CN110210680A - A kind of fish body Noninvasive Measuring Method of Freshness and device based on temperature change - Google Patents
A kind of fish body Noninvasive Measuring Method of Freshness and device based on temperature change Download PDFInfo
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Abstract
The embodiment of the present invention provides a kind of fish body Noninvasive Measuring Method of Freshness and device based on temperature change, this method comprises: obtaining storage temperature, storage time and the escaping gas of fish body, extracts the gas Principal component of the escaping gas；The storage temperature, storage time and gas Principal component are input to the freshness prediction model that training obtains in advance, obtain the grade of freshness of fish body.By measuring the corrupt index of known related clear limit standard and to the sensory evaluation of fish, determine its corrupt trend and shelf life: again by its variation for corresponding to escaping gas ingredient or content in decay process of electronic nose Instrument measuring, then principal component is extracted with Principal Component Analysis, finally each storage temperature, storage time and corresponding escaping gas Principal component and corrupt index content are applied in radial basis function neural network and establish freshness prediction model, achievees the purpose that Fast nondestructive evaluation fish body freshness.
Description
Technical field
The present embodiments relate to food safety monitoring technical field more particularly to a kind of fish body based on temperature change are new
Freshness detection method and device.
Background technique
Microorganism growth, the generation of amine substance and volatilization are the important factor in order of fish quality comparison, and wherein bacterium colony is total
The variation of the indexs such as several and Volatile Base Nitrogen is usually related to the variation of the freshness of fish, and then affects smell and mouthfeel.It is right
These parameters carry out conveniently real-time detection, can reach the purpose for quickly determining fish freshness.
In the transport of fish, sales process, prevent corruption fish enter selling market damage consumer health at
For the important topic of food safety.Currently, consumer buys aquatic products can only differentiate the fresh journey of fish by experience and sense organ
Degree, while businessman guarantees the fresh coherent detection that can aquatic products be carried out with freshness of fish when stocking up, but due to people
There is time-consuming, inefficiency in work detection, and will cause the damage of fish body when artificial detection, cause the freshness of fish by
To influence, to not be able to satisfy consumer demand, unsalable waste is caused.
Summary of the invention
The embodiment of the present invention provides a kind of fish body Noninvasive Measuring Method of Freshness and device based on temperature change, by combining diameter
Fish escaping gas is acquired to basic function computation model and calculates corrupt index content in real time and then determines grade of freshness, is reached
To the purpose of Fast nondestructive evaluation salmon freshness.
In a first aspect, the embodiment of the present invention provides a kind of fish body Noninvasive Measuring Method of Freshness based on temperature change, comprising:
Obtain fish body storage temperature, storage time and escaping gas, extract the escaping gas gas it is main at
Score value；The storage temperature, storage time and gas Principal component are input to the freshness prediction model that training obtains in advance,
It obtains the corrupt index content of fish body and determines grade of freshness.
Further, before the storage temperature, storage time and escaping gas that obtain fish body, further includes:
Obtain storage temperature, storage time and the escaping gas and storage temperature, storage time and volatility of fish body
The corresponding TVB-N content of gas, total plate count and sensory evaluation scores；
Extract the gas Principal component in the escaping gas, with the storage temperature, storage time and gas it is main at
Score value is input, is output with corresponding TVB-N content, total plate count and sensory evaluation scores；Carry out neural network instruction
Practice, obtains freshness prediction model.
Further, the gas Principal component in the escaping gas is extracted, is specifically included:
The principal component in the escaping gas is extracted based on principal component analytical method, the principal component includes the volatilization
The highest first gas principal component of content, second gas principal component and third gas principal component in property gas；
It is adopted based on the first gas principal component, the second gas principal component and the third gas principal component with corresponding
The relationship for collecting sensor, by the first gas principal component, the second gas principal component and the third gas principal component point
First principal component value, Second principal component, value and third Principal component are not converted to.
Further, neural metwork training is carried out, is specifically included:
Radial basis function neural network is chosen, using storage temperature, storage time and gas Principal component as the defeated of input layer
Enter, using TVB-N content, total plate count and sensory evaluation scores as the output of output layer, it is 40 that maximum neuron number, which is arranged,
Test addition neuron number is 1 every time, and relative error is located within ± 10%, obtains freshness prediction model with training.
Second aspect, the embodiment of the present invention provide a kind of fish body freshness detection device based on temperature change, comprising:
Acquisition module extracts the volatility gas for obtaining the storage temperature, storage time and escaping gas of fish body
The gas Principal component of body；
Prediction module is obtained for the storage temperature, storage time and gas Principal component to be input to training in advance
Freshness prediction model, obtain the grade of freshness of fish body.
Further, the acquisition module includes temperature sensor and multiple electronic nose sensors；The temperature sensor
For acquiring storage temperature, the electronic nose sensor is used to obtain the response of the escaping gas of fish body.
Further, the prediction module is also used to:
Obtain storage temperature, storage time and the escaping gas and storage temperature, storage time and volatility of fish body
The corresponding TVB-N content of gas, total plate count and sensory evaluation scores；
Extract the gas Principal component in the escaping gas, with the storage temperature, storage time and gas it is main at
Score value is input, is output with corresponding TVB-N content, total plate count and sensory evaluation scores；Carry out neural network instruction
Practice, obtains freshness prediction model.
Further, the acquisition module is also used to:
The principal component in the escaping gas is extracted based on principal component analytical method, the principal component includes the volatilization
The highest first gas principal component of content, second gas principal component and third gas principal component in property gas；
It is adopted based on the first gas principal component, the second gas principal component and the third gas principal component with corresponding
The relationship for collecting sensor, by the first gas principal component, the second gas principal component and the third gas principal component point
First principal component value, Second principal component, value and third Principal component are not converted to.
The third aspect, the embodiment of the present invention provides a kind of electronic equipment, including memory, processor and is stored in memory
Computer program that is upper and can running on a processor, the processor realize such as first aspect present invention when executing described program
The step of fish body Noninvasive Measuring Method of Freshness described in embodiment based on temperature change.
Fourth aspect, the embodiment of the present invention provide a kind of non-transient computer readable storage medium, are stored thereon with calculating
Machine program, realization is as described in first aspect present invention embodiment when which is executed by processor based on temperature change
The step of fish body Noninvasive Measuring Method of Freshness.
A kind of fish body Noninvasive Measuring Method of Freshness and device based on temperature change provided in an embodiment of the present invention, passes through measurement
The corrupt index of the known clear limit standard of correlation and sensory evaluation to fish determine its corrupt trend and shelf life: leading to again
Its variation for corresponding to escaping gas ingredient or content in decay process of electronic nose Instrument measuring is crossed, principal component analysis is then used
Method extracts principal component, finally by each storage temperature, storage time and corresponding escaping gas Principal component and corrupt index
Content, which is applied in radial basis function neural network, establishes freshness prediction model, acquires fish in conjunction with radial basis function computation model
Escaping gas calculates corrupt index content in real time and determines grade of freshness, reaches Fast nondestructive evaluation fish body freshness
Purpose.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is this hair
Bright some embodiments for those of ordinary skill in the art without creative efforts, can be with root
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is the fish body Noninvasive Measuring Method of Freshness schematic diagram based on temperature change according to the embodiment of the present invention；
Fig. 2 is according to Volatile Base Nitrogen trend chart under the different temperatures of the embodiment of the present invention；
Fig. 3 is according to total plate count trend chart under the different temperatures of the embodiment of the present invention；
Fig. 4 is according to sensory evaluation scores variation tendency tendency chart under the different temperatures of the embodiment of the present invention；
Fig. 5 is the variation schematic diagram according to electronic nose sensor response under 10 DEG C of reserve temperatures of the embodiment of the present invention；
Fig. 6 is the variation schematic diagram according to electronic nose sensor response under 4 DEG C of reserve temperatures of the embodiment of the present invention；
Fig. 7 is the variation schematic diagram according to electronic nose sensor response under 0 DEG C of reserve temperature of the embodiment of the present invention；
Fig. 8 is the variation schematic diagram according to electronic nose sensor response under -2 DEG C of reserve temperatures of the embodiment of the present invention；
Fig. 9 is the radial basis function neural network calculation step schematic diagram according to the embodiment of the present invention；
The predicted value and experiment value comparison diagram that Figure 10 is the TVB-N according to the embodiment of the present invention；
The predicted value and experiment value comparison diagram that Figure 11 is the TAC according to the embodiment of the present invention；
Figure 12 is the predicted value and experiment value comparison diagram of the sensory evaluation scores according to the embodiment of the present invention；
Figure 13 is the entity structure schematic diagram according to the electronic equipment of the embodiment of the present invention.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
Every other embodiment obtained without creative efforts, shall fall within the protection scope of the present invention.
The side such as chemical composition change, change in physical properties, microorganism detection is concentrated mainly on to fish products Quality Research at present
Face.This method is cumbersome, is not suitable for the subjective judgement of consumer, because consumer relies primarily on the taste of fillet to make a decision.
With the continuous improvement of the Cold Chain Logistics level of IT application, environmental monitoring and process control skill more and more mature in logistics transportation
Art, in the market for the scheme acquired in real time and equipment of the environmental informations such as temperature, the humidity in compartment of freighting in transportational process
It has been suggested and has developed.
There is some defects and deficiencies for existing technology and methods, and the inspection of quick nondestructive cannot be carried out to the freshness of fish
It surveys, it is time-consuming to the detection method of fish freshness at present or fish and its product are caused due to lacking corresponding device and method
Damage is invaded, last terminal sale is unfavorable for.Therefore, temperature, the odor data information how effectively obtained using environmental monitoring,
The quality of fish during Cold Chain Logistics is detected, is the process urgent problem.
For example, fish products atlantic salmon, also known as salmon, are a kind of important raw fish raw materials.Salmon mouth
Feel delicious exquisiteness, protein content is high, and heat is low, is rich in unsaturated fatty acid, more and more popular with consumers.China three
Literary fish is mainly from Europes such as Norway, Britain.After slaughter, excision internal organ, air transportion to domestic major port, cold chain transportation is extremely
Various regions.In the final stage of cold chain, salmon is peeled, sale of cutting into slices, until consumer buys at home.In this process
In, salmon piece has left fish body, and its high protein, high-fat characteristic make the quality of salmon piece be easy to decline, lead
The smell and mouthfeel for causing salmon piece change.
Chemical composition change, change in physical properties, microorganism detection are concentrated mainly on to salmon product Quality Research at present
Etc..This method is cumbersome, is not suitable for the subjective judgement of consumer, because consumer relies primarily on the taste of fillet to do certainly
It is fixed.Therefore, it is necessary to study a kind of quick, lossless, easy detection method.Smell sensor is applied to Safety of Food Quality point
The main artificial intelligence sensing system of analysis.Smell sensor is made of the sensor of one group of imitation human smell.Smell
Sensor is usually used to the variation of the quality and freshness of measurement fish, and this variation is based on selectively detection volatility
Object, including amine, sulphur compound and ethyl alcohol etc. are closed, these volatile compounds can generate corrupt smell.Researcher passes through gas
The correlative study for 4 DEG C of variations that taste sensor is stored in for fresh fish, discovery smell sensor can facilitate and nondestructive evaluation
The fresh variation of fish.Research fillet are stored in 0 DEG C, 4 DEG C, 7 DEG C and 10 DEG C of variation, by combining electronic nose and electronic tongues and diameter
To basis function neural network, it will volatilize gas for the first time and organic or inorganic compound combined and modeled, reach Fast nondestructive evaluation
The purpose of fish freshness.Expansion explanation and introduction will be carried out by multiple embodiments below.
Fig. 1 is a kind of fish body Noninvasive Measuring Method of Freshness based on temperature change according to the embodiment of the present invention, comprising:
S1, storage temperature, storage time and the escaping gas for obtaining fish body, extract the gas master of the escaping gas
Signal component value；
S2, that the storage temperature, storage time and gas Principal component are input to the obtained freshness of training in advance is pre-
Model is surveyed, the hair corruption index of fish body is obtained and determines grade of freshness.
In the present embodiment, by measuring the corrupt index of known related clear limit standard and commenting the sense organ of fish
Valence, determine its corrupt trend and shelf life: by electronic nose Instrument measuring, it corresponds to escaping gas ingredient in decay process again
Or the variation of content, principal component then is extracted with Principal Component Analysis, finally by each storage temperature, storage time and correspondence
Escaping gas Principal component and corrupt index content be applied in radial basis function neural network and establish freshness prediction mould
Type calculates corrupt index content in conjunction with radial basis function computation model acquisition salmon escaping gas in real time and determines fresh
Grade is spent, achievees the purpose that Fast nondestructive evaluation fish body freshness.
On the basis of the above embodiments, it before the storage temperature, storage time and escaping gas that obtain fish body, also wraps
It includes:
Obtain storage temperature, storage time and the escaping gas and storage temperature, storage time and volatility of fish body
The corresponding TVB-N content of gas, total plate count and sensory evaluation scores；
Extract the gas Principal component in the escaping gas, with the storage temperature, storage time and gas it is main at
Score value is input, is output with corresponding TVB-N content, total plate count and sensory evaluation scores；Carry out neural network instruction
Practice, obtains freshness prediction model.
In the present embodiment, it transports and trades by the foundation of fish freshness prediction model, Cold Chain Logistics under temperature fluctuation
Portable scent sensor device is refreshing to the acquisition of escaping gas, portable scent sensor combination radial basis function in the process
Through network computing model to the Real-time Feedback of corrupt index index and grade of freshness.
Specifically, the following steps are included:
(1) fresh fish products are purchased；
(2) reserve temperature: the fish of purchase is cut into after fillet sample be stored in -2 DEG C, 0 DEG C, 4 DEG C, in 10 DEG C of refrigerators, often
The measurement of Volatile Base Nitrogen, total plate count, sensory evaluation scores is carried out every a period of time acquisition fillet sample；
(3) Volatile Base Nitrogen, total plate count detection.Sensory evaluation: full marks 40 score and show fish very for 40 or >=35
Fresh, scoring≤25 consumers refusal is edible, and≤20 salmon of scoring are putrid and deteriorated, cannot eat；
As shown in Fig. 2 to Fig. 4, respectively salmon piece storage at different temperatures Volatile Base Nitrogen, total plate count,
Sensory evaluation scores variation tendency；Find out from Fig. 2 and Fig. 3, with the increase of storage time, Volatile Base Nitrogen, total plate count are all
Different degrees of growth trend is showed, according to salmon food sanitation standard in national standard GB2733-2015, Volatile Base Nitrogen≤
30mg/100g, total plate count≤6logcfu/g.As storage time increases, Volatile Base Nitrogen and total plate count exceed state
Limit standard as defined in family.It can be seen that in Fig. 4, as storage time increases, salmon quality decline, sensory evaluation scores drop therewith
It is low, until corruption is inedible.
(4) it gas collecting: is acquired with escaping gas of the smell sensor to the flesh of fish, with Principal Component Analysis to gas
Taste sensor the data obtained carries out Principle component extraction and obtains principal component and calculation formula；
In the present embodiment, smell sensor uses electronic nose sensor, and Fig. 5 to Fig. 8 respectively illustrates electronic nose sensing
Device at different temperatures changes the response of salmon fillet sample.The response of electronic nose sensor determines salmon fillet
The volatile gaseous compound of primary categories in headspace.P10/1, T40/1, TA/2 sensor are to salmon fillet volatility
The response of gas componant is higher than other sensors.Sensor P10/1, T40/1 and TA/2 respectively correspond hydrocarbon/first
Alkane, fluoride and ethyl alcohol.
(5) the gas Principal component in the escaping gas is extracted, with the storage temperature, storage time and gas master
Signal component value is input, is output with corresponding TVB-N content, total plate count and sensory evaluation scores；Carry out neural network instruction
Practice, obtains freshness prediction model；
(6) the reliability of the adjustment model is verified: it is pre- that related data at -2 DEG C, 4 DEG C and 10 DEG C as training sample establishes freshness
Model is surveyed, the predicted value of 0 DEG C of corrupt index is acquired according to freshness prediction model and actual measured value compares, passes through average phase
To the reliability of error assessment freshness prediction model.
(7) in practical logistics and process of exchange the application of freshness prediction model with amendment: during actually detected
Whether escaping gas concentration and temperature are debugged can survey in range, and are carried out repeated detection and reduced error.
On the basis of the various embodiments described above, the gas Principal component in the escaping gas is extracted, is specifically included:
The principal component in the escaping gas is extracted based on principal component analytical method, the principal component includes the volatilization
The highest first gas principal component of content, second gas principal component and third gas principal component in property gas；
It is adopted based on the first gas principal component, the second gas principal component and the third gas principal component with corresponding
The relationship for collecting sensor, by the first gas principal component, the second gas principal component and the third gas principal component point
First principal component value, Second principal component, value and third Principal component are not converted to.
In the present embodiment, as shown in Fig. 5 to Fig. 8, respectively different reserve temperatures (10 DEG C, 4 DEG C, 0 DEG C and -2 DEG C)
The variation schematic diagram of lower electronic nose sensor response, the response of electronic nose sensor determine in salmon fillet headspace
The volatile gaseous compound of primary categories.P10/1, T40/1, TA/2 sensor are to salmon fillet escaping gas ingredient
Response is higher than other sensors.Sensor P10/1, T40/1 and TA/2 respectively correspond hydrocarbon/methane, fluoride and
Ethyl alcohol.Principle component extraction is carried out to electronic nose data using SPASS software, obtains first principal component value PC1, Second principal component, value
PC2 and third Principal component PC3, i.e. principal component processing costs, each principal component relational expression corresponding with each sensor of electronic nose
Are as follows:
PC1=1.943x1-2.5876x2-2.4295x3-2.7425x4-2.6402x5-0.0496x6+2.6371x7+
1.5711x8+1.3232x9+2.6185x10+2.7146x11+2.823x12+2.7797x13+2.6557x14+2.5969x15+
2.0112x16+1.5556x17 (1)
PC2=0.9154x1+0.8033x2+0.8831x3+0.07065x4+0.5963x5+0.4159x6-0.7027x7+
1.5269x8+1.4244x9+0.395x10-0.6704x11-0.5203x12-0.3931x13+0.773x14+0.1083x15+
1.3598x16+1.1737x17 (2)
PC3=0.4543x1+0.3315x2+0.3206x3+0.2293x4+0.3032x5-0.1445x6+0.3043x7-
0.2195x8-0.4673x9+0.3717x10+0.1761x11-0.1532x12+0.1641x13-0.0826x14+0.4434x15+
0.0815x16-0.1478x17 (3)
X1-x17 respectively corresponds the influence value of electronic nose sensor: LY2/LG, LY2/G, LY2/AA, LY2/GH, LY2/
GCTl, LY2/gCT, T30/1, P10/1, P10/2, T70/2, PA/2, P30/1, P40/2, P30/2, T40/2, T40/1, TA/2.
In the present embodiment, if evaluating other fish, then wherein the corresponding coefficient of x1-x17 according to actual measurement data,
It is previously obtained after statistical analysis.
On the basis of the various embodiments described above, neural metwork training is carried out, is specifically included:
Radial basis function neural network is chosen, using storage temperature, storage time and gas Principal component as the defeated of input layer
Enter, using TVB-N content, total plate count and sensory evaluation scores as the output of output layer, it is 40 that maximum neuron number, which is arranged,
Test addition neuron number is 1 every time, and relative error is located within ± 10%, obtains freshness prediction model with training.
In the present embodiment, as shown in Figure 9, by salmon reserve temperature (- 2 DEG C: 271K, 4 DEG C: 277K, 10 DEG C:
283K), storage time and principal component processing costs are as input layer, and principal component 1, principal component 2, principal component 3 are corresponding above-mentioned each in figure
First principal component value PC1, Second principal component, value PC2 and third Principal component PC3 in embodiment, the corresponding corruption of three temperature
Index and sensory evaluation scores are as output layer, and it is 40 that maximum neuron number, which is arranged, and the added neuron number of test is 1 every time, relatively
Error is 0, establishes prediction model as training sample.
Sample is verified using 0 DEG C of related data as test.It obtains salmon piece shown by Figure 10 to Figure 12 and is stored in 0 DEG C
Relative error between the freshness index predicted value and experiment value of (273K).The relative error of total plate count ± 5% with
Interior, the relative error of Volatile Base Nitrogen is within ± 10%, and the relative error of sensory evaluation scores value is ± 15%.Therefore, fresh
Spend the accuracy of prediction model within an acceptable range.
Radial basis function neural network model calculating process is as follows:
T=[temperature, time]；T is selection training sample；
Alldata=[temperature；Time；Electronic nose principal component PC1；Electronic nose principal component PC2；Electronic nose principal component PC3]；
Alldata is data used in this training pattern input layer；
Outdata=[Volatile Base Nitrogen；Total plate count；Sensory evaluation scores]；Outdata is this training pattern output layer
Data used；
[p, ps]=mapminmax (alldata)；P is input vector, and mapminmax is normalization；
[t, ts]=mapminmax (outdata)；T is output vector；
Net=newrb (p, t, 0,6.5,40,1)；Net=newrb is the caller of radial basis function neural network, 0
It is radial basis function diffusion velocity for relative error target, 6.5, density 0.5,40 is maximum neuron number, and 1 is to show twice
Between added neuron number.
Test=[temperature；Time；Electronic nose principal component PC1；Electronic nose principal component PC2；Electronic nose principal component PC3].
Test is data used in this test prediction model；
Test=mapminmax (' apply', test, ps)；Ps is test sample；
Anewn=sim (net, test)；Sim is the network output that radial basis function is obtained for given input；
Anewn is the name of this output result；
Anewnn=mapminmax (' reverse', anewn, ts)；Renormalization is carried out to anewn data and obtains reality
Predicted value；Anewnn is the name of this output result；
save；Save data result.
Aforesaid operations process is the operation of the system radial basis function neural network model (freshness prediction model)
Journey.
By comparing the predicted value and experiment value of TVB-N, TAC and sensory evaluation scores, R2Respectively 0.9976,0.9977 and
0.9978, and the relative error between TVB-N and TAC experiment value and predicted value is calculated within 10%, sensory evaluation scores are opposite
Error shows higher accuracy within 15%.
On the basis of the above embodiments, from multi-temperature fluctuation, based on logistics practical application aspect, support is constructed
The fish freshness fast non-destructive detection method of logistics and process of exchange temperature change, expansible fish detection method facilitate Quality Inspector
Deng carrying out quality tracking and management to cold fresh fish, the Quality Control Technology of fish is improved.
As Quality Inspector's real-time detection salmon changes since dispatching to the freshness for selling website:
(1) salmon is first acquired 2g sample, is calculated and worked as using freshness prediction model before entering cold-storage delivery vehicle
Preceding Volatile Base Nitrogen value, total plate count and sensory evaluation scores；
(2) salmon is placed into refrigerator carriage, uses three under the temperature fluctuation of customization in Cold Chain Logistics, transactional stage
Literary flesh of fish smell sensor detection device carries out the sampling observation of not timing unfixed point；
(3) after system equipment is opened, choose sample, escaping gas is acquired, data processing, freshness it is anti-
Feedback；
(4) by freshness prediction model can real-time detection salmon freshness grade.
For another example consumer's real-time detection salmon retail level freshness changes:
(1) after salmon sells the place such as supermarket market, each retail site is equipped with three under the temperature fluctuation of customization
Literary fish smell sensor detection device is used for businessman and consumer；
(2) seller cuts a small amount of sample of batch salmon and is put into small sample dish, detects or tastes for consumer；
(3) consumer is detected using the salmon smell sensor detection device of outfit；
(4) salmon grade of freshness is detected by freshness prediction model and decides whether to buy by consumer.
The present embodiment can accurately simulate the salmon freshness in cold chain transportation and process of exchange；Effectively promoted to cold chain
The quality monitoring ability of transport and the salmon in process of exchange guarantees salmon quality, and is the quick real-time detection of Quality Inspector
It is convenient to provide；Shelf retail level salmon freshness can be accurately predicted, quality foundation is provided for consumer, effectively subtracts
It is few that damage is invaded to salmon commodity, reach non-destructive testing.
A kind of fish body freshness detection device based on temperature change is additionally provided in the present embodiment, is based on above-mentioned each implementation
The fish body Noninvasive Measuring Method of Freshness based on temperature change in example, comprising:
Acquisition module extracts the volatility gas for obtaining the storage temperature, storage time and escaping gas of fish body
The gas Principal component of body；
Prediction module is obtained for the storage temperature, storage time and gas Principal component to be input to training in advance
Freshness prediction model, obtain the grade of freshness of fish body.
In the present embodiment, by measuring the corrupt index of known related clear limit standard and commenting the sense organ of fish
Valence, determine its corrupt trend and shelf life: by electronic nose Instrument measuring, it corresponds to escaping gas ingredient in decay process again
Or the variation of content, principal component then is extracted with Principal Component Analysis, finally by each storage temperature, storage time and correspondence
Escaping gas Principal component and corrupt index content be applied in radial basis function neural network and establish freshness prediction mould
Type calculates corrupt index content in conjunction with radial basis function computation model acquisition salmon escaping gas in real time and determines fresh
Grade is spent, achievees the purpose that Fast nondestructive evaluation fish body freshness.
On the basis of the various embodiments described above, the acquisition module includes temperature sensor and multiple electronic nose sensors；
The temperature sensor is used to obtain the response of the escaping gas of fish body for acquiring storage temperature, the electronic nose sensor
Value.
In the present embodiment, electronic nose sensor includes: LY2/LG, LY2/G, LY2/AA, LY2/GH, LY2/gCTl,
LY2/gCT, T30/1, P10/1, P10/2, T70/2, PA/2, P30/1, P40/2, P30/2, T40/2, T40/1, TA/2.
On the basis of the various embodiments described above, the prediction module is also used to:
Obtain storage temperature, storage time and the escaping gas and storage temperature, storage time and volatility of fish body
The corresponding TVB-N content of gas, total plate count and sensory evaluation scores；
Extract the gas Principal component in the escaping gas, with the storage temperature, storage time and gas it is main at
Score value is input, is output with corresponding TVB-N content, total plate count and sensory evaluation scores；Carry out neural network instruction
Practice, obtains freshness prediction model.
On the basis of the various embodiments described above, the acquisition module is also used to:
The principal component in the escaping gas is extracted based on principal component analytical method, the principal component includes the volatilization
The highest first gas principal component of content, second gas principal component and third gas principal component in property gas；
It is adopted based on the first gas principal component, the second gas principal component and the third gas principal component with corresponding
The relationship for collecting sensor, by the first gas principal component, the second gas principal component and the third gas principal component point
First principal component value, Second principal component, value and third Principal component are not converted to.
The response of electronic nose sensor determines the escaping gas chemical combination of primary categories in salmon fillet headspace
Object.P10/1, T40/1, TA/2 sensor are higher than other sensors to the response of salmon fillet escaping gas ingredient.It passes
Sensor P10/1, T40/1 and TA/2 respectively correspond hydrocarbon/methane, fluoride and ethyl alcohol.Using SPASS software to electronics
Nose data carry out Principle component extraction, obtain first principal component value PC1, Second principal component, value PC2 and third Principal component PC3, i.e.,
Principal component processing costs, each principal component relational expression corresponding with each sensor of electronic nose are as follows:
PC1=1.943x1-2.5876x2-2.4295x3-2.7425x4-2.6402x5-0.0496x6+2.6371x7+
1.5711x8+1.3232x9+2.6185x10+2.7146x11+2.823x12+2.7797x13+2.6557x14+2.5969x15+
2.0112x16+1.5556x17 (1)
PC2=0.9154x1+0.8033x2+0.8831x3+0.07065x4+0.5963x5+0.4159x6-0.7027x7+
1.5269x8+1.4244x9+0.395x10-0.6704x11-0.5203x12-0.3931x13+0.773x14+0.1083x15+
1.3598x16+1.1737x17 (2)
PC3=0.4543x1+0.3315x2+0.3206x3+0.2293x4+0.3032x5-0.1445x6+0.3043x7-
0.2195x8-0.4673x9+0.3717x10+0.1761x11-0.1532x12+0.1641x13-0.0826x14+0.4434x15+
0.0815x16-0.1478x17 (3)
X1-x17 respectively corresponds the influence value of electronic nose sensor: LY2/LG, LY2/G, LY2/AA, LY2/GH, LY2/
GCTl, LY2/gCT, T30/1, P10/1, P10/2, T70/2, PA/2, P30/1, P40/2, P30/2, T40/2, T40/1, TA/2.
In the present embodiment, if evaluating other fish, then wherein the corresponding coefficient of x1-x17 according to actual measurement data,
It is previously obtained after statistical analysis.
Figure 13 is the entity structure schematic diagram of electronic equipment provided in an embodiment of the present invention, and as shown in figure 13, which sets
Standby may include: processor (processor) 810,820, memory communication interface (Communications Interface)
(memory) 830 and communication bus 840, wherein processor 810, communication interface 820, memory 830 pass through communication bus 840
Complete mutual communication.Processor 810 can call the meter that is stored on memory 830 and can run on processor 810
Calculation machine program, to execute the fish body Noninvasive Measuring Method of Freshness based on temperature change of the various embodiments described above offer, for example,
S1, storage temperature, storage time and the escaping gas for obtaining fish body, extract the gas master of the escaping gas
Signal component value；
S2, that the storage temperature, storage time and gas Principal component are input to the obtained freshness of training in advance is pre-
Model is surveyed, the corrupt index content of fish body is obtained and determines grade of freshness.
In addition, the logical order in above-mentioned memory 830 can be realized by way of SFU software functional unit and conduct
Independent product when selling or using, can store in a computer readable storage medium.Based on this understanding, originally
The technical solution of the inventive embodiments substantially part of the part that contributes to existing technology or the technical solution in other words
It can be embodied in the form of software products, which is stored in a storage medium, including several fingers
It enables and using so that a computer equipment (can be personal computer, server or the network equipment etc.) executes the present invention respectively
The all or part of the steps of a embodiment the method.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory
(ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic or disk
Etc. the various media that can store program code.
The embodiment of the present invention also provides a kind of non-transient computer readable storage medium, is stored thereon with computer program,
The computer program the is implemented to carry out the various embodiments described above offer fish body based on temperature change when being executed by processor is fresh
Spend detection method, for example,
S1, storage temperature, storage time and the escaping gas for obtaining fish body, extract the gas master of the escaping gas
Signal component value；
S2, that the storage temperature, storage time and gas Principal component are input to the obtained freshness of training in advance is pre-
Model is surveyed, the corrupt index content of fish body is obtained and determines grade of freshness.
The embodiment of the present invention also provides the present embodiment and discloses a kind of computer program product, the computer program product packet
The computer program being stored in non-transient computer readable storage medium is included, the computer program includes program instruction, when
When described program instruction is computer-executed, computer is able to carry out the detection of the fish body freshness as above-mentioned based on temperature change
Method, for example,
S1, storage temperature, storage time and the escaping gas for obtaining fish body, extract the gas master of the escaping gas
Signal component value；
S2, that the storage temperature, storage time and gas Principal component are input to the obtained freshness of training in advance is pre-
Model is surveyed, the corrupt index content of fish body is obtained and determines grade of freshness.
In conclusion a kind of fish body Noninvasive Measuring Method of Freshness and dress based on temperature change provided in an embodiment of the present invention
Set, by measuring the corrupt index of known related clear limit standard and to the sensory evaluation of fish, determine its corrupt trend and
Shelf life: again by its variation for corresponding to escaping gas ingredient or content in decay process of electronic nose Instrument measuring, then
Principal component is extracted with Principal Component Analysis, finally by each storage temperature, storage time and corresponding escaping gas principal component
Value and corrupt index content are applied in radial basis function neural network and establish freshness prediction model, in conjunction with radial basis function meter
It calculates model acquisition salmon escaping gas to calculate corrupt index content in real time and determine grade of freshness, reaches quick nondestructive
Detect the purpose of fish body freshness.
The apparatus embodiments described above are merely exemplary, wherein described, unit can as illustrated by the separation member
It is physically separated with being or may not be, component shown as a unit may or may not be physics list
Member, it can it is in one place, or may be distributed over multiple network units.It can be selected according to the actual needs
In some or all of the modules achieve the purpose of the solution of this embodiment.Those of ordinary skill in the art are not paying creativeness
Labour in the case where, it can understand and implement.
Through the above description of the embodiments, those skilled in the art can be understood that each embodiment can
It realizes by means of software and necessary general hardware platform, naturally it is also possible to pass through hardware.Based on this understanding, on
Stating technical solution, substantially the part that contributes to existing technology can be embodied in the form of software products in other words, should
Computer software product may be stored in a computer readable storage medium, such as ROM/RAM, magnetic disk, CD, including several fingers
It enables and using so that a computer equipment (can be personal computer, server or the network equipment etc.) executes each implementation
Method described in certain parts of example or embodiment.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
Present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: it still may be used
To modify the technical solutions described in the foregoing embodiments or equivalent replacement of some of the technical features；
And these are modified or replaceed, technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution spirit and
Range.
Claims (10)
1. a kind of fish body Noninvasive Measuring Method of Freshness based on temperature change characterized by comprising
Storage temperature, storage time and the escaping gas for obtaining fish body, extract the gas Principal component of the escaping gas；
The storage temperature, storage time and gas Principal component are input to the freshness prediction model that training obtains in advance, obtained
The corrupt index content of fish body simultaneously determines grade of freshness.
2. the fish body Noninvasive Measuring Method of Freshness according to claim 1 based on temperature change, which is characterized in that obtain fish body
Storage temperature, before storage time and escaping gas, further includes:
Obtain storage temperature, storage time and the escaping gas and storage temperature, storage time and escaping gas of fish body
Corresponding TVB-N content, total plate count and sensory evaluation scores；
The gas Principal component in the escaping gas is extracted, with the storage temperature, storage time and gas Principal component
It is output with corresponding TVB-N content, total plate count and sensory evaluation scores for input；Neural metwork training is carried out, is obtained
To freshness prediction model.
3. the fish body Noninvasive Measuring Method of Freshness according to claim 2 based on temperature change, which is characterized in that described in extraction
Gas Principal component in escaping gas, specifically includes:
The principal component in the escaping gas is extracted based on principal component analytical method, the principal component includes the volatility gas
The highest first gas principal component of content, second gas principal component and third gas principal component in body；
It is passed based on the first gas principal component, the second gas principal component and the third gas principal component with corresponding acquisition
The relationship of sensor turns the first gas principal component, the second gas principal component and the third gas principal component respectively
It is changed to first principal component value, Second principal component, value and third Principal component.
4. the fish body Noninvasive Measuring Method of Freshness according to claim 2 based on temperature change, which is characterized in that carry out nerve
Network training specifically includes:
Radial basis function neural network is chosen, using storage temperature, storage time and gas Principal component as the input of input layer, with
TVB-N content, total plate count and sensory evaluation scores are the output of output layer, and it is 40 that maximum neuron number, which is arranged, are surveyed every time
Examination addition neuron number is 1, and relative error is located within ± 10%, obtains freshness prediction model with training.
5. a kind of fish body freshness detection device based on temperature change characterized by comprising
Acquisition module extracts the escaping gas for obtaining the storage temperature, storage time and escaping gas of fish body
Gas Principal component；
Prediction module, for by the storage temperature, storage time and gas Principal component be input in advance training obtain it is new
Freshness prediction model obtains the corrupt index content of fish body and determines grade of freshness.
6. the fish body freshness detection device according to claim 5 based on temperature change, which is characterized in that the acquisition
Module includes temperature sensor and multiple electronic nose sensors；The temperature sensor is for acquiring storage temperature, the electronics
Nose sensor is used to obtain the response of the escaping gas of fish body.
7. the fish body freshness detection device according to claim 5 based on temperature change, which is characterized in that the prediction
Module is also used to:
Obtain storage temperature, storage time and the escaping gas and storage temperature, storage time and escaping gas of fish body
Corresponding TVB-N content, total plate count and sensory evaluation scores；
The gas Principal component in the escaping gas is extracted, with the storage temperature, storage time and gas Principal component
It is output with corresponding TVB-N content, total plate count and sensory evaluation scores for input；Neural metwork training is carried out, is obtained
To freshness prediction model.
8. the fish body freshness detection device according to claim 5 based on temperature change, which is characterized in that the acquisition
Module is also used to:
The principal component in the escaping gas is extracted based on principal component analytical method, the principal component includes the volatility gas
The highest first gas principal component of content, second gas principal component and third gas principal component in body；
It is passed based on the first gas principal component, the second gas principal component and the third gas principal component with corresponding acquisition
The relationship of sensor turns the first gas principal component, the second gas principal component and the third gas principal component respectively
It is changed to first principal component value, Second principal component, value and third Principal component.
9. a kind of electronic equipment including memory, processor and stores the calculating that can be run on a memory and on a processor
Machine program, which is characterized in that the processor is realized as described in any one of Claims 1-4 when executing described program based on temperature
The step of spending the fish body Noninvasive Measuring Method of Freshness of variation.
10. a kind of non-transient computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer
The fish body freshness detection side as described in any one of Claims 1-4 based on temperature change is realized when program is executed by processor
The step of method.
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| CN112345717A (en) * | 2020-10-15 | 2021-02-09 | 武汉轻工大学 | Neural network-based cold fresh pork quality prediction method |
| CN112782376A (en) * | 2021-01-29 | 2021-05-11 | 广州富港万嘉智能科技有限公司 | Food material freshness detection method, storage medium and intelligent cooking equipment |
| CN113515857A (en) * | 2021-07-08 | 2021-10-19 | 中国农业大学 | Multi-period evaluation method and system for storage and transportation process of raw aquatic products |
| CN113515857B (en) * | 2021-07-08 | 2023-08-22 | 中国农业大学 | Multi-period assessment method and system for raw water product storage and transportation process |
| CN113791055A (en) * | 2021-08-17 | 2021-12-14 | 北京农业信息技术研究中心 | Fish freshness detection method and system |
| CN113791055B (en) * | 2021-08-17 | 2024-05-14 | 北京农业信息技术研究中心 | Fish freshness detection method and system |
| CN114414566A (en) * | 2021-12-20 | 2022-04-29 | 北京市农林科学院信息技术研究中心 | Nondestructive testing method and device for freshness of fishes |
| CN115184395A (en) * | 2022-05-25 | 2022-10-14 | 北京市农林科学院信息技术研究中心 | Fruit and vegetable weight loss rate prediction method and device, electronic equipment and storage medium |
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