CN104483458A - Method for predicting shelf life of cold chain pork and system thereof - Google Patents
Method for predicting shelf life of cold chain pork and system thereof Download PDFInfo
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Abstract
The invention relates to a method for predicting shelf life of cold chain pork. The method comprises the following steps: S1, headspace volatile smell of cold chain storage pork is gathered by adoption of a smell sensor array system, and sensory evaluation is carried out synchronously; S2, feature extraction is carried out on obtained sensor data and storage time; and S3, clustering classification is carried out on different shelf life of pork by principal component analysis, and a prediction model of smell sensor response signal and shelf life is established. The invention provides a rapid and accurate solution for prediction of pork quality. The invention also discloses a system for predicting shelf life of cold chain pork.
Description
Technical field
The present invention relates to computing machine agricultural technology field, particularly relate to a kind of method and system predicting cold chain pork shelf life.
Background technology
Smell is the important indicator that pork freshness is evaluated, and in storage, the change of smell imply that quality changes.Smell sensors array system (also referred to as electric nasus system) is a kind of biology sensor of simulating the olfactory system of people, there is objective, sensitive measuring ability, compared with conventional analytical instruments, sample does not need pre-treatment just can gather volatile flavor fast, nondestructively substantially, feature extraction is carried out to obtained sensor array data, carries out modeling classification and pattern-recognition by various chemometrics method.Chinese scholars is inquired into the quartile length, greenness determination etc. that smell sensors array system is applied to milk, cereal, drinks, aquatic products etc.; Have scholar to adopt self-control electric nasus system can judge the sea bream of different freshness, Electronic Nose also can judge the freshness of beef, mutton well.But seldom report adopts the shelf life of electric nasus system prediction pork.Current existing shelf life forecasting model mainly predicts the shelf life of pork for physical and chemical index and microorganism detection, detect reagent poisonous and step complex operation, time and effort consuming, can not meet the object of harmless fast prediction quality.
Summary of the invention
Technical matters to be solved by this invention is for the shelf life of logistics and distribution process pork provides the key issue of the method and system of fast prediction.
For this purpose, the present invention proposes a kind of method predicting cold chain pork shelf life, comprise concrete following steps:
S1: by adopting the head space volatile flavor of smell sensors array system acquisition cold chain storage pork, synchronously carry out sensory evaluation mensuration;
S2: feature extraction is carried out to acquisition sensing data and storage time;
S3: adopt the different shelf lifes of principal component analytical method to pork to carry out cluster differentiation, set up the forecast model of smell sensor response signal and shelf life.
Further, described step S1 comprises further:
S11: pick a bone through pig slaughtering, cooling acid discharge, segmentation, the unified back leg lean meat getting hog on hook carries out aerobic pallet packing, transport analysis room in 0 ~ 4 DEG C of ice temperature;
S12: be stored in by sample in 0 DEG C, 5 DEG C, 10 DEG C, 15 DEG C High Precision Low Temperature incubators respectively, under duration of storage gets each temperature at set intervals at random, 3 box porks carry out sensory evaluation mensuration.
Further, described step S12 comprises further:
S12.1: before test, sense of taste primary dcreening operation and sense organ training are carried out to sensory evaluation personnel, the evaluation personnel screening 6 ~ 8 sense organs sensitive and accurate test;
S12.2: formulate ten point system sensory evaluation standard scale according to GB 9959.1-2001 and NY/T 632-2002, carries out peculiar smell to raw meat smell and judges to evaluate with acceptable.
Further, described step S2 comprises further:
S21: when sensor array system measures pork odor characteristics, obtain the response collection of illustrative plates of 10 sensor arraies, wherein, in described response collection of illustrative plates, each curve represents that a sensor is to the response of smell, and the point on curve represents that odour component is by the change with storage time of the relative resistance rate of described sensor passage;
S22: choose change curve and respond stable signal value and carry out multivariate statistical analysis as feature extraction value.
Further, described step S3 comprises further: by the sensor response curve corresponding to different sensory evaluation score value and odor characteristics and feature extraction, build the Clustering Model based on principal component analytical method.
Further, also comprise after described step S3: described forecast model is verified.
For this purpose, the invention allows for a kind of system predicting cold chain pork shelf life, comprising:
Gathering determinator, for the head space volatile flavor by adopting smell sensors array system acquisition cold chain storage pork, synchronously carrying out sensory evaluation mensuration;
Feature extraction and analytical equipment, for carrying out feature extraction to acquisition sensing data and storage time;
Modling model device, for adopting the different shelf lifes of principal component analytical method to pork to carry out cluster differentiation, sets up the forecast model of smell sensor response signal and shelf life.
Further, also comprise: demo plant, for verifying described forecast model.
The present invention discloses a kind of method predicting cold chain pork shelf life, integrated smell sensors array is adopted to gather the head space volatile flavor of chilled pork in storage, synchronously carry out sensory evaluation, feature extraction and multivariate statistical analysis are carried out to obtained sensing data and storage time, adopt master to be divided into analytical approach and cluster differentiation is carried out to different shelf life pork, set up the forecast model of smell sensor response signal and shelf life, for meat quality prediction provides solution quickly and accurately.The invention also discloses a kind of system predicting cold chain pork shelf life.
Accompanying drawing explanation
Can understanding the features and advantages of the present invention clearly by reference to accompanying drawing, accompanying drawing is schematic and should not be construed as and carry out any restriction to the present invention, in the accompanying drawings:
To show in the embodiment of the present invention a kind of predicts the variation diagram of pork sense organ smell score value under the different refrigerated storage temperatures in the method for cold chain pork shelf life for Fig. 1;
Fig. 2 shows a kind of flow chart of steps predicting the method for cold chain pork shelf life in the embodiment of the present invention;
Fig. 3 shows the response diagram of the smell sensor fresh and corrupt odor characteristics to pork in a kind of method predicting cold chain pork shelf life in the embodiment of the present invention;
To show in the embodiment of the present invention a kind of predicts and distinguish pork shelf life figure based on sensor array response signal in the method for cold chain pork shelf life for Fig. 4;
Fig. 5 to show in the embodiment of the present invention a kind of predict in the method for cold chain pork shelf life based on sensor response signal prediction pork shelf life figure;
Fig. 6 shows a kind of structural drawing predicting the system of cold chain pork shelf life in the embodiment of the present invention.
Embodiment
Below in conjunction with accompanying drawing, embodiments of the present invention is described in detail.
Smell is the principal character of pork corruption, usually for evaluating the freshness of meat.When the freshness continuous decrease of meat, the peculiar smell evaporated from the inside to the outside in meat is easy to be realized, finally can produce disgusting putrefactive odor.Fresh chilled pork has the intrinsic smell of pork and slightly pure and fresh tart flavour, without other peculiar smell, along with the prolongation of storage time, the peculiar smell that meat distributes after corruption is usually sour etc. with amine, volatile sulfur compound, volatile lower aliphatic to link together.
As shown in Fig. 1 (a)-(d), the freshness of the fresh chilled pork fetched from factory is fine, initial smell score value at 7.5 ~ 8.5 points, average 8.1 points.Fresh chilled pork presents tart flavour, and storage time extends, and pure and fresh tart flavour weakens, and the intrinsic smell of pork slightly presents, more close with fresh pork smell.Along with storage time further extends, the linearly downtrending of smell score value.Because in pallet blister-pack, pork and outside air exist free exchange process, distributing of smell is very fast.At storage mid-early stage (about 2-3 days), before pork not yet enters corruption, pork smell weakens to tasteless, also free from extraneous odour; Namely there is slight peculiar smell in the past, strengthen transformation ammonification taste, the garlic solvent taste boiled and pungent rotten-egg odour gradually in the tasteless stage.Can not accept (6.5 points) for boundary with half sensory evaluation personnel, the accepted phase of 0 DEG C, 5 DEG C, 10 DEG C, 15 DEG C smell is: 7 days, 5 days, 3 days, about 2.5 days.
In order to better understand a kind of method and system predicting cold chain pork shelf life proposed with application the present invention, be described in detail with following accompanying drawing example.
As shown in Figure 2, the invention provides a kind of method predicting cold chain pork shelf life, comprise concrete following steps:
Step S1: by adopting the head space volatile flavor of smell sensors array system acquisition cold chain storage pork, synchronously carry out sensory evaluation mensuration.
Particularly, pork smell acquisition method is: in cold storage procedure, gets each 3 pieces of pork under different reserve temperature at set intervals at random, is cut into meat cubelets.Accurately take meat cubelets 15 g, be laid in 150 mL beakers respectively, seal immediately with double-deck preservative film, room temperature starts after leaving standstill 10 min to measure, and each sample repeats 3 times.The workflow of sensor array system is: sample sealing balances after a period of time until smell, headspace gas is pumped in detection system through sampling channel, sensor is because having adsorbed a certain amount of volatile matter, conductivity changes, and this signal is obtained by data acquisition system (DAS) and is stored in computing machine.After sampling, the pure air after activated carbon filtration is pumped to Electronic Nose, cleans and make it return to original state to sensor, for measurement is next time prepared.When wherein Electronic Nose is measured, detection time is 60 s, and scavenging period is 60 s.60 s scavenging periods fully can ensure that each sensor of Electronic Nose recovers its original state.
Further, chilled pork is from the large-scale processing factory in regular Shandong, and cold chain pork storage practice comprises:
Step S11: pick a bone through pig slaughtering, cooling acid discharge, segmentation, the unified back leg lean meat getting hog on hook carries out aerobic pallet packing, transport analysis room in 0 ~ 4 DEG C of ice temperature.
Step S12: be stored in by sample in 0 DEG C, 5 DEG C, 10 DEG C, 15 DEG C High Precision Low Temperature incubators respectively, under duration of storage gets each temperature at set intervals at random, 3 box porks carry out sensory evaluation mensuration.
Further, sensory evaluation measures and comprises:
Step S12.1: carry out sense of taste primary dcreening operation and sense organ training to sensory evaluation personnel before test, the evaluation personnel screening 6 ~ 8 sense organs sensitive and accurate test.
Step S12.2: formulate ten point system sensory evaluation standard scale according to GB 9959.1-2001 and NY/T 632-2002, as shown in table 1:
Table 1 chilled pork sense organ Odor Evaluations standard
Namely carry out peculiar smell to raw meat smell judge and acceptable to evaluate, wherein, the higher freshness of score value is better, and 10 points best, and 0 is divided into very corrupt, and 6.5 are divided into sense organ acceptable limits.It is the shelf life terminal of meat when exceeding half evaluation personnel sense organ refusal.
Step S2: feature extraction is carried out to acquisition sensing data and storage time.
Particularly, when sensor array system measures pork odor characteristics, obtain the response collection of illustrative plates of 10 sensor arraies, in figure, each curve represents a sensor to the response of smell, when point on curve represents odour component by sensor passage, relative resistance rate (G/G0) is with the situation of change of storage time.Can find out from sensor array response curve, as shown in Fig. 3 (a)-(b), sensor array has obvious response to pork volatile flavor, and the response of each sensor is different.In response curve, from zero initial gas to the stationary process of final sample gas, relative resistance rate in the early stage (within 20 seconds) increases fast, and then tend to be steady (after 35 seconds).By the response curve of each sensor array under the different reserve temperature of Integrated comparative, after 35 seconds, each advantage sensor response tends towards stability and metastable state, and therefore the present invention adopts the signal of under steady state (SS) 40 ~ 45 seconds as the feature extraction of this model construction.
Further, under 0 ~ 15 DEG C of different reserve temperature, sensor response increases along with the increase of odorousness, and the kind of sensor mainly responded along with the change of odour component also changes.Compare by analysis, with 10 (headspace): the sensor response signal of 1 (sample size) ratio is the most stable, therefore carries out odor detection with this dilution proportioning.By analyzing the change of pork different storage time sensor response signal, show that smell sensor can respond to the pork sample of different freshness well.For the pallet packing pork of 5 DEG C of storages, each sensor response condition is as shown in Fig. 3 (a)-(b).
Step S3: adopt the different shelf lifes of principal component analytical method to pork to carry out cluster differentiation, set up the forecast model of smell sensor response signal and shelf life.
Particularly, by the sensor response curve corresponding to different sensory evaluation score value and odor characteristics and feature extraction, the Clustering Model based on principal component analytical method (Principal componentanalysis, PCA) is built.Further, data analysis is the core of electric nasus system, and pattern-recognition then determines the net result of data analysis, and it is proper whether mode identification method is applied, and decides the quality of Detection results.Suitable pattern-recognition, can forecast testing result fast accurately.This method adopts PCA to carry out pattern-recognition.Wherein, extracted multi-sensor information is carried out data conversion by PCA, and replaces original multi-C vector by less major component, thus eliminates the redundancy composition in sample data, reaches the object of Data Dimensionality Reduction.This method is chosen the first two major component PC1 and PC2 and is analyzed, PC1 and PC2 contains the contribution rate of first principal component and the Second principal component, obtained in PCA conversion.Contribution rate is larger, illustrates that principal ingredient more can reflect the information of original multi objective preferably.If the contribution rate of accumulative total of the first two major component is greater than 80%, then can analyze for the coefficient in the first two major component.
Further, the sensor array response of principal component analysis (PCA) to pork storage number of days is adopted to carry out feature extraction and pattern-recognition.Fig. 4 (a)-(d) is the component-bar chart of pork storage time at 0 ~ 15 DEG C of each temperature.Under PCA pattern, total contribution rate of PC1+PC2 is larger, illustrates that major component can reflect the information of original higher dimensional matrix data preferably.From Fig. 4 (a)-(d), pork shelf life under 0 DEG C, 5 DEG C, 10 DEG C, 15 DEG C each reserve temperatures obtains good differentiation, and the differentiation effect of shelf life length presents good linear or curve distribution, the distinguishing limit of fresh, secondary fresh and corrupt sample is obvious.As Fig. 4, at each temperature, the total contribution rate of PC1+PC2 is all greater than more than 90%, shows that this model has good reliability.
Further, also comprise after step S3: forecast model is verified.Particularly, by gathering the smell of the chilled pork of known shelf life, and carry out the quantitative model that deflected secondary air sets up different shelf life and sensor response, sentence checking, the average relative error of computational prediction result by the predicted value of shelf life and returning of measured value:
[(predicted value-measured value) × 100%/measured value], and then carry out the reliability of evaluation model.
Further, adopt the sensor array response of partial least square method to pork storage number of days to carry out feature extraction, build the quantitative model of pork shelf life and sensor array response.As shown in Fig. 5 (a)-(d), the prediction number of days of 0 DEG C, 5 DEG C, 10 DEG C, 15 DEG C preserves the Partial Least-Squares Regression Model of number of days as Fig. 5 and table 2 with actual, be and build pork shelf life verification model based on sensor response signal, the R of model
2value is all greater than 0.80 respectively, wherein the R of 10 DEG C, 15 DEG C forecast models
2value, more than 0.90, shows that data point degree of fitting is high.Analysed with returning to appraise by modelling verification, the predicted value of shelf life and the average relative error of measured value are all within 15%, and wherein the prediction average relative error of 10 DEG C and 15 DEG C is less than 5%, shows the shelf life adopting this model energy predict pork, and predictablity rate is higher, model is reliable.
Table 2 builds pork shelf life verification model based on sensor response signal
A kind of method predicting cold chain pork shelf life provided by the invention, compared with prior art, major advantage is: the present invention adopts sensor array system to predict the shelf life of pork, its gas collecting speed is fast, pattern-recognition and return that to sentence speed fast, precision of prediction is high, can provide a kind of effective solution for the rapid evaluation of logistics progress meat quality and quality management.
In order to better understand a kind of method predicting cold chain pork shelf life proposed with application the present invention, the present invention takes out a kind of system predicting cold chain pork shelf life from said method.
As shown in Figure 6, present invention also offers a kind of system 10 predicting cold chain pork shelf life, comprising: gather determinator 101, feature extraction and analytical equipment 102, Modling model device 103 and demo plant 104.
Particularly, gathering determinator 101 for the head space volatile flavor by adopting smell sensors array system acquisition cold chain storage pork, synchronously carrying out sensory evaluation mensuration; Feature extraction and analytical equipment 102 are for obtaining sensing data and storage time carries out feature extraction; Modling model device 103 carries out cluster differentiation for adopting the different shelf lifes of principal component analytical method to pork, sets up the forecast model of smell sensor response signal and shelf life; Demo plant 104 is for verifying forecast model.
A kind of method predicting cold chain pork shelf life disclosed by the invention, integrated smell sensors array is adopted to gather the head space volatile flavor of chilled pork in storage, synchronously carry out sensory evaluation, feature extraction is carried out to obtained sensing data and storage time, adopt master to be divided into analytical approach and cluster differentiation is carried out to different shelf life pork, set up the forecast model of smell sensor response signal and shelf life, for meat quality prediction provides solution quickly and accurately.The invention also discloses a kind of system predicting cold chain pork shelf life.
Although describe embodiments of the present invention by reference to the accompanying drawings, but those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, such amendment and modification all fall into by within claims limited range.
Claims (8)
1. predict a method for cold chain pork shelf life, it is characterized in that, comprise concrete following steps:
S1: by adopting the head space volatile flavor of smell sensors array system acquisition cold chain storage pork, synchronously carry out sensory evaluation mensuration;
S2: feature extraction is carried out to acquisition sensing data and storage time;
S3: adopt the different shelf lifes of principal component analytical method to pork to carry out cluster differentiation, set up the forecast model of smell sensor response signal and shelf life.
2. the method for claim 1, is characterized in that, described step S1 comprises further:
S11: pick a bone through pig slaughtering, cooling acid discharge, segmentation, the unified back leg lean meat getting hog on hook carries out aerobic pallet packing, transport analysis room in 0 ~ 4 DEG C of ice temperature;
S12: be stored in by sample in 0 DEG C, 5 DEG C, 10 DEG C, 15 DEG C High Precision Low Temperature incubators respectively, under duration of storage gets each temperature at set intervals at random, 3 box porks carry out sensory evaluation mensuration.
3. the method for claim 1, is characterized in that, described step S12 comprises further:
S12.1: before test, sense of taste primary dcreening operation and sense organ training are carried out to sensory evaluation personnel, the evaluation personnel screening 6 ~ 8 sense organs sensitive and accurate test;
S12.2: formulate ten point system sensory evaluation standard scale according to GB 9959.1-2001 and NY/T 632-2002, carries out peculiar smell to raw meat smell and judges to evaluate with acceptable.
4. the method for claim 1, is characterized in that, described step S2 comprises further:
S21: when sensor array system measures pork odor characteristics, obtain the response collection of illustrative plates of 10 sensor arraies, wherein, in described response collection of illustrative plates, each curve represents that a sensor is to the response of smell, and the point on curve represents that odour component is by the change with storage time of the relative resistance rate of described sensor passage;
S22: choose change curve and respond stable signal value and carry out multivariate statistical analysis as feature extraction value.
5. the method for claim 1, is characterized in that, described step S3 comprises further: by the sensor response curve corresponding to different sensory evaluation score value and odor characteristics and feature extraction, build the Clustering Model based on principal component analytical method.
6. the method for claim 1, is characterized in that, also comprises after described step S3: verify described forecast model.
7. predict a system for cold chain pork shelf life, it is characterized in that, comprising:
Gathering determinator, for the head space volatile flavor by adopting smell sensors array system acquisition cold chain storage pork, synchronously carrying out sensory evaluation mensuration;
Feature extraction and analytical equipment, for carrying out feature extraction to acquisition sensing data and storage time;
Modling model device, for adopting the different shelf lifes of principal component analytical method to pork to carry out cluster differentiation, sets up the forecast model of smell sensor response signal and shelf life.
8. system as claimed in claim 7, is characterized in that, also comprise: demo plant, for verifying described forecast model.
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| CN108593861A (en) * | 2018-04-08 | 2018-09-28 | 湖北省农业科学院农产品加工与核农技术研究所 | A method of prediction fresh-water fishes shelf life |
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| CN112036619A (en) * | 2020-08-17 | 2020-12-04 | 中国标准化研究院 | Method for judging whether roasted duck exceeds shelf end point by combining electronic nose with Bayesian algorithm |
| CN112036618A (en) * | 2020-08-17 | 2020-12-04 | 中国标准化研究院 | Method for predicting shelf time of roast duck by combining electronic nose with partial least square regression |
| CN112036618B (en) * | 2020-08-17 | 2023-06-23 | 中国标准化研究院 | Method for predicting roast duck shelf time by combining electronic nose with partial least square regression |
| CN114137167A (en) * | 2021-11-26 | 2022-03-04 | 惠州市食品药品检验所(惠州市药品不良反应监测中心) | Method and system for predicting shelf life of wet rice noodles |
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