixing and the fractionation comprise material, mixing be in the various raw material sources microbial profile with, fractionation is that the microorganism on the product is divided into many parts;
The harm shift module, said harm shift module is described frequency and the probability distribution thereof that risk factors are polluted meat products, mathematical description be if (0,0, P), expression, if risk does not exist, the probability distribution of microbial biomass is 0; If risk exists, the probability distribution of microbial biomass is P, and P can be a Discrete Distribution, also can continuous distribution; Microorganism is transferred to the ratio of the amount on the food and representes that with function g g is relevant with factors such as running time, temperature, contacts area.
3. according to the described meat products process of claim 1 microorganism methods of risk assessment, it is characterized in that: processing parameter described in the step 1) comprises that running time, temperature, operating personnel contact the mode of meat products, use the disinfection way of equipment utensil and the frequency of sterilizing.
4. according to the described meat products process of claim 1 microorganism methods of risk assessment, it is characterized in that: risk factors described in the step 1) comprise temperature, environmental health situation, operating personnel's sanitary conditions, use the sanitary conditions of equipment utensil.
5. according to the described meat products process of claim 1 microorganism methods of risk assessment, it is characterized in that: said microorganism is not produce ectotoxic food borne bacteria, causes human infection through the absorption to viable bacteria, comprises salmonella.
6. according to the described meat products process of claim 5 microorganism methods of risk assessment, it is characterized in that: said salmonella is present in the round ham, and production procedure described in the step 1) comprises:
11) raw material receives: the round ham raw material is generally freezing pork; Go into the library storage certain hour after the buying; Storing temperature-18 ℃; The risk factors that this link need be considered comprise the bacterial bearing rate and the content of molds of raw meat, and the storage temperature of raw material and time, the growth of salmonella is suppressed in the storing process;
12) thaw: this link need be considered the environment that thaws of raw meat, and major risk factors is the temperature variation when thawing, and the temperature rising can cause Salmonella growth in this link, to be lower than 12 ℃ as a reference;
13) add auxiliary material: auxiliary material itself may be by salmonella-polluted; Therefore need to consider the bacterial bearing rate and the content of molds of auxiliary material; Add auxiliary material simultaneously and changed the inventory of goods in process; Have material mixed process, this link need use harm to shift and two process risk module of mixing of materials are described;
14) tumbling: this link is supplementary material to be put into the tumbling machine handle, and mainly considers the time of tumbling, and because the tumbling machine sterilization thoroughly possibly not introduced the pollution of salmonella, the workshop temperature is not higher than 12 ℃;
15) can: the risk factors that this link need be considered comprise that meat stuffing enters to the intact required time of can and the temperature of product, and maybe be because bottle placer introducing salmonella-polluted; The sausage that is filled into casing is at this link merogenesis, so this link need comprise that material splits module, and the workshop temperature is not higher than 12 ℃;
16) boiling and drying: this link operation can suppress microbial growth in the product, and the risk factors that need to consider comprise temperature and duration, and steaming temperature is 82～83 ℃, and the time is more than 30 minutes; The food deep temperature must reach 80 ℃, and salmonella could be dead; Come out of the stove when reducing to product temperature below 38 ℃ after the boiling, carry out putting into chilling room after the cooling of cold water spray, between airing, dry up surperficial steam;
17) packing: this link need consider that the workshop temperature remains on below 12 ℃ because wrappage are introduced the risk of harm;
18) vanning warehouse-in: this link need be considered duration and the warehouse temperature of product in the warehouse storage, and the finished product storing temperature is at 0～4 ℃.
7. according to the described meat products process of claim 1 microorganism methods of risk assessment, it is characterized in that: said microorganism is the monocyte hyperplasia listeria spp.
8. according to the described meat products process of claim 7 microorganism methods of risk assessment, it is characterized in that: said monocyte hyperplasia listeria spp is present in the low temperature sandwich ham, and production procedure described in the step 1) comprises:
11) raw meat thaws: about 0 ℃ of meat central temperature, surface temperature are below 8 ℃, and the operation room temperature is below 15 ℃, and the cube meat of choosing weighs 0.75～1.0kg;
12) pickle: amount on the rocks is no less than 1/3 of the salt water yield during butcher's meat, and phosphate will thoroughly dissolve with warm water, and the brine temp for preparing is lower than 5 ℃; Injection volume should be controlled at more than 35%, and pressure, speed will be stablized, when injector breaks down; Should stop charging at once; And between the meat of choosing pushed refrigerator or pickle, injection back temperature was not higher than 8 ℃, and salting period is no less than 16h;
13) batching: the secondary tumbling number of turns be no less than 1440 the circle, go out jar temperature at 5～8 ℃, go out jar after; With the meat grinder in 25mm aperture strand system, the filling temperature should be about 8 ℃ after the strand with material, from the secondary tumbling to filling; Should carry out as early as possible, undesired like equipment, should with the filling for preparing in time push pickle between in;
14) record: semi-manufacture are the storage period before sterilization, is no more than 20 minutes summer, is no more than 40 minutes winter, if overstock too much, in time with semi-manufacture push pickle between, and stop to record;
15) sterilization: the sterilization water changes weekly once winter, and change once 2 days summers, and to guarantee clean water quality, especially pressure should keep stable during back-pressure, and product fully cools off the retorts planted agent, and central temperature can take the dish out of the pot below 25 ℃;
16) refrigeration: the product that will take the dish out of the pot is rinsed well, dries, and is labelled, is stored in the refrigerator, and the refrigerator temperature should be at 0～4 ℃, and the principle by FIFO during outbound is carried out.
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103940991A (en) * | 2013-03-15 | 2014-07-23 | 河南省农业科学院 | Porcine salmonella heat-resistant toxin rapid detection test paper strip |
| CN105044307A (en) * | 2015-07-14 | 2015-11-11 | 中国科学院沈阳应用生态研究所 | Method for assessing two-dimension risk probability of soil heavy metal based on Bayes' theorem |
| CN105930936A (en) * | 2016-05-04 | 2016-09-07 | 山东省标准化研究院 | Growth prediction method of microorganisms included in food in production circulation process |
| CN106796678A (en) * | 2014-10-09 | 2017-05-31 | 利乐拉瓦尔集团及财务有限公司 | Quality monitoring in packaging line |
| CN107292472A (en) * | 2016-04-11 | 2017-10-24 | 江苏奥迈生物科技有限公司 | Mycotoxins in feed solution assessment system |
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| CN110956365A (en) * | 2019-11-11 | 2020-04-03 | 北京工商大学 | Colony total number dynamic risk assessment method of wheat flour supply chain based on hybrid Bayesian network |
| CN111739579A (en) * | 2020-05-26 | 2020-10-02 | 浙江省农业科学院 | Quantitative risk assessment method for salmonella in broiler chicken industrial chain |
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| US11074534B2 (en) | 2017-11-08 | 2021-07-27 | Tetra Laval Holdings & Finance S.A. | Method of determining a microbiological risk level in a food batch |
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Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102364512A (en) * | 2011-10-11 | 2012-02-29 | 中华人民共和国宁波出入境检验检疫局 | Method for realizing automatically sampling inspection of computer during product inspection and quarantine |
-
2012
- 2012-06-14 CN CN201210196911.7A patent/CN102768711B/en not_active Expired - Fee Related
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102364512A (en) * | 2011-10-11 | 2012-02-29 | 中华人民共和国宁波出入境检验检疫局 | Method for realizing automatically sampling inspection of computer during product inspection and quarantine |
Non-Patent Citations (6)
| Title |
|---|
| J. H. SMID ET AL: "A Practical Framework for the Construction of a Biotracing Model: Application to Salmonella in the Pork Slaughter Chain", 《RISK ANALYSIS》, vol. 31, no. 9, 31 December 2011 (2011-12-31), pages 1434 - 1450 * |
| J.H. SMID ET AL: "Strengths and weaknesses of Monte Carlo simulation models and Bayesian belief networks in microbial risk assessment", 《INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY》, vol. 2010, no. 139, 31 December 2010 (2010-12-31), pages 57 - 63 * |
| MAARTEN J. NAUTA ET AL: "Modelling bacterial growth in quantitative microbiological risk assessment: is it possible?", 《INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY》, vol. 73, no. 2, 31 December 2002 (2002-12-31), pages 297 - 304 * |
| 刘丽梅等: "食品安全追溯方法研究", 《标准科学》, vol. 2012, no. 2, 28 February 2012 (2012-02-28), pages 48 - 51 * |
| 杨彦峰等: "肉制品加工过程中的微生物控制", 《肉类工业》, vol. 2008, no. 10, 31 October 2008 (2008-10-31), pages 45 - 49 * |
| 祝美云等: "低温肉制品中微生物的控制", 《农产品加工.学刊》, vol. 2008, no. 11, 30 November 2008 (2008-11-30) * |
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