CN104568776B - Beef holding time detection method - Google Patents
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Abstract
The invention discloses a kind of beef holding time detection method, including Vis/NIR instrument, fibre-optical probe, sample detection pallet, arc guide rail and cantilever, detecting step one：Prepare detection beef sample；Step 2：Beef sample is detected using Vis/NIR instrument；Step 3：It is calculated two principal component output signals PC1 and PC2；Step 4：Carry out principal component analysis；Step 5：Set up the monostable stochastic resonance system output signal strength characteristic peaks tables of data of the beef of different holding times；Step 6：Method according to step one takes beef sample to be measured, repeat step two to four, on the premise of PC1 and PC2 principal component contributor rates are more than or equal to 90%, ifThen the tested time corresponding with signal strength characteristics value Px beef sample holding time is identical.The present invention can quickly, the holding time that is easy, accurately detecting pork, it is ensured that the safety of beef food.
Description
Technical field
The present invention relates to food field of storage, especially a kind of detection method of beef holding time.
Background technology
Beef is consumers in general than preferable food, the safety of beef food, concern common people life security and
Social stability.It is desirable to have it is a kind of can quickly, the easy, method that accurately detects the cold fresh beef holding time, so as to timely
The beef for storing is processed in an orderly manner, it is ensured that the safety of beef food.
The content of the invention
It is an object of the invention to：A kind of beef holding time detection method is provided, can quickly, easy, accurately inspection
The holding time of beef is measured, to process the beef for storing in an orderly manner in time, it is ensured that the safety of beef food.
To achieve the above object, the present invention can take following technical proposals：
A kind of beef holding time detection method of the present invention, including Vis/NIR instrument, double bifurcateds for detecting
Optical fiber, fibre-optical probe, halogen light source and sample detection pallet, the Vis/NIR instrument are connected and lead to computer
Cross described pair of bifurcation fiber to be connected with fibre-optical probe, the halogen light source is by light-source controller controls and by double bifurcated light
Fibre is connected with fibre-optical probe, and the sample detection pallet is spheric, is provided with a circular arc directly over the sample detection pallet and leads
Rail, the center of circle of the arc guide rail overlaps with the centre of sphere of sample detection pallet, and arc guide rail is provided with what is driven by transmission mechanism one
Sliding block, the upper end of a cantilever is radially fixedly arranged on the sliding block, and chute is radially provided with the cantilever, and fibre-optical probe passes through
The driving of transmission mechanism two is slidably installed in the chute on cantilever, and the bottom of sample detection pallet is installed in interior turning
The upper end of axle, arc guide rail is installed on outer shaft by strut, motor by transmission mechanism three respectively with inside and outside rotating shaft transmission
Connection,
Detecting step is ---
Step one：Prepare detection beef sample
Beef sample to be detected is chosen, 5-10 millimeters of thin slice is cut into, sample detection pallet is put into；
Step 2：Beef sample is detected using Vis/NIR instrument
Fibre-optical probe respectively to point to the centre of sphere of sample detection pallet in vertical direction with 0 degree, 15 degree, 30 degree of angle,
Under every kind of angle, using following method gathered data：
Sample detection pallet often rotates 5 degree, suspends 50 seconds, and in 50 seconds of pause, first 25 seconds by light-source controller controls
Halogen light source controls fibre-optical probe by weak crescendo and by transmission mechanism two, and radially groove draws near near sample detection support
Disk, controls fibre-optical probe radially in 25 seconds by light-source controller controls halogen light source by strong diminuendo and by transmission mechanism two afterwards
From the close-by examples to those far off away from sample detection pallet, fibre-optical probe gathered a data to groove every 5 seconds, and the relaxation spectrum using beef sample is special
Property, the effect that is excited of different light intensity different time group and absorb different, detection data is enriched, to eliminate beef sample because of inspection
Survey the measurement difference caused by direction difference, texture difference, musculature difference；
Step 3：It will be seen that the above-mentioned testing result of/near infrared spectrometer is input into the monostable accidental resonance system of computer
System, is calculated two principal component output signals PC1 and PC2；
Step 4：Carry out principal component analysis
If the contribution rate sum of the first two principal component PC1 and PC2 is more than or equal to 90%, monostable accidental resonance output letter
Number can realize the detection of beef holding time；If the contribution rate sum of the first two principal component PC1 and PC2 is less than 90%,
Re-start detection；
Step 5：Set up the monostable stochastic resonance system output signal strength characteristic peaks of the beef of different holding times
Tables of data
Method according to step one is gone bail for the beef sample deposited 1 to 8 day, repeat step two to four, in PC1 and PC2 respectively
On the premise of principal component contributor rate is more than or equal to 90%, the monostable stochastic resonance system output signal of each beef sample is extracted
Strength characteristic peak value P, sets up the monostable stochastic resonance system output signal strength characteristic peaks of the beef of different holding times
Tables of data；
Step 6：Method according to step one takes beef sample to be measured, repeat step two to four, in PC1 and PC2 principal components
On the premise of contribution rate is more than or equal to 90%, monostable stochastic resonance system output signal strength characteristic peaks P is extracted, by P values
Carried out with each characteristic peaks in the monostable stochastic resonance system output signal strength characteristic peaks tables of data of the beef
Compare, if the signal strength characteristics value Px for certain day, hasThen the tested beef sample holding time with
The signal strength characteristics value Px corresponding times are identical.
Light tight sample pool cover is externally provided with sample detection pallet and arc guide rail, for reducing extraneous light to measurement
Interference.
The monostable stochastic resonance system that described monostable stochastic resonance system is described using nonlinear Langevin equation：
Wherein,It is the first derivative of system output x (t)；S (t) is input signal, it will be seen that/near infrared spectrometer
Detection signal is input in monostable system as S (t)；N (t) is the exponential type white Gaussian noise of zero-mean, its auto-correlation
Function isIt is the first derivative of monostable potential function U (x)；And
In formula, a is systematic parameter, represents the biasing of system, influences the position of systematic steady state point, and b is systematic parameter, is taken big
In zero real number,
Formula (1) describes damped motion of the Brownian Particles in monostable system, without input noise and signal
In the case of, system only hasOne steady state point, does not have potential barrier；
System quasi-steady state distribution function can be expressed as：
Wherein, NstIt is normaliztion constant, U (x) is monostable potential function, B (x)=Dx2+2λDx+D。
We define monostable accidental resonance output signal strength approximate calculation expression formula：
Wherein A is input signal amplitude, and D is coloured noise intensity；
Spectral signal is coupled r (t) a cycles signal sin (ω t) as total input signal for we, i.e.,
S (t)=lsin (ω t)+mr (t) (5)
And the least common multiple of l and m is taken as signal input amplitude A；
Therefore the monostable accidental resonance output signal strength of formula (4) expression can be with approximate derivation：
Wherein I (ω) is input power spectrum, and O (ω) is output power spectrum.Wherein O (ω) and I (ω) are approximately：
In spectral detection analysis, it is seen that/near infrared band includes abundant material information, and spectral information is with measured object certainly
The content and composition of body are closely related, therefore Vis/NIR can be applied to classification of substances judgement.Side of the present invention
The beneficial effect of method is：Due to using above-mentioned technical proposal, the ox of different holding times is detected using Vis/NIR instrument
Meat sample product, the accidental resonance signal to noise ratio eigenvalue of curve for extracting spectroscopic data carries out principal component analysis, when realizing different preservations
Between beef sample differentiation, meanwhile, can according to the first two principal component contributor rate sum of principal component analysis judge distinguish journey
Degree.Using kind of a method, can quickly, the holding time that is easy, accurately detecting beef, so as in time in an orderly manner to storage
Beef is processed, it is ensured that the safety of beef food；The sample detection pallet is spheric, and the sample detection pallet is just gone up
Side is provided with an arc guide rail, and the center of circle of the arc guide rail is overlapped with the centre of sphere of sample detection pallet, and arc guide rail is provided with by passing
The sliding block that motivation structure one drives, the upper end of a cantilever is radially fixedly arranged on the sliding block, and cunning is radially provided with the cantilever
Groove, fibre-optical probe is slidably installed in the chute on cantilever by the driving of transmission mechanism two, sample detection pallet
Bottom be installed in the upper end of interior rotating shaft, arc guide rail is installed on outer shaft by strut, and motor passes through three points of transmission mechanism
It is not connected with inside and outside rotating shaft transmission, this structure, sliding block can reciprocatingly slide along arc guide rail, fibre-optical probe can be upper and lower along chute
Slide, motor can rotate sample detection pallet and/or arc guide rail by rotating mechanism, no matter cantilever, light are popped one's head in such as
What is moved, and reflecting surface of the light that light probe sends with sample detection pallet is vertical, can obtain most strong reflected light signal.
Brief description of the drawings
Fig. 1 is the structural representation of inventive samples detecting system；
Fig. 2 is the diffusing reflection spectrum curve synoptic diagram that beef detects sample；
Fig. 3 is the two-dimensional space schematic diagram that principal component PC1 and PC2 are constituted；
Fig. 4 is spectral signal principal component analysis result schematic diagram.
Specific embodiment
As shown in figure 1, a kind of beef holding time detection method of the invention, including the Vis/NIR Spectroscopy for detecting
Spectrometer 12, double bifurcation fibers 13, fibre-optical probe 6, halogen light source 14 and sample detection pallet 4, the Vis/NIR
Instrument 12 is connected with computer 11 and is connected with fibre-optical probe 6 by described pair of bifurcation fiber 13, and the halogen light source 14 is by light
Source controller 15 is controlled and is connected with fibre-optical probe 6 by double bifurcation fibers 13, and the sample detection pallet 4 is spheric, should
The surface of sample detection pallet 4 is provided with an arc guide rail 9, the center of circle of the arc guide rail 9 and the centre of sphere weight of sample detection pallet 4
Close, arc guide rail 9 is provided with the sliding block 10 driven by transmission mechanism one, and the upper end of a cantilever 7 is radially fixedly arranged on the sliding block
On 10, chute 8 is radially provided with the cantilever 7, fibre-optical probe 6 is slidably installed on outstanding by the driving of transmission mechanism two
In the chute 8 on arm 7, the bottom of sample detection pallet 4 is installed in the upper end of interior rotating shaft 31, and arc guide rail 9 passes through strut
It is installed on outer shaft 32, motor 1 is connected with inside and outside rotating shaft 31,32 respectively by transmission mechanism 32, preferably,
Sample detection pallet 4 and arc guide rail 9 are externally provided with light tight sample pool cover, for reducing interference of the extraneous light to measuring,
The step of specific detection method of beef holding time, is as follows：
Step one：Prepare detection beef sample
Beef sample to be detected is chosen, 5-10 millimeters of thin slice is cut into, sample detection pallet 4 is put into；In order to further improve
Testing result, the beef sample of selection, it is possible to specify the position of meat sample, such as ox thigh, ox belly；
Step 2：Beef sample is detected using Vis/NIR instrument
Fibre-optical probe 6 is respectively pointing to the ball of sample detection pallet 4 in vertical direction with 0 degree, 15 degree, 30 degree of angle
The heart, under every kind of angle, using following method gathered data：
Sample detection pallet 4 often rotates 5 degree, suspends 50 seconds, in 50 seconds of pause, is controlled by light source controller 7 within first 25 seconds
Halogen light source processed 5 controls fibre-optical probe 6 by weak crescendo and by transmission mechanism two, and radially groove 8 draws near near sample inspection
Pallet 4 is surveyed, controls halogen light source 5 to control fibre-optical probe by strong diminuendo and by transmission mechanism two by light source controller 7 within 25 seconds afterwards
6 radially groove 8 from the close-by examples to those far off away from sample detection pallet 4, fibre-optical probe 6 gathered a data every 5 seconds, using beef sample
Relaxation spectral property, the effect that is excited of different light intensity different time group and absorb different, detection data is enriched, to eliminate ox
Meat sample product are because of the measurement difference caused by detection direction difference, texture difference, musculature difference；
In order to further enrich detection data, in detection process, fibre-optical probe 6 can be any with the angle of vertical direction
Increase, the anglec of rotation and time out of sample detection pallet 4 can arbitrarily be chosen；In order to reduce beef sample in rotary course
In be subjected to displacement relative to sample detection pallet 4 and influence testing result, it may be preferred to interior rotating shaft is static, by outer shaft drive justify
Arc guide rail rotates；
Step 3：It will be seen that the monostable of the above-mentioned testing result input computer 11 of/near infrared spectrometer 12 is common at random
Vibrating system, is calculated two principal component output signals PC1 and PC2；
Step 4：Carry out principal component analysis
If the contribution rate sum of the first two principal component PC1 and PC2 is more than or equal to 90%, monostable accidental resonance output letter
Number can realize the detection of beef holding time；If the contribution rate sum of the first two principal component PC1 and PC2 is less than 90%,
Re-start detection；
Step 5：Set up the monostable stochastic resonance system output signal strength characteristic peaks of the beef of different holding times
Tables of data
Method according to step one is gone bail for the beef sample deposited 1 to 8 day, repeat step two to four, in PC1 and PC2 respectively
On the premise of principal component contributor rate is more than or equal to 90%, the monostable stochastic resonance system output signal of each beef sample is extracted
Strength characteristic peak value P, sets up the monostable stochastic resonance system output signal strength characteristic peaks of the beef of different holding times
Tables of data；
Step 6：Method according to step one takes beef sample to be measured, repeat step two to four, in PC1 and
On the premise of PC2 principal component contributor rates are more than or equal to 90%, monostable stochastic resonance system output signal is extracted strong
Degree characteristic peaks P, in the monostable stochastic resonance system output signal strength characteristic peaks tables of data by P values with the beef
Each characteristic peaks is compared, if the signal strength characteristics value Px for certain day, hasThe ox being then tested
Time corresponding with signal strength characteristics value Px meat sample product holding time is identical.
The monostable stochastic resonance system that described monostable stochastic resonance system is described using nonlinear Langevin equation：
Wherein,It is the first derivative of system output x (t)；S (t) is input signal, it will be seen that/near infrared spectrometer
12 detection signals are input in monostable system as S (t)；N (t) is the exponential type white Gaussian noise of zero-mean, and it is from phase
Closing function isIt is the first derivative of monostable potential function U (x)；And
In formula, a is systematic parameter, represents the biasing of system, influences the position of systematic steady state point, and b is systematic parameter, is taken big
In zero real number,
Formula (1) describes damped motion of the Brownian Particles in monostable system, without input noise and signal
In the case of, system only hasOne steady state point, does not have potential barrier；
System quasi-steady state distribution function can be expressed as：
Wherein, NstIt is normaliztion constant, U (x) is monostable potential function, B (x)=Dx2+2λDx+D。
We define monostable accidental resonance output signal strength approximate calculation expression formula：
Wherein A is input signal amplitude, and D is coloured noise intensity；
Spectral signal is coupled r (t) a cycles signal sin (ω t) as total input signal for we, i.e.,
S (t)=lsin (ω t)+mr (t) (5)
And the least common multiple of l and m is taken as signal input amplitude A；
Therefore the monostable accidental resonance output signal strength of formula (4) expression can be with approximate derivation：
Wherein I (ω) is input power spectrum, and O (ω) is output power spectrum.Wherein O (ω) and I (ω) are approximately：
Following table is the monostable stochastic resonance system output signal strength characteristic peaks of the beef of different holding times
The spectral curve that diffuses of Fig. 2 beef samples, spectral signal intensity highest near 625nm, in addition 472nm,
Also characteristic peak is occurred in that at 562nm, 710nm and 441nm, spectral detection signal contains the detection information compared with horn of plenty.
The beef spectral detection data input of different storage times is chosen to being analyzed in monostable stochastic resonance system.
One feature of accidental resonance is and the intrinsic noise signal in non-elimination detecting system, and uses the outer noise modulated mesh of addition
Mark signal reaches resonance state, strengthens Target Weak Signal and is easy to detection.Fig. 3 is that the two dimension that principal component PC1 and PC2 are constituted is empty
Between schematic diagram, the output signal-to-noise ratio curve of the beef sample spectroscopic data of different holding times is in rising trend first, in noise
Begun to decline after maximum is reached at intensity 87, the contribution rate of the first two principal component is respectively 80.21% and 12.79%, difference
There is obvious differentiation between the beef sample of storage time, therefore monostable accidental resonance output signal can be as beef sample
The foundation of differentiation.
Fig. 4 is spectral signal principal component analysis result schematic diagram.
Claims (2)
1. a kind of beef holding time detection method, including Vis/NIR instrument (12), bifurcation fiber for detecting
(13), fibre-optical probe (6), halogen light source (14) and sample detection pallet (4), the Vis/NIR instrument (12) with
Computer (11) is connected and is connected with fibre-optical probe (6) by the bifurcation fiber (13), and the halogen light source (14) is by light
Source controller (15) is controlled and is connected with fibre-optical probe (6) by bifurcation fiber (13), it is characterised in that：The sample detection
Pallet (4) is spheric, is provided with an arc guide rail (9) directly over the sample detection pallet (4), the circle of the arc guide rail (9)
The heart overlaps with the centre of sphere of sample detection pallet (4), and arc guide rail (9) is provided with the sliding block (10) driven by transmission mechanism one, one
The upper end of cantilever (7) is radially fixedly arranged on the sliding block (10), and chute (8) is radially provided with the cantilever (7), and optical fiber is visited
Head (6) is slidably installed on the chute (8) on cantilever (7) Nei by the driving of transmission mechanism two, sample detection pallet
(4) bottom is installed in the upper end of interior rotating shaft, and arc guide rail (9) is installed on outer shaft by strut, and motor (1) is by transmission
Mechanism three (2) is connected with inside and outside rotating shaft transmission respectively,
Detecting step is ---
Step one：Prepare detection beef sample
Beef sample to be detected is chosen, 5-10 millimeters of thin slice is cut into, sample detection pallet (4) is put into；
Step 2：Beef sample is detected using Vis/NIR instrument
Fibre-optical probe (6) is respectively pointing to the ball of sample detection pallet (4) in vertical direction with 0 degree, 15 degree, 30 degree of angle
The heart, under every kind of angle, using following method gathered data：
Sample detection pallet (4) often rotates 5 degree, suspends 50 seconds, in 50 seconds of pause, is controlled by light source controller (15) within first 25 seconds
Halogen light source (14) processed controls fibre-optical probe (6) to be drawn near near sample along chute (8) by weak crescendo and by transmission mechanism two
Pallet (4) is surveyed in product examine, controls halogen light source (14) by strong diminuendo and by transmission mechanism two by light source controller (15) within 25 seconds afterwards
Along chute (8) from the close-by examples to those far off away from sample detection pallet (4), fibre-optical probe (6) gathered one every 5 seconds for control fibre-optical probe (6)
Individual data, the effect and absorption being excited using the relaxation spectral property of beef sample, different light intensity different time groups is different, rich
Rich detection data, to eliminate beef sample because the measurement caused by detection direction difference, texture difference, musculature difference is poor
It is different；
Step 3：It will be seen that the monostable of above-mentioned testing result input computer (11) of/near infrared spectrometer (12) is common at random
Vibrating system, is calculated two principal component output signals PC1 and PC2；
Step 4：Carry out principal component analysis
If the contribution rate sum of the first two principal component PC1 and PC2 is more than or equal to 90%, monostable accidental resonance output signal can
To realize the detection of beef holding time；If the contribution rate sum of the first two principal component PC1 and PC2 is less than 90%, again
Detected；
Step 5：Set up the monostable stochastic resonance system output signal strength characteristic peaks data of the beef of different holding times
Table
Method according to step one is gone bail for the beef sample deposited 1 to 8 day respectively, repeat step two to four, PC1 and PC2 it is main into
On the premise of dividing contribution rate more than or equal to 90%, the monostable stochastic resonance system output signal strength of each beef sample is extracted
Characteristic peaks P, sets up the monostable stochastic resonance system output signal strength characteristic peaks data of the beef of different holding times
Table；
Step 6：Method according to step one takes beef sample to be measured, repeat step two to four, in the contribution of PC1 and PC2 principal components
On the premise of rate is more than or equal to 90%, monostable stochastic resonance system output signal strength characteristic peaks P is extracted, by P values and institute
Each characteristic peaks stated in the monostable stochastic resonance system output signal strength characteristic peaks tables of data of beef are compared,
If the signal strength characteristics value Px for certain day, hasThen the tested beef sample holding time is strong with signal
The degree characteristic value Px corresponding times are identical.
2. beef holding time detection method according to claim 1, it is characterised in that：In sample detection pallet (4) and
Arc guide rail (9) is externally provided with light tight sample pool cover, for reducing interference of the extraneous light to measuring.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7238954B1 (en) * | 2003-10-08 | 2007-07-03 | Fay Jr Theodore Denis | Optical external cavities having brewster angle wedges |
| CN102507459A (en) * | 2011-11-23 | 2012-06-20 | 中国农业大学 | Method and system for quick lossless evaluation on freshness of fresh beef |
| CN103308457A (en) * | 2013-04-10 | 2013-09-18 | 浙江工商大学 | Establishment method of prediction model for bergamot pear maturity |
| CN103383350A (en) * | 2013-06-28 | 2013-11-06 | 中国丝绸博物馆 | Non-constructive detection method for dyes on textile antiques |
| CN103424374A (en) * | 2013-06-19 | 2013-12-04 | 浙江省海洋开发研究院 | Method for quickly detecting freshness level of hairtail by using near-infrared spectrum technology |
| CN104076001A (en) * | 2013-12-17 | 2014-10-01 | 浙江工商大学 | Detection device based on laser array and large yellow croaker storage time detection method |
| CN104089881A (en) * | 2013-12-17 | 2014-10-08 | 浙江工商大学 | Pseudosciaena crocea storage time detection method |
| CN104089897A (en) * | 2014-03-31 | 2014-10-08 | 浙江工商大学 | Detection device and detection method for spliced beef |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09145606A (en) * | 1995-11-28 | 1997-06-06 | Shimadzu Corp | Spectroscopic measuring instrument |
-
2015
- 2015-01-01 CN CN201510002903.8A patent/CN104568776B/en not_active Expired - Fee Related
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7238954B1 (en) * | 2003-10-08 | 2007-07-03 | Fay Jr Theodore Denis | Optical external cavities having brewster angle wedges |
| CN102507459A (en) * | 2011-11-23 | 2012-06-20 | 中国农业大学 | Method and system for quick lossless evaluation on freshness of fresh beef |
| CN103308457A (en) * | 2013-04-10 | 2013-09-18 | 浙江工商大学 | Establishment method of prediction model for bergamot pear maturity |
| CN103424374A (en) * | 2013-06-19 | 2013-12-04 | 浙江省海洋开发研究院 | Method for quickly detecting freshness level of hairtail by using near-infrared spectrum technology |
| CN103383350A (en) * | 2013-06-28 | 2013-11-06 | 中国丝绸博物馆 | Non-constructive detection method for dyes on textile antiques |
| CN104076001A (en) * | 2013-12-17 | 2014-10-01 | 浙江工商大学 | Detection device based on laser array and large yellow croaker storage time detection method |
| CN104089881A (en) * | 2013-12-17 | 2014-10-08 | 浙江工商大学 | Pseudosciaena crocea storage time detection method |
| CN104089897A (en) * | 2014-03-31 | 2014-10-08 | 浙江工商大学 | Detection device and detection method for spliced beef |
Non-Patent Citations (1)
| Title |
|---|
| 采用粒子群算法的冲击信号自适应单稳态随机共振检测方法;李继猛等;《机械工程学报》;20111130;第47卷(第21期);58-63 * |
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