CN105891020B - A kind of tenderness fast non-destructive detection method based on air-flow pulse and laser ranging - Google Patents
A kind of tenderness fast non-destructive detection method based on air-flow pulse and laser ranging Download PDFInfo
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- CN105891020B CN105891020B CN201610196609.XA CN201610196609A CN105891020B CN 105891020 B CN105891020 B CN 105891020B CN 201610196609 A CN201610196609 A CN 201610196609A CN 105891020 B CN105891020 B CN 105891020B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N3/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N3/30—Investigating strength properties of solid materials by application of mechanical stress by applying a single impulsive force, e.g. by falling weight
- G01N3/307—Investigating strength properties of solid materials by application of mechanical stress by applying a single impulsive force, e.g. by falling weight generated by a compressed or tensile-stressed spring; generated by pneumatic or hydraulic means
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N3/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N3/02—Details
- G01N3/06—Special adaptations of indicating or recording means
- G01N3/068—Special adaptations of indicating or recording means with optical indicating or recording means
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N2203/003—Generation of the force
- G01N2203/0042—Pneumatic or hydraulic means
- G01N2203/0044—Pneumatic means
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N2203/0058—Kind of property studied
- G01N2203/0069—Fatigue, creep, strain-stress relations or elastic constants
- G01N2203/0075—Strain-stress relations or elastic constants
Abstract
The present invention relates to a kind of tenderness fast non-destructive detection methods based on air-flow pulse and laser ranging, include the following steps：S1, sample collection and displacement information acquisition, and form displacement curve；S2, tenderness physics and chemistry value is obtained；S3,6 parameters are extracted to the displacement curve in S1；S4, the displacement curve in S1 is fitted using the function of many variables, obtains 6 function of many variables fit characteristic parameters；S5, three kinds of regressive prediction models are established；S6, the precision for comparing three kinds of regressive prediction models obtain tenderness prediction best model, and poultry meat sample tenderness predicted value to be measured can be obtained using the prediction best model.The present invention based on air-flow pulse and laser ranging detection poultry meat tenderness, acquires change in displacement data by laser displacement sensor, establishes the prediction model between tenderness and displacement curve, for finally detecting, have the advantages that non-destructive, quick nondestructive.
Description
Technical field
The present invention relates to the field of non destructive testing of poultry measurement techniques for quality detection of meat, specifically a kind of to be based on air-flow pulse and Laser Measuring
Away from tenderness fast non-destructive detection method.
Background technology
China is a meat consumption big country, as the improvement of people's living standards, meat quality is also more next by people
More concerns.The index of quality of meat includes tenderness, freshness, color and luster, flavor, is waterpower etc., and wherein tenderness is as evaluation meat
The primary index of product quality becomes the emphasis of many research worker's researchs.
The tenderness of meat refers to mouthfeel of the meat when eating, and the quality of meat is reflected, also as consumer evaluation's meat quality
One of common counter.More currently for the tenderness detection technique method of poultry meat, traditional meat tenderness evaluation is main
There are two methods of subjective assessment and objective evaluation, subjective assessment is judged by veteran reviewer, evaluation result
By interference caused by subjective factors, error is larger；Objective evaluation is presently mainly according to cutting described in professional standard NY/T1180-2006
Shear force measuring method measures the shearing force of meat using tenderness boxshear apparatus, and this method has destructiveness, and measurement process is complicated, consumption
When, the meat sample after measure loses follow-up use value, causes to waste.
For above deficiency, in order to improve the tenderness detection technique of poultry meat, the lossless quick detection method tool of research
It is of great significance.
Invention content
For defect in the prior art, the purpose of the present invention is to provide a kind of method for detecting meat tenderness,
Tenderness fast non-destructive detection method based on air-flow pulse and laser ranging, has the advantages that non-destructive, quick nondestructive.
To achieve the above objectives, the technical solution adopted by the present invention is that：
A kind of tenderness fast non-destructive detection method based on air-flow pulse and laser ranging, which is characterized in that including as follows
Step：
S1, sample collection and displacement information acquisition：Under same time point, same external environment, using having merged air-flow
Pulse and the poultry meat viscoelasticity nondestructive detection system of laser ranging, what the displacement that acquisition is no less than 10 samples changed over time
Data, and form displacement curve；
S2, each sample in S1 is detected its tenderness according to chemical detection method as defined in professional standard, obtains
Obtain tenderness physics and chemistry value；
S3, following 6 parameters are extracted to the displacement curve in S1：
The displacement curve area S1 of displacement curve loading section,
Displacement curve unloads the displacement curve area S2 of part,
Maximum compression displacement d1,
Displacement d2 is replied,
Instantaneous herk displacement variable L1,
Instantaneous unloading displacement variable L2；
S4, the displacement curve in S1 is fitted using the function of many variables, displacement curve is divided into according to whether air-flow acts on
Loading and unloading two parts, obtain 6 function of many variables fit characteristic parameters；
The function of many variables are：
As 0≤t≤t1When,
Work as t1During≤t,
In formula：T is the time, and y is shift value, t1For the load time, i.e., in t1Moment air-flow starts to act on sample surfaces,
a1、b1、c1、a2、b2、c2For function of many variables fit characteristic parameter, aftermentioned research is participated in；
S5, regressive prediction model is established：
6 parameters extracted in the tender assay value and S3 that are measured in S2 are established and treat modeling set, are divided into school in proportion
Positive collection and verification collection, establish regressive prediction model；
6 parameters extracted in the tender assay value and S4 that are measured in S2 are established and treat modeling set, are divided into school in proportion
Positive collection and verification collection, establish another regressive prediction model；
12 characteristic parameters altogether extracted in the tender assay value and S3, S4 that are measured in S2 are established and treat modeling set,
It is divided into calibration set in proportion and verification collects, establishes another regressive prediction model；
S6, the precision for comparing three kinds of regressive prediction models obtain tenderness prediction best model, utilize the best mould of prediction
Type can obtain poultry meat sample tenderness predicted value to be measured.
Based on the above technical solution, in step S1, sample uses same size, and same position cannot take sample
Excessively.
Based on the above technical solution, step S7 is further included：
When S7, S5 establish regressive prediction model, characteristic parameter is modeled, to eliminate the synteny between parameter, is established
Before regressive prediction model, need to pre-process characteristic parameter using some Variable Selection methods.
Based on the above technical solution, in step S1,
Air-flow pulse is provided by air pump, and acts power to sample surfaces；
Laser ranging acquires the displacement of each sample at any time for measuring change in displacement data by laser displacement sensor
Between change information；
The operating condition of nondestructive detection system is：Air pump pressure is 30kPa~80kPa, sample frequency 50Hz, during sampling
Between no less than 12s.
Based on the above technical solution, in step s 2, the measure of tenderness physics and chemistry value is according to professional standard NY/
Chemical detection method as defined in T1180-2006 is detected to obtain to the tenderness of sample.
Based on the above technical solution, in step s 5, the ratio of calibration set and verification collection is 2~3:1.
Based on the above technical solution, in step s 5, it using the characteristic parameter of calibration set and tenderness physics and chemistry value, builds
The prediction model of vertical sample tenderness establishes prediction model using Partial Least Squares Regression, multiple linear regression and least square branch
Hold vector machine regression modeling；
Using characteristic parameter, tenderness physics and chemistry value and the calibration set model of verification collection, the accuracy of prediction model is judged, determine
For the change in displacement information optimum prediction model of meat tenderness.
Based on the above technical solution, in step s 6, it is related to include calibration set for the parameter of judgment models accuracy
Coefficients Rc, calibration set standard deviation S EC, verification collection coefficient Rv, verification collection standard deviation S EP and validation-cross standard deviation
SECV。
Based on the above technical solution, in the step s 7, the Variable Selection method is Principal Component Analysis, even
Continuous projection algorithm or ridge analysis method.
Tenderness fast non-destructive detection method of the present invention based on air-flow pulse and laser ranging has non-demolition
The advantages of property, quick nondestructive.
Tenderness fast non-destructive detection method of the present invention based on air-flow pulse and laser ranging, passes through air-flow pulse
Meat surface is caused to impact, then laser ranging (laser displacement sensor) acquisition change in displacement data extract displacement curve
Characteristic parameter, the synteny between parameter is eliminated using effective characteristic parameter preprocess method, it is bent to establish tenderness and displacement
Prediction model between line for finally detecting, has the advantages that non-destructive, quick nondestructive.
Description of the drawings
The present invention has drawings described below：
The flow chart of Fig. 1 present invention.
Fig. 2 experiment acquisition displacement curves.
Fig. 3 area features.
Fig. 4 displacement characteristics.
Fig. 5 immediate movement features.
Fig. 6 loading curves.
Fig. 7 loads matched curve.
Fig. 8 unloading curves.
Fig. 9 unloads matched curve.
Specific embodiment
The present invention is described in further detail below in conjunction with attached drawing.
As shown in Figure 1, the tenderness fast non-destructive detection method of the present invention based on air-flow pulse and laser ranging, tool
Body includes the following steps：
S1, sample collection and displacement information acquisition：Under same time point, same external environment, using having merged air-flow
Pulse and the poultry meat viscoelasticity nondestructive detection system of laser ranging, what the displacement that acquisition is no less than 10 samples changed over time
Data, and form displacement curve；
Sample uses same size, and same position cannot take sample excessive；
S2, each sample in S1 is detected its tenderness according to chemical detection method as defined in professional standard, obtains
Obtain tenderness physics and chemistry value；
S3, following 6 parameters are extracted to the displacement curve in S1：
The displacement curve area S1 of displacement curve loading section,
Displacement curve unloads the displacement curve area S2 of part,
Maximum compression displacement d1,
Displacement d2 is replied,
Instantaneous herk displacement variable L1,
Instantaneous unloading displacement variable L2；
S4, the displacement curve in S1 is fitted using the function of many variables, displacement curve is divided into according to whether air-flow acts on
Loading and unloading two parts, obtain 6 function of many variables fit characteristic parameters；
The function of many variables are：
As 0≤t≤t1When,
Work as t1During≤t,
In formula：T is the time, and y is shift value, t1For the load time, i.e., in t1Moment air-flow starts to act on sample surfaces,
a1、b1、c1、a2、b2、c2For function of many variables fit characteristic parameter, aftermentioned research is participated in；
S5, regressive prediction model is established：
6 parameters extracted in the tender assay value and S3 that are measured in S2 are established and treat modeling set, are divided into school in proportion
Positive collection and verification collection, establish regressive prediction model；
6 parameters extracted in the tender assay value and S4 that are measured in S2 are established and treat modeling set, are divided into school in proportion
Positive collection and verification collection, establish another regressive prediction model；
12 characteristic parameters altogether extracted in the tender assay value and S3, S4 that are measured in S2 are established and treat modeling set,
It is divided into calibration set in proportion and verification collects, establishes another regressive prediction model；
S6, the precision for comparing three kinds of regressive prediction models obtain tenderness prediction best model, utilize the best mould of prediction
Type can obtain poultry meat sample tenderness predicted value to be measured.
Based on the above technical solution, in step sl, the poultry meat viscoelasticity nondestructive detection system, preferably Shen
Please livestock meat viscoelasticity nondestructive detection system, the nondestructive detection system described in (patent) number CN201410770806.9 merge
Air-flow pulse and laser ranging, wherein：
Air-flow pulse is provided by air pump, and acts power to sample surfaces；
Laser ranging acquires the displacement of each sample at any time for measuring change in displacement data by laser displacement sensor
Between change information；
The operating condition of the nondestructive detection system is：Air pump pressure is 30kPa~80kPa, sample frequency 50Hz, is sampled
Time is no less than 12s.
Based on the above technical solution, in step s 2, the measure of tenderness physics and chemistry value is according to professional standard NY/
Chemical detection method as defined in T1180-2006 is detected to obtain to the tenderness of sample.
Based on the above technical solution, as shown in figure 3, in step s3, the displacement of displacement curve loading section is bent
Line area S1 is started to act on to air-flow by air-flow to fail the area that time intrinsic displacement curve surrounds with y=0,
The displacement curve area S2 of displacement curve unloading part fails for air-flow and tends to parallel (displacement to displacement curve
Value tends to a steady state value) the area that is surrounded of time (t is no less than 7s) intrinsic displacement curve and y=0,
It is apparent from the displacement curve area S1 of displacement curve loading section and the displacement curve area of displacement curve unloading part
S2 is related to action time；
As shown in figure 4, in step s3, maximum compression displacement d1 is shift value and the displacement of displacement minimum point when not loading
Difference, it is the displacement difference that displacement gradually reverts to a steady state value and displacement minimum point after unloading to reply displacement d2；
As shown in figure 5, in step s3, instantaneous herk displacement variable L1 refers to sample a certain fixation under airflow function
Immediate movement decrement in time (time, t was between 0.02s-0.06s),
Instantaneous unloading displacement variable L2 refers to that same set time of the sample after air-flow consumption, (time, t existed
Between 0.02s-0.06s) in immediate movement reply volume.
Based on the above technical solution, in step s 5, the ratio of calibration set and verification collection is 2~3:1.
Based on the above technical solution, in step s 5, it using the characteristic parameter of calibration set and tenderness physics and chemistry value, builds
The prediction model of vertical sample tenderness establishes prediction model using Partial Least Squares Regression, multiple linear regression and least square branch
Hold vector machine regression modeling；
Using characteristic parameter, tenderness physics and chemistry value and the calibration set model of verification collection, the accuracy of prediction model is judged, determine
For the change in displacement information optimum prediction model of meat tenderness.
Based on the above technical solution, in step s 6, it is related to include calibration set for the parameter of judgment models accuracy
Coefficients Rc, calibration set standard deviation S EC, verification collection coefficient Rv, verification collection standard deviation S EP and validation-cross standard deviation
SECV。
Based on the above technical solution, step S7 is further included：
When S7, S5 establish regressive prediction model, characteristic parameter is modeled, to eliminate the synteny between parameter, is established
Before regressive prediction model, need to pre-process characteristic parameter using some Variable Selection methods.
In the step s 7, the Variable Selection method is Principal Component Analysis, successive projection algorithm or ridge analysis
Method.
The above-mentioned technical proposal of the present invention has the advantages that：It is bent that the curve that sample displacement data are formed is divided into loading
Line and unloading curve two parts, the method by extracting displacement curve characteristic parameter and curve matching respectively, to two methods
The characteristic parameter of extraction establishes the prediction model between tenderness physics and chemistry value and displacement curve, and eventually for unknown tenderness meat
Detection.This method can establish the new detection method of meat tenderness, and meat tenderness physics and chemistry value is directly obtained by this method.
It is illustrated below by way of the example of 52 samples：
(1), sample displacement information collection
In step S1,52 parts of beef samples are bought from supermarket, sample cuts into same size, identical at same time point
It is operated under external environment.Using application No. is 201410770806.9 poultry meat viscoelasticity nondestructive detection system, this is
System fusion air-flow pulse and the method for laser ranging, wherein air-flow pulse is provided by air pump, and acts power to sample surfaces；
For laser displacement sensor for measuring change in displacement, the displacement for acquiring each sample changes over time information.Air pump pressure is
Between 70kPa, sample frequency 50HZ, i.e. harvester every 0.02s acquire a displacement data, acquisition time 15s, from
3s starts air-flow and sample is acted, and 5s air-flows stop, and displacement starts to restore, and acquires the data of 15s altogether as treating point
Analyse data.Using 0mm as displacement datum, laser displacement sensor acquisition is change in displacement absolute value, and the curve of formation is negative
To displacement curve, as shown in Figure 2.
(2) tenderness physics and chemistry value measures
In step S2, the sample for having acquired displacement curve is examined according to chemistry as defined in professional standard NY/T1180-2006
Survey method is detected the tenderness of sample to obtain chemical measurements, preferably as early as possible, is placed in air to avoid sample too long
Influence result.
(3) parameter of curve is extracted
In step S3, loaded according to air-flow, discharge time, by the displacement curve of acquisition be divided into loading curve (3s~5s) and
Unloading curve (5s~15s) two parts, as shown in Fig. 2, when the displacement curve area S1 of displacement curve loading section is 3s~5s
Between the area that is surrounded of intrinsic displacement curve and y=0, the displacement curve area S2 of displacement curve unloading part is position in 5s~15s
Move the area that curve is surrounded with y=0.Maximum compressibility d1, the maximum reply volume d2 of displacement are directly carried by curvilinear figure feature
It takes.
What immediate movement took is to start the immediate movement decrement L1 under effect in 0.04s and disappear in air-flow to make in air-flow
With the immediate movement reply volume L2 in the 0.04s of rear (5s).
(4) function of many variables are fitted
In step S4, function of many variables fitting is carried out to curve, the function of many variables specifically used are as follows：
As 0≤t≤t1When,
Work as t1During≤t,
In formula：T is the time, and y is shift value, t1For the load time, i.e., in t1Moment air-flow starts to act on sample surfaces,
a1、b1、c1、a2、b2、c2For function of many variables fit characteristic parameter, aftermentioned research is participated in.
Respectively as shown in Figure 6, Figure 7, unloading curve divides after unloading curve and fitting for loading curve and loading curve after fitting
Not as shown in Figure 8, Figure 9.
(5) division of calibration set and verification collection
In step S5, sample principal component is grouped, according to 3:1 ratio, two groups are respectively 39 and 13.
(6) model foundation
To d1, d2, S1, S2, L1 and L2 for being extracted in tenderness physics and chemistry value and step S3, totally 6 parameters are established and treat modeling collection
It closes, by 3:1 ratio is divided into calibration set and verification collects, and establishes regressive prediction model；
To a extracted in tenderness physics and chemistry value and step S41、b1、c1、a2、b2、c2Totally 6 parameters, which are established, treats modeling set, presses
3:1 ratio is divided into calibration set and verification collects, and establishes regressive prediction model；
12 characteristic parameters altogether extracted in tenderness physics and chemistry value and step S3, S4 are established and treat modeling set, by 3:1
Ratio is divided into calibration set and verification collects, and establishes regressive prediction model.
(7) collinear of parameter is eliminated
In view of between the characteristic parameter of extraction there are synteny, before establishing and predicting regression model, using principal component
Analytic approach, successive projection algorithm and ridge analysis method treat three kinds in (6) modeling set pre-processes, selection variables, ginseng
It is established with aftermentioned prediction regression model.
(8) evaluation of model
In step S5, for the prediction regression model of foundation, the parameter of judgment models accuracy includes calibration set phase relation
Number RC, calibration set standard deviation S EC, verification collection coefficient Rv, verification collection standard deviation S EP and validation-cross standard deviation
SECV.General calibration set coefficient RC, verification collection coefficient RvValue is bigger and better close to 1, calibration set standard deviation S EC,
Verification collection standard deviation S EP and validation-cross standard deviation S ECV values are smaller and better closer to 0.
Modeling result is as shown in the following table 1, table 2 and table 3, the results showed that：Best modeled method is 12 features to extraction
The Partial Least-Squares Regression Model established after parameter principal component analysis, the number of principal components of best meat tenderness prediction model is 7, school
Positive collection coefficient RC=0.81, calibration set standard deviation S EC=1.01, verification collection coefficient Rv=0.79, verify collection standard
Deviation SEP=1.11.
16 parameter of table (a1, b1, c1, a2, b2, c2) tenderness modeling result
26 parameter of table (d1, d2, S1, S2, L1, L2) tenderness modeling result
3 12 parameter of table (a1, b1, c1, a2, b2, c2, d1, d2, S1, S2, L1, L2) tenderness modeling result
In conclusion the present invention provides a kind of tenderness fast non-destructive detection method based on air-flow pulse and laser ranging,
It is effectively extracted by the displacement information to acquisition, characteristic parameter and tender assay value is established into prediction model one by one, used
Effective characteristic parameter preprocess method eliminates the synteny between parameter, determines best modeled method and obtains prediction model,
Partial Least-Squares Regression Model best results are established after obtaining 12 parameter principal component regressions by comparing, verification collection related coefficient reaches
To 0.79.This method can establish the model between tenderness and displacement curve, and the meat of unknown tenderness value can be sentenced
Fixed prediction.
The embodiment of the present invention provides for the sake of example and description, and is not exhaustively or by this to send out
It is bright to be limited to disclosed form.Many modifications and variations are obvious for the ordinary skill in the art.Choosing
It is to more preferably illustrate the principle of the present invention and practical application to select and describe embodiment, and makes those of ordinary skill in the art
It will be appreciated that the present invention is so as to design the various embodiments with various modifications suitable for special-purpose.
The content not being described in detail in this specification belongs to the prior art well known to professional and technical personnel in the field.
Claims (9)
1. a kind of tenderness fast non-destructive detection method based on air-flow pulse and laser ranging, which is characterized in that including walking as follows
Suddenly：
S1, sample collection and displacement information acquisition：Under same time point, same external environment, using having merged air-flow pulse
With the poultry meat viscoelasticity nondestructive detection system of laser ranging, acquisition is no less than the number that the displacement of 10 samples changes over time
According to, and form displacement curve；
S2, each sample in S1 is detected its tenderness according to chemical detection method as defined in professional standard, obtains tender
Spend physics and chemistry value；
S3, following 6 characteristic parameters are extracted to the displacement curve in S1：
The displacement curve area S1 of displacement curve loading section,
Displacement curve unloads the displacement curve area S2 of part,
Maximum compression displacement d1,
Displacement d2 is replied,
Instantaneous herk displacement variable L1,
Instantaneous unloading displacement variable L2；
S4, the displacement curve in S1 is fitted using the function of many variables, displacement curve is divided into loading according to whether air-flow acts on
With unloading two parts, 6 function of many variables fit characteristic parameters are obtained；
The function of many variables are：
As 0≤t≤t1When,
Work as t1During≤t,
In formula：T is the time, and y is shift value, t1For the load time, i.e., in t1Moment air-flow starts to act on sample surfaces, a1、b1、
c1、a2、b2、c2For function of many variables fit characteristic parameter, aftermentioned research is participated in；
S5, regressive prediction model is established：
6 characteristic parameters extracted in the tender assay value and S3 that are measured in S2 are established and treat modeling set, are divided into school in proportion
Positive collection and verification collection, establish regressive prediction model；
6 characteristic parameters extracted in the tender assay value and S4 that are measured in S2 are established and treat modeling set, are divided into school in proportion
Positive collection and verification collection, establish another regressive prediction model；
12 characteristic parameters altogether extracted in the tender assay value and S3, S4 that are measured in S2 are established and treat modeling set, by than
Example is divided into calibration set and verification collects, and establishes another regressive prediction model；
S6, the precision for comparing three kinds of regressive prediction models obtain tenderness prediction best model, can using the prediction best model
Obtain poultry meat sample tenderness predicted value to be measured.
2. the tenderness fast non-destructive detection method based on air-flow pulse and laser ranging, feature exist as described in claim 1
In：In step S1, sample uses same size, and same position cannot take sample excessive.
3. the tenderness fast non-destructive detection method based on air-flow pulse and laser ranging, feature exist as described in claim 1
In：Further include step S7：
When S7, S5 establish regressive prediction model, characteristic parameter is modeled, to eliminate the synteny between parameter, establishes and returns
Before prediction model, need to pre-process characteristic parameter using some Variable Selection methods.
4. the tenderness fast non-destructive detection method based on air-flow pulse and laser ranging, feature exist as described in claim 1
In：In step S1,
Air-flow pulse is provided by air pump, and acts power to sample surfaces；
For measuring change in displacement data, the displacement that each sample is acquired by laser displacement sensor becomes at any time for laser ranging
Change information；
The operating condition of nondestructive detection system is：Air pump pressure is 30kPa~80kPa, and sample frequency 50Hz, the sampling time is not
Less than 12s.
5. the tenderness fast non-destructive detection method based on air-flow pulse and laser ranging, feature exist as described in claim 1
In：In step s 2, the measure of tenderness physics and chemistry value according to chemical detection method as defined in professional standard NY/T1180-2006 to sample
The tenderness of product is detected to obtain.
6. the tenderness fast non-destructive detection method based on air-flow pulse and laser ranging, feature exist as described in claim 1
In：In step s 5, the ratio of calibration set and verification collection is 2~3:1.
7. the tenderness fast non-destructive detection method based on air-flow pulse and laser ranging, feature exist as described in claim 1
In：In step s 5, using the characteristic parameter of calibration set and tenderness physics and chemistry value, the prediction model of sample tenderness is established, is established pre-
It surveys model and uses Partial Least Squares Regression, multiple linear regression and least square method supporting vector machine regression modeling；
Using characteristic parameter, tenderness physics and chemistry value and the calibration set model of verification collection, judge the accuracy of prediction model, determine to be directed to
The change in displacement information optimum prediction model of meat tenderness.
8. the tenderness fast non-destructive detection method based on air-flow pulse and laser ranging, feature exist as claimed in claim 7
In：In step s 6, the parameter of judgment models accuracy includes calibration set coefficient Rc, calibration set standard deviation S EC, verification
Collect coefficient Rv, verification collection standard deviation S EP and validation-cross standard deviation S ECV.
9. the tenderness fast non-destructive detection method based on air-flow pulse and laser ranging, feature exist as claimed in claim 3
In：In the step s 7, the Variable Selection method is Principal Component Analysis, successive projection algorithm or ridge analysis method.
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| CN108801795A (en) * | 2018-06-20 | 2018-11-13 | 中国农业大学 | A kind of livestock meat viscoelasticity detection data acquisition method based on air-flow and laser |
| CN108827783B (en) * | 2018-06-20 | 2019-11-26 | 中国农业大学 | A kind of more elements of livestock meat are glutinous to play method for establishing model |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104458594A (en) * | 2014-12-16 | 2015-03-25 | 中国农业大学 | System and method for simultaneously detecting quality parameters of raw meat from multiple points |
| CN104568736A (en) * | 2014-12-12 | 2015-04-29 | 中国农业大学 | Nondestructive testing method for visco-elasticity of livestock and poultry meat |
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