CN114705727A - Meat quality corruption detection method considering multilayer space-time impedance difference - Google Patents
Meat quality corruption detection method considering multilayer space-time impedance difference Download PDFInfo
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Abstract
The invention discloses a meat quality deterioration detection method and system considering multilayer space-time-impedance difference. Firstly, obtaining a fish body area to be measured, measuring the fish body impedance of each putrefaction area by calculating a space-impedance difference coefficient obtained by calculating the xyz space-impedance difference of the fish body of each putrefaction area and a time-impedance difference coefficient obtained by calculating the time-impedance difference of the fish body of each putrefaction area, calculating a space-impedance difference coefficient according to the space-impedance difference coefficient and the time-impedance difference coefficient, and reconstructing the fish body impedance of each putrefaction area according to the space-impedance difference coefficient; and calculating the corruption grade of each corruption area and calculating the overall corruption degree of the area to be detected of the fish body. On the one hand, the quick and nondestructive detection of the bio-impedance can be realized based on the flexible impedance electrode, and on the other hand, the fish body impedance can be reconstructed aiming at the multilayer space-time impedance difference characteristic of the fish impedance measurement, so that the impedance measurement result can more accurately represent the fish body putrefaction degree.
Description
Technical Field
The disclosure relates to the field of flexible electronics, bioimpedance sensing and meat quality corruption prediction, in particular to a meat quality corruption detection method and system considering multilayer space-time impedance difference.
Background
At present, the aquatic product breeding industry develops rapidly, and high-quality animal protein food can be economically provided for human beings. In animal breeding, the fish is aquatic temperature-variable animal, and has low energy consumption, high feed conversion efficiency and high animal protein content compared with terrestrial constant-temperature livestock and poultry. Accordingly, however, fish are more susceptible to death and deterioration than terrestrial livestock. The method is characterized in that living fishes, fresh fishes, frozen fishes and other fishes which are stored and processed by various methods are sold on the market at present, after the fishes are rotten, sellers and consumers cannot easily and intuitively grasp the quality of the fishes, so that the fishes are deteriorated, and economic waste is caused;
bioimpedance is a fundamental physical parameter of biological tissue, reflecting the electrical properties of biological tissue, organs, cells or whole organisms. Bioimpedance analysis has been used for meat quality analysis as a rapid meat quality detection method. However, for fish, the biological tissues have large differences and mainly include fish scales, fish skins, fish meat, fish bones, viscera and the like from outside to inside. The impedance differences produced by different tissue morphologies are significant. The impedance distribution of the tissue has anisotropy and has an interlayer difference. The bone forms such as fish scales and fish bones generate larger impedance and smaller impedance variation compared with fish skins.
Disclosure of Invention
In view of the above, it is an object of the present invention to provide a method, system, computer device and storage medium for detecting meat deterioration in consideration of multi-layer spatio-temporal-impedance differences.
In a first aspect, a method for detecting meat quality deterioration considering multi-layer spatio-temporal-impedance differences, the method comprising:
obtaining a region to be detected of a fish body;
measuring the fish body impedance of each putrefactive area by calculating a space-impedance difference coefficient obtained by calculating the xyz space-impedance difference of each putrefactive area fish body and a time-impedance difference coefficient obtained by calculating the time-impedance difference of each putrefactive area fish body;
calculating to obtain a space-time impedance difference coefficient according to the space-impedance difference coefficient and the time-impedance difference coefficient, and reconstructing the fish body impedance of each putrefactive area according to the space-time impedance difference coefficient and the space-time impedance difference coefficient; calculating the corruption grade of each corruption area;
and calculating the integral putrefaction degree of the area to be detected of the fish body.
In the foregoing scheme, optionally, the acquiring the region to be detected of the fish body further includes:
setting the direction vertical to the muscle fiber of the fish body as a y axis;
setting the direction along the muscle fiber of the fish body as an x axis;
the thickness direction of the fish body is taken as a z axis;
for the area of the fish body to be detected, n small square areas are used for fully covering the area of the fish body to be detected and are not overlapped and equally divided, each small square area is set as a putrefaction area, and then n putrefaction areas exist: n ═ {1,2, …, n };
the four end points of each small square corruption area are provided with a flexible impedance electrode, and the end point electrodes of the whole fish body area to be detected form the front end of a mesh electrode for collecting key impedance parameters;
and similarly dividing the region and placing a flexible impedance electrode at the same position of the symmetrical plane of the region to be detected of the fish body.
In the above solution, it is further optional that the disposing of one flexible impedance electrode at each of the four end points of each small square septic zone comprises:
setting the upper left of each septic zone as (A1), the upper right as (A2), the lower left as (A3) and the lower right as (A4);
then the impedance along the fiber in the x-direction is measured by the upper left (a1) -upper right (a2), lower left (A3) -lower right (a4) double electrodes;
the impedance measured for the y-axis direction perpendicular to the fiber was measured for the top left (a1) -bottom left (A3), top right (a2) -bottom right (a4) dual electrodes.
In the foregoing solution, further optionally, the measuring the fish impedance of each putrefactive region includes:
calculate xyz space-impedance difference: setting the side length of the corruption area to be detected as L, namely the length between the working electrode and the reference electrode;
selecting one putrefaction area, and respectively measuring the impedance of two sites A1A2 and A3A4 in the x-axis direction and the impedance of two sites A1A3 and A2A4 in the y-axis direction;
the space-impedance difference calculation formula in the x direction is:
wherein z is12And z34The impedance of two sites A1A2 and A3A4 in the x-axis direction respectively;
the impedance average of the two sites; z0Contact resistance of the x-axis direction locus;
the space-impedance difference in the y direction is calculated as:
wherein z is13And Z24The impedance of two sites A1A3 and A2A4 in the y-axis direction respectively;
the impedance average of the two sites; z0Contact impedance of y-axis direction position point;
calculating the space-impedance difference in the z-axis direction: the detected thickness h of the ac excitation is frequency dependent and the frequency and depth relationship can be expressed by the following equation:
wherein m is respectively a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and an internal organ layer, ZmMeasuring impedance values of a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and an internal organ layer; h ismThe thickness of the fish scale layer, the fish skin layer, the fish meat layer, the fish bone layer and the visceral layer;
is calculated to obtain fm＝{f1,f2,f3,f4,f5The frequency corresponding to the five-layer structure for detecting the impedance of the fish body in the z-axis direction is obtained;
the space-impedance difference rule model in the z-axis direction is as follows:
s at the same timexyzThe triaxial composite space-impedance difference coefficient can be written as:
Sxyz＝(Sx，Sy，Sz) #(5)。
in the foregoing solution, further optionally, the measuring the fish body impedance of each putrefactive region further includes:
calculating the time-impedance difference:
the monitoring time of the fish body is t ═ t1,t2,…,tn}；
The time-impedance difference calculation formula in the x-axis direction is:
wherein, the
The time of two sites A1A2 and A3A4 in the x-axis directionA segment impedance; z0Is the contact resistance; l is two different sites in a certain putrefactive area on the same axis;
the time-impedance difference in the y direction is calculated as:
wherein, the
Impedance of two sites A1A3 and A2A4 in the y-axis direction at different time intervals respectively; z0Is the contact resistance.
The fish body is divided into five layers of a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and an internal organ layer on the z axis, and impedance difference in time can be generated in each layer along with the prolonging of time, so that the impedance difference of the fish skin layer, the fish meat layer and the internal organ layer is more obvious; the difference of the impedance of the fish scale layer and the fishbone layer along with the change of time is not obvious; when the z-axis time-impedance difference is calculated, the fish scale layer and the fish bone layer with inconspicuous impedance difference change are removed, and the rule is as follows:
when fm＝f1When, Tz0, (m 1), only the impedance change of the fish scale layer is measured on the z-axis, and since it is not significant, only the spatio-impedance difference exists at this time;
when fm＝f2When the temperature of the water is higher than the set temperature,
the Z-axis time-impedance difference now depends primarily on the change in the skin layer, Zt+1、ZtThe impedance of the fish skin layer in different time periods;
when f ism＝f3Or fm＝f4When the temperature of the water is higher than the set temperature,
the z-axis time-impedance difference now depends mainly on the changes of the skin layer and the fish layer,
respectively representing the impedance of the fish skin layer and the fish meat layer in different time periods;
when fm＝f5When the temperature of the water is higher than the set temperature,
at the moment, the z-axis time-impedance difference mainly depends on the changes of the fish skin layer, the fish layer and the visceral layer,
respectively the impedance of the fish skin layer, the fish meat layer and the visceral layer in different time periods;
then T under the same spacexyzThe triaxial composite time-impedance difference coefficient can be written as:
Txyz＝(Tx，Ty，Tz) #(8)
the unit spatio-temporal-impedance difference coefficient of the monitoring time period is obtained as follows:
ω(f)＝(Tx*Sx，Ty*Sy，Tz*Sz) #(9)。
in the foregoing solution, further optionally, the calculating, according to the space-impedance difference coefficient and the space-time-impedance difference coefficient, the corruption level of each corruption area includes: the impedance of any position point in each direction of the x, y and z axes of a certain corruption area is measured as follows: zx,Zy,ZzThen the final impedance of the corruption zone is:
Z(f)＝2(Tx*Sx*Zx+Ty*Sy*Zy+Tz*Sz*Zz)#(10)；
calculating to obtain final impedance Z ═ Z of each corruption area1,Z2,…,ZnSimultaneously detecting the TVB-N content of each putrefactive area of the fish body, determining an impedance threshold value according to the detected TVB-N, and inverting the impedance parameter;
and (5) levels of extreme freshness, sub-freshness, sub-rot and putrefaction are preliminarily divided into the levels of 5 levels according to the TVB-N and the impedance threshold value, wherein the levels are (level1, level2, level3, level4 and level 5).
In the foregoing scheme, further optionally, the calculating the overall putrefaction degree of the region to be tested of the fish body includes:
marking the corruption level of each corruption area, randomly selecting a corruption area level1, carrying out correlation judgment on the corruption levels of adjacent areas, and carrying out area division; the rules are as follows:
if level e (level1, level2) → reaching the Association condition
if level ∈ (level3, level4, level5) → skip
if level e (level1, level2) → reaching the Association condition
Randomly selecting a corruption area level 2:
if level e (level1, level2) → reaching the association condition
if level e (level2, level3) → reaching the association condition
if level ∈ (level3, level4, level5) → skip
Randomly selecting a corruption area level 3:
if level e (level2, level3) → reaching the association condition
Spanning the fresh and putrefactive stages: if level ∈ (level3, level4) → skip over
if level ∈ (level1, level5) → skip over
Randomly selecting a corruption area level 4:
if level ∈ (level3, level4) → skip over
if level e (level4, level5) → reaching the association condition
if level ∈ (level1, level2) → skip over
Randomly selecting a corruption area level 5:
if level e (level4, level5) → reaching the association condition
if level ∈ (level1, level2, level3) → skip
Judging the meat quality putrefaction state of the area reaching the correlation condition by using a two-parameter comparable distance P value model; the two parameters are subjected to comparable conversion, and comparable conversion formulas of the impedance and the actual measured value of TVB-N are respectively as follows:
the impedance and the comparable conversion formula of any two corruption level thresholds of TVB-N are respectively as follows:
wherein Z is0、N0Respectively, the initial values of the comparably transformed impedance and TVB-N, ZnFor each corruption level impedance threshold, ZlFor the actual measured impedance value, N, at the corruption levelnFor each corruption level TVB-N threshold, NlFor the actual measured TVB-N value, Z, at this level of spoilagen+1、ZnFor each corruption level impedance threshold, Nn+1、NnFor each corruption level TVB-N threshold, Zi、NiResults of measurements after comparable conversions; zT、NTThreshold results after comparable conversion; after transformation, the value range of each parameter under five freshness degrees is (0, 1);
by passing
the two-parameter comparable distance P value model is:
F(x)＝PR-PT
comparing F (x), if F (x) is ≧ 0, PR≥PTThe level of the corruption area after correlation is the lower level of the two areas to be correlated;
if F (x) < 0, i.e. PR＜PTAnd the level of the corruption area after correlation is the higher level of the two areas to be correlated, and the corruption area is subjected to correlation integration to realize prediction of the overall corruption state of the fish body.
In a second aspect, a meat quality deterioration detection system considering multi-layer spatio-temporal-impedance differences, the system comprising:
at least one user module, which is used for user registration and login functions and is used for system management;
at least one integrated database for storing the data result of each module;
at least one visual output display interface for visually displaying the division result of the corruption area, the fish impedance reconstruction result, the area association result and the fish corruption level result;
the system early warning module is used for carrying out system monitoring on information of each module, analyzing the information of each module according to early warning conditions preset by the system, sending an alarm to user personnel by the system when the early warning conditions are met, and processing risks by the user; if the user does not react to the early warning, the system continues to operate after marking the current early warning information, and data without problems are stored in a database in real time;
the corruption area dividing module is used for dividing the area to be detected of the fish body and installing a flexible impedance electrode; the impedance and TVB-N measuring module is used for measuring the impedance and TVB-N of each divided corruption area; the space-time impedance difference calculation module is used for calculating the fish body time-impedance difference and the space-impedance difference according to a preset model; the fish body impedance reconstruction module is used for reconstructing the impedance of each putrefactive area of the fish body by taking the calculated fish body time-impedance difference and space-impedance difference as coefficients and preliminarily judging the grade of each putrefactive area; the corruption area association module is used for carrying out association judgment on each preliminarily divided corruption area grade according to a preset association rule; and the fish body putrefaction area grade calculation module is used for performing relevance integration of putrefaction areas of the putrefaction areas reaching relevance conditions according to a preset two-parameter comparable distance P value model and predicting the overall putrefaction state of the fish body.
In a third aspect, a computer device comprises a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
obtaining a region to be detected of a fish body;
measuring the fish body impedance of each putrefactive area by calculating a space-impedance difference coefficient obtained by calculating the xyz space-impedance difference of each putrefactive area fish body and a time-impedance difference coefficient obtained by calculating the time-impedance difference of each putrefactive area fish body;
calculating to obtain a space-time impedance difference coefficient according to the space-impedance difference coefficient and the time-impedance difference coefficient, and calculating the corruption grade of each corruption area according to the space-time impedance difference coefficient;
and calculating the integral putrefaction degree of the area to be detected of the fish body.
In a fourth aspect, a computer readable storage medium having stored thereon a computer program which when executed by a processor implements the steps of:
obtaining a region to be detected of a fish body;
measuring the fish body impedance of each putrefactive area by calculating a space-impedance difference coefficient obtained by calculating the xyz space-impedance difference of each putrefactive area fish body and a time-impedance difference coefficient obtained by calculating the time-impedance difference of each putrefactive area fish body;
calculating to obtain a space-time impedance difference coefficient according to the space-impedance difference coefficient and the time-impedance difference coefficient, and calculating the corruption grade of each corruption area according to the space-time impedance difference coefficient;
and calculating the integral putrefaction degree of the area to be detected of the fish body.
The invention has at least the following beneficial effects:
the invention provides a meat quality deterioration detection method and system considering multilayer space-time impedance difference based on further analysis and research on the problems of the prior art. On one hand, the quick and nondestructive detection of the biological impedance can be realized based on the flexible impedance electrode; on the other hand, the method provided by the invention aims at the multilayer space-time impedance difference characteristic of fish impedance measurement, and can be used for reconstructing the fish impedance, so that the impedance measurement result can more accurately represent the fish putrefaction degree.
Drawings
FIG. 1 is a schematic diagram showing the application flow of a method for detecting meat quality deterioration in consideration of multi-layer spatio-temporal-impedance differences according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a three-dimensional fish body region to be measured and an electrode placement position according to an embodiment of the present invention;
FIG. 3 is a schematic view of the impedance reconstruction process for a fish putrefactive area according to an embodiment of the present invention;
FIG. 4 is a graphical illustration of the relationship between spoilage level and TVB-N content in accordance with an embodiment of the present invention;
FIG. 5 is a flow chart of fish spoilage area association integration and grade prediction according to an embodiment of the present invention
A schematic diagram;
FIG. 6 is a block diagram of a system for detecting meat spoilage of fish according to an embodiment of the present invention;
FIG. 7 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one embodiment, as shown in fig. 1, there is provided a meat quality deterioration detecting method considering multi-layer spatio-temporal-impedance differences, including the steps of:
and obtaining the area to be detected of the fish body.
Wherein, obtaining the region to be measured of the fish body comprises: setting the direction vertical to the muscle fiber of the fish body as a y axis; setting the direction along the muscle fiber of the fish body as an x axis; the thickness direction of the fish body is taken as a z axis; for the area of the fish body to be detected, n small square areas are used for fully covering the area of the fish body to be detected and are not overlapped and equally divided, each small square area is set as a putrefaction area, and then n putrefaction areas exist: n ═ {1,2, …, n }; the four end points of each small square corruption area are provided with a flexible impedance electrode, and the end point electrodes of the whole fish body area to be detected form the front end of a mesh electrode for collecting key impedance parameters; and equally dividing the region and placing flexible impedance electrodes at the same position of the symmetrical plane of the region to be detected of the fish body, and taking the average value of the time-impedance difference and the space-impedance difference measured at the same position of the region to be detected and the symmetrical plane according to the time-impedance difference and the space-impedance difference.
The arrangement of one flexible impedance electrode at each of the four end points of the small square corruption area is achieved by: setting the upper left of each septic zone as (A1), the upper right as (A2), the lower left as (A3) and the lower right as (A4); then the impedance along the fiber in the x-direction is measured by the upper left (a1) -upper right (a2), lower left (A3) -lower right (a4) double electrodes; the impedance measured for the y-axis direction perpendicular to the fiber was measured for the top left (a1) -bottom left (A3), top right (a2) -bottom right (a4) dual electrodes.
And measuring the fish body impedance of each putrefactive area by calculating a space-impedance difference coefficient obtained by calculating the xyz space-impedance difference of each putrefactive area fish body and a space-impedance difference coefficient obtained by calculating the time-impedance difference of each putrefactive area fish body. Wherein, measure each corruption district fish body impedance includes: calculating an xyz space-impedance difference, and setting the side length of the corruption area to be detected as L, namely the length between the working electrode and the reference electrode; one putrefaction area is selected, the impedance of two sites A1A2 and A3A4 in the x-axis direction and the impedance of two sites A1A3 and A2A4 in the y-axis direction are measured respectively, and the calculation formula of the space-impedance difference in the x-axis direction is as follows:
wherein Z is12And Z34The impedance of two sites A1A2 and A3A4 in the direction of the x axis respectively,
is the average of the impedances at two sites, Z0Contact resistance for the x-axis location.
The space-impedance difference in the y direction is calculated as:
wherein Z is13And Z24The impedance of two sites A1A3 and A2A4 in the y-axis direction respectively;
the impedance average of the two sites; z0Contact resistance for the y-axis location.
Calculating the space-impedance difference in the z-axis direction: the detected thickness h of the ac excitation is frequency dependent and the frequency and depth relationship can be expressed by the following equation:
wherein m is respectively a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and an internal organ layer, ZmMeasuring impedance values of a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and an internal organ layer; h ismIs the thickness of fish scale layer, fish skin layer, fish meat layer, fish bone layer and visceral layer.
Is calculated to obtain fm＝{f1,f2,f3,f4,f5And the frequency corresponds to a five-layer structure for detecting the impedance of the fish body in the z-axis direction.
The space-impedance difference rule model in the z-axis direction is as follows:
s at the same timexyzThe triaxial composite space-impedance difference coefficient can be written as: sxyz＝(Sx，Sy，Sz) # (5). Calculating the time-impedance difference:
the monitoring time of the fish body is t ═ t1,t2,…,tn}；
The time-impedance difference in the x-axis direction is calculated as:
wherein, the
Impedance of two sites A1A2 and A3A4 in the x-axis direction at different time intervals respectively; z0Is the contact resistance; l is two different sites in a putrefactive region on the same axis.
The time-impedance difference in the y direction is calculated as:
wherein, the
Impedance at two sites A1A3 and A2A4 in the y-axis direction at different time periods, Z0Is the contact resistance.
The fish body is divided into five layers of a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and an internal organ layer on the z axis, and impedance difference in time can be generated in each layer along with the prolonging of time, so that the impedance difference of the fish skin layer, the fish meat layer and the internal organ layer is more obvious; the difference of the impedance of the fish scale layer and the fishbone layer along with the change of time is not obvious; when the z-axis time-impedance difference is calculated, the fish scale layer and the fish bone layer with inconspicuous impedance difference change are removed, and the rule is as follows:
ninthly when fm＝f1When, TzWhen the z-axis is measured for only the change in impedance of the fish scale layer (m 1), only the spatio-impedance difference is present because it is not significant.
When fm＝f2When the temperature of the water is higher than the set temperature,
the Z-axis time-impedance difference now depends mainly on the change of the fish skin layer, Zt+1、ZtThe impedance of the fish skin layer at different time periods.
then T under the same spacexyzThe triaxial composite time-impedance difference coefficient can be written as:
Txyz＝(Tx，Ty，Tz)#(8)
the unit spatio-temporal-impedance difference coefficient of the monitoring time period is obtained as follows:
ω(f)＝(Tx*Sx，Ty*Sy，Tz*Sz)#(9)
and calculating the corruption grade of each corruption area according to the space-impedance difference coefficient and the space-time-impedance difference coefficient.
And calculating the integral putrefaction degree of the area to be detected of the fish body.
Calculating the corruption level of each corruption area according to the space-impedance difference coefficient and the space-time-impedance difference coefficient, wherein the calculation comprises the following steps: the impedance of any position point in each direction of x, y and z axes of a certain corruption area is measured as: zx,Zy,ZzThe resulting impedance of the septic zone is then:
Z(f)＝2(Tx*Sx*Zx+Ty*Sy*Zy+Tz*Sz*Zz)#(10)；
calculating to obtain final impedance Z ═ Z of each corruption area1,Z2,…,ZnSimultaneously detecting the TVB-N content of each putrefactive area of the fish body, determining an impedance threshold value according to the detected TVB-N, and inverting the impedance parameter;
and (5) levels of extreme freshness, sub-freshness, sub-rot and putrefaction are preliminarily divided into the levels of 5 levels according to the TVB-N and the impedance threshold value, wherein the levels are (level1, level2, level3, level4 and level 5).
The step of calculating the integral putrefaction degree of the area to be detected of the fish body comprises the following steps:
marking the corruption level of each corruption area, randomly selecting a corruption area level1, carrying out correlation judgment on the corruption levels of adjacent areas, and carrying out area division; the rules are as follows:
if level e (level1, level2) → reaching the association condition
if level ∈ (level3, level4, level5) → skip
if level e (level1, level2) → reaching the association condition
Randomly selecting a corruption area level 2:
if level e (level1, level2) → reaching the Association condition
if level e (level2, level3) → reaching the Association condition
if level e (level3, level4, level5) → skipping
Randomly selecting a corruption area level 3:
if level e (level2, level3) → reaching the association condition
Spanning the fresh and putrefactive stages: if level ∈ (level3, level4) → skip over
if level ∈ (level1, level5) → skip over
Randomly selecting a corruption area level 4:
if level ∈ (level3, level4) → skip over
if level e (level4, level5) → reaching the association condition
if level ∈ (level1, level2) → skip over
Randomly selecting a corruption area level 5:
if level e (level4, level5) → reaching the association condition
if level ∈ (level1, level2, level3) → skip
Judging the meat quality putrefaction state of the area reaching the correlation condition by using a two-parameter comparable distance P value model; the two parameters are subjected to comparable conversion, and comparable conversion formulas of the impedance and the actual measured value of TVB-N are respectively as follows:
the comparable conversion formulas of the impedance and any two corruption level thresholds of TVB-N are respectively as follows:
wherein Z is0、N0Respectively, the initial values of the comparably transformed impedance and TVB-N, ZnFor each corruption level impedance threshold, ZlFor the actual measured impedance value, N, at the corruption levelnFor each corruption level TVB-N threshold, NlFor the actual measured TVB-N value, Z, at this level of spoilagen+1、ZnFor each corruption level impedance threshold, Nn+1、NnFor each corruption level TVB-N threshold, Zi、NiResults of measurements after comparable conversions; zT、NTThreshold results after comparable conversion; after transformation, the value range of each parameter under five freshness degrees is (0, 1);
by passing
The two-parameter comparable distance P value model is:
F(x)＝PR-PT
comparing F (x), if F (x) is not less than 0, then P isR≥PTAnd the level of the correlated corruption area is the lower level of the two areas to be correlated.
If F (x) < 0, i.e. PR＜PTAnd the level of the corruption area after correlation is the higher level of the two areas to be correlated, and the corruption area is subjected to correlation integration to realize prediction of the overall corruption state of the fish body.
In one embodiment, as shown in fig. 2, the region to be measured of the fish body is first determined, the direction perpendicular to the muscle fibers is taken as the y-axis, the direction along the muscle fibers is taken as the x-axis, and the thickness direction is taken as the z-axis. For a given area, it is fully covered with n small square areas and not overlapped and equally divided, there are n corruption areas: n is {1,2, …, n }. A flexible impedance electrode is arranged at each of four end points of the square corruption area, and the end point electrodes in the whole area form the front end of a mesh electrode for collecting key impedance parameters. Particularly, as the fish body is of a symmetrical structure, the same position of the symmetrical plane of the fish body is divided into areas and flexible impedance electrodes are placed. The flexible sensing electrode can be used as the working electrode and the reference electrode.
The impedance of the fiber along the x-axis direction is measured by the upper left (A1) -upper right (A2), lower left (A3) -lower right (A4) double electrodes, and the impedance of the fiber vertical to the y-axis direction is measured by the upper left (A1) -lower left (A3), upper right (A2) -lower right (A4) double electrodes. The fish body is of a three-dimensional structure and has a certain thickness, and the structural morphology and the characteristics of the fish body are different, so that the impedance difference in the thickness direction (z axis) of the fish body is generated.
In one embodiment, as shown in fig. 3, the area to be measured is determined and the fish impedance of each putrefactive area is measured after the electrodes are placed, and the measurement process is as follows:
firstly, determining the impedance difference composition of the fish body, and analyzing to show that the fish body mainly has the difference of x, y and z axial directions, the difference of the x and y axial directions is caused by the difference of the muscle fiber directions, the difference of the z axis depends on the structure of the fish body, and the fish body mainly comprises a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and an internal organ layer from outside to inside.
The first step is as follows: and calculating an xyz space-impedance difference, and setting the side length of the corruption area to be detected as L, namely the length between the working electrode and the reference electrode. Taking a putrefactive area, the impedance of two sites A1A2 and A3A4 in the x-axis direction and the impedance of two sites A1A3 and A2A4 in the y-axis direction are measured respectively.
The space-impedance difference in the x direction is calculated as:
Z12and Z34The impedance of two sites A1A2 and A3A4 in the x-axis direction respectively;
the impedance average of the two sites; z0Contact resistance for the x-axis location.
The space-impedance difference in the y-direction is calculated as:
Z13and Z24The impedance of two sites A1A3 and A2A4 in the y-axis direction respectively;
the impedance average of the two sites; z0Contact resistance for the y-axis location.
And finally, calculating the space-impedance difference in the z-axis direction, wherein the detection thickness h of the alternating current excitation is related to the frequency, and the relationship between the frequency and the depth can be expressed by the following formula:
wherein m is respectively a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and an internal organ layer, ZmMeasuring impedance values of a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and an internal organ layer; h ismThe thickness of the fish scale layer, the fish skin layer, the fish meat layer, the fish bone layer and the visceral layer;
is calculated to obtain fm＝{f1,f2,f3,f4,f5And the frequency corresponds to a five-layer structure for detecting the impedance of the fish body in the z-axis direction.
The space-impedance difference rule model in the z-axis direction is:
then S at the same timexyzThe triaxial composite space-impedance difference coefficient can be written as:
Sxyz＝(Sx，Sy，Sz) #(5)
the second step is that: the time-impedance difference is calculated.
The fish body impedance not only has difference on the same time different position space, and to the same region, under different time periods, the change of impedance also has the difference. The time-impedance difference needs to be calculated. Let fish putrefaction time period t ═ t1,t2,…,tnAnd (5) dividing time periods according to the fish body putrefaction TVB-N putrefaction grades in the table 1.
The time-impedance difference in the x direction is calculated as:
The time-impedance difference in the y direction is calculated as:
The time-impedance difference in the z-axis direction is different, the fish body is divided into five layers of a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and a visceral layer in the z-axis direction, and the impedance difference in time can be generated in each layer along with the extension of time, but particularly, the impedance difference of the fish skin layer, the fish meat layer and the visceral layer is more obvious; the fish scale layer and the fish bone layer are formed by more stable structures and substances, and the difference of impedance changes along with time is not obvious, so that the fish scale layer and the fish bone layer with the inconspicuous impedance difference need to be removed when the z-axis time-impedance difference is calculated, and the rule is as follows:
then T under the same spacexyzThe triaxial composite time-impedance difference coefficient can be written as:
Txy＝(Tx，Ty)，fm＝f1#(8)
Txyz＝(Tx，Ty，Tz)，fm≠f1#(8)
finally, the three-axis composite space-time-impedance difference coefficient in a certain time period is obtained as follows:
ω(f)＝(Tx*Sx，Ty*Sy，Sz)，fm＝f1#(9)
ω(f)＝(Tx*Sx，Ty*Sy，Tz*Sz)，fm≠f1#(9)
finally, the impedance of any point in each direction of the x, y and z axes of a certain corruption area measured in a certain time period is as follows: zx,Zy,ZzThen the final reconstructed impedance of a corruption area in the time period is:
Z(f)＝2(Tx*Sx*Zx+Ty*Sy*Zy+Tz*Sz*Zz)#(10)
calculating to obtain a final reconstruction impedance set Z ═ Z of each corruption area1,Z2,…,ZnAnd detecting the impedance and the TVB-N content N ═ N of each putrefactive area of the fish body at the same time1,N2,…,NnAnd determining an impedance threshold according to the measured TVB-N, wherein response trends of the TVB-N and the impedance parameters to the meat quality deterioration are respectively positive response and reverse response, so that the impedance parameters are reversed, and the parameters are all positive response.
As shown in fig. 4, the TVB-N threshold preliminarily divides each corruption area level into 5 levels of extreme freshness, sub-freshness, sub-decay, corruption) (level1, level2, level3, level4, level 5); and obtaining the impedance threshold value corresponding to each corruption grade.
In one embodiment, as shown in fig. 5, the overall putrefaction degree of the region to be detected of the fish body is calculated;
firstly, the corruption level of each corruption area is marked, a corruption area level1 is randomly selected, the corruption level correlation judgment of adjacent areas is carried out, and area division is carried out. The rules are as follows:
i if level belongs to (level1, level2) → reaching the association condition
if level ∈ (level3, level4, level5) → skip
if level e (level1, level2) → reaching the association condition
Randomly selecting a corruption area level 2:
if level e (level1, level2) → reaching the association condition
if level e (level2, level3) → reaching the association condition
if level ∈ (level3, level4, level5) → skip
Randomly selecting a corruption area level 3:
if level e (level2, level3) → reaching the association condition
Spanning the fresh and putrefactive stages: if level ∈ (level3, level4) → skip over
if level ∈ (level1, level5) → skip over
Randomly selecting a corruption area level 4:
if level ∈ (level3, level4) → skip over
if level e (level4, level5) → reaching the association condition
if level e (level1, level2) → skip
Randomly selecting a corruption area level 5:
if level e (level4, level5) → reaching the association condition
if level ∈ (level1, level2, level3) → skip
And then judging the meat quality putrefaction state of the area reaching the relevant condition by using a two-parameter comparable distance P value model. The two parameters are subjected to comparable conversion, and comparable conversion formulas of the impedance and the actual measured value of TVB-N are respectively as follows:
the comparable conversion formulas of the impedance and any two corruption level thresholds of TVB-N are respectively as follows:
wherein Z0、N0Respectively, the initial values of the comparably transformed impedance and TVB-N, ZnFor each corruption level impedance threshold, ZlFor the actual measured impedance value, N, at the level of corruptionnFor each corruption level TVB-N threshold, NlFor the actual measured TVB-N value, Z, at this level of spoilagen+1、ZnFor each corruption level impedance threshold, Nn+1、NnFor each corruption level TVB-N threshold, Zi、NiAre comparable converted measurement results. ZT、NTThreshold results after comparable conversion; after transformation, the value range of each parameter under the five freshness degrees is (0, 1).
Then, calculating the corruption distance of the impedance of the area to be correlated and the actual measured value of TVB-N:
the final two-parameter comparable distance P value model is then:
F(x)＝PR-PT
comparing F (x), when F (x) is not less than 0, namely PR≥PTThe level of the corruption area after correlation is the lower level of the two areas to be correlated; when F (x) < 0, i.e., PR＜PTAnd the level of the correlated corruption area is the higher level of the two areas to be correlated, so that the correlation integration of the corruption areas is realized, and the prediction of the overall corruption state of the fish body is realized.
In one embodiment, as shown in fig. 6, a meat quality deterioration detecting system considering multi-layer spatio-temporal-impedance differences, at least one user module including user registration and login functions for management of the system;
at least one integrated database for storing the data result of each module;
at least one visual output display interface for visually displaying the division result of the corruption area, the fish impedance reconstruction result, the area association result and the fish corruption level result;
and the system early warning module is used for carrying out system monitoring on information of each module, analyzing the information of each module according to early warning conditions preset by the system, and sending an alarm to user personnel by the system when the early warning conditions are met so as to process risks by the user. If the user does not respond to the early warning, the system continues to operate after marking the current early warning information, and data without problems are stored in a database in real time;
the putrefactive region division module is used for dividing a region to be detected of the fish body and installing a flexible impedance electrode; the impedance and TVB-N measuring module is used for measuring the impedance and TVB-N of each divided corruption area; the space-time impedance difference calculation module is used for calculating the fish body time-impedance difference and the space-impedance difference according to a preset model; the fish body impedance reconstruction module is used for reconstructing the impedance of each putrefactive area of the fish body by taking the calculated fish body time-impedance difference and space-impedance difference as coefficients and preliminarily judging the grade of each putrefactive area; the corruption area association module is used for carrying out association judgment on each preliminarily divided corruption area grade according to a preset association rule; and the fish body putrefaction area grade calculation module is used for performing relevance integration of putrefaction areas of the putrefaction areas reaching relevance conditions according to a preset two-parameter comparable distance P value model and predicting the overall putrefaction state of the fish body.
For the specific definition of the meat quality deterioration detection system considering the multi-layer spatio-temporal-impedance difference, reference may be made to the above definition of the meat quality deterioration detection method considering the multi-layer spatio-temporal-impedance difference, and details thereof are not repeated herein. The various modules in the meat quality deterioration detection system considering the multi-layer spatio-temporal-impedance difference can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing meat quality deterioration detection data considering multi-layer spatio-temporal-impedance differences. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of detecting meat deterioration considering multi-layer spatio-temporal-impedance differences.
Those skilled in the art will appreciate that the architecture shown in fig. 7 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, which includes a memory and a processor, wherein the memory stores a computer program, and all or part of the procedures in the method of the above embodiment are involved.
In one embodiment, a computer-readable storage medium having a computer program stored thereon is provided, which relates to all or part of the processes of the above-described embodiment methods.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for meat quality deterioration detection considering multi-layer spatio-temporal-impedance differences, the method comprising:
obtaining a region to be detected of a fish body;
measuring the fish body impedance of each putrefactive area by calculating a space-impedance difference coefficient obtained by calculating the xyz space-impedance difference of each putrefactive area fish body and a time-impedance difference coefficient obtained by calculating the time-impedance difference of each putrefactive area fish body;
calculating to obtain a space-time impedance difference coefficient according to the space-impedance difference coefficient and the time-impedance difference coefficient, and reconstructing the fish body impedance of each putrefactive area according to the space-time impedance difference coefficient; calculating the corruption grade of each corruption area;
and calculating the integral putrefaction degree of the area to be detected of the fish body.
2. The method of claim 1, wherein the obtaining the region of the fish to be tested further comprises:
setting the direction vertical to the muscle fiber of the fish body as a y axis;
setting the direction along the muscle fiber of the fish body as an x axis;
the thickness direction of the fish body is taken as a z axis;
for the area of the fish body to be detected, n small square areas are used for fully covering the area of the fish body to be detected and are not overlapped and equally divided, each small square area is set as a corruption area, and n corruption areas are {1,2, …, n };
the four end points of each small square corruption area are provided with a flexible impedance electrode, and the end point electrodes of the whole fish body area to be detected form the front end of a mesh electrode for collecting key impedance parameters;
and similarly dividing the region and placing a flexible impedance electrode at the same position of the symmetrical plane of the region to be detected of the fish body.
3. The method of claim 2, wherein said positioning a flexible impedance electrode at each of the four ends of each of said small square septic zones comprises:
setting the upper left of each septic zone as (A1), the upper right as (A2), the lower left as (A3) and the lower right as (A4);
then the impedance along the fiber in the x-direction is measured by the upper left (a1) -upper right (a2), lower left (A3) -lower right (a4) double electrodes;
the impedance of the vertical fiber in the y-axis direction was measured by the upper left (A1) -lower left (A3), upper right (A2) -lower right (A4) two electrodes.
4. The method of claim 1, wherein said measuring fish impedance of each septic zone comprises:
calculate xyz space-impedance difference: setting the side length of the corruption area to be detected as L, namely the length between the working electrode and the reference electrode;
selecting one putrefaction area, and respectively measuring the impedance of two sites A1A2 and A3A4 in the x-axis direction and the impedance of two sites A1A3 and A2A4 in the y-axis direction;
the space-impedance difference calculation formula in the x direction is:
wherein Z is12And Z34The impedance of two sites A1A2 and A3A4 in the x-axis direction respectively;
the impedance average of the two sites; z0Contact resistance of the x-axis direction locus;
the space-impedance difference in the y direction is calculated as:
wherein Z is13And z24The impedance of two sites A1A3 and A2A4 in the y-axis direction respectively;
the impedance average of two sites; z0Contact impedance of a y-axis direction locus;
calculating the space-impedance difference in the z-axis direction: the detected thickness h of the ac excitation is frequency dependent and the frequency and depth relationship can be expressed by the following equation:
wherein m is respectively a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and an internal organ layer, ZmMeasuring impedance values of a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and an internal organ layer; h is a total ofmThe thickness of the fish scale layer, the fish skin layer, the fish meat layer, the fish bone layer and the visceral layer;
is calculated to obtain fm＝{f1,f2,f3,f4,f5The frequency corresponding to the five-layer structure for detecting the impedance of the fish body in the z-axis direction is obtained;
the space-impedance difference rule model in the z-axis direction is as follows:
s at the same timexyzThe triaxial composite space-impedance difference coefficient can be written as:
Sxyz＝(Sx，Sy，Sz)#(5)。
5. the method of claim 1, wherein measuring the fish impedance of each septic zone further comprises:
calculating the time-impedance difference:
the monitoring time of the fish body is t ═ t1,t2,…,tn}；
The time-impedance difference calculation formula in the x-axis direction is:
wherein the content of the first and second substances,
impedance of two sites A1A2 and A3A4 in the x-axis direction at different time intervals respectively; z0Is the contact resistance; l is two different sites in a putrefactive region on the same axis;
the time-impedance difference in the y direction is calculated as:
wherein the content of the first and second substances,
impedance of two sites A1A3 and A2A4 in the y-axis direction at different time intervals respectively; z is a linear or branched member0Is the contact resistance;
the fish body is divided into five layers of a fish scale layer, a fish skin layer, a fish meat layer, a fish bone layer and an internal organ layer on the z axis, and impedance difference in time can be generated in each layer along with the prolonging of time, so that the impedance difference of the fish skin layer, the fish meat layer and the internal organ layer is more obvious; the difference of the impedance of the fish scale layer and the fishbone layer along with the change of time is not obvious; when the z-axis time-impedance difference is calculated, the fish scale layer and the fish bone layer with inconspicuous impedance difference change are removed, and the rule is as follows:
when fm＝f1When, TzOnly the change in impedance of the fish scale layer is measured on the z-axis (m 1), and since it is not significant, only the spatio-impedance difference is present at this time;
when fm＝f2When the temperature of the water is higher than the set temperature,
the Z-axis time-impedance difference now depends mainly on the change of the fish skin layer, Zt+1、ZtImpedance of the fish skin layer in different time periods;
(iii) when fm＝f3Or fm＝f4When the temperature of the water is higher than the set temperature,
the z-axis time-impedance difference now depends mainly on the changes of the skin layer and the fish layer,
respectively representing the impedance of the fish skin layer and the fish meat layer in different time periods;
when fm＝f5When the temperature of the water is higher than the set temperature,
at the moment, the z-axis time-impedance difference mainly depends on the changes of the fish skin layer, the fish layer and the visceral layer,
respectively the impedance of the fish skin layer, the fish meat layer and the visceral layer in different time periods;
then T under the same spacexyzThe triaxial composite time-impedance difference coefficient can be written as:
Txyz＝(Tx，Ty，Tz)#(8)
finally, we can obtain the unit space-time-impedance difference coefficient of a certain time period as:
ω(f)＝(Tx*Sx，Ty*Sy，Tz*Sz)#(9)。
6. the method of claim 1, wherein calculating the corruption level for each corruption area based on the spatial-impedance difference coefficient and the temporal-impedance difference coefficient comprises: the impedance of any position point in each direction of x, y and z axes of a certain corruption area is measured as: zx，Zy，ZzThe ultimate impedance of the corruption area is
Z(f)＝2(Tx*Sx*Zx+Ty*Sy*Zy+Tz*Sz*Zz)#(10)；
Calculating to obtain final impedance Z ═ Z of each corruption area1，Z2，...，ZnSimultaneously detecting the TVB-N content of each putrefactive area of the fish body, determining an impedance threshold value according to the detected TVB-N, and inverting the impedance parameter;
and (5) preliminarily dividing the levels of the corruption areas into 5 levels (extreme freshness, sub-freshness, sub-decay and corruption) according to the TVB-N and the impedance threshold value, wherein the levels are (level1, level2, level3, level4 and level 5).
7. The method of claim 1, wherein the calculating the overall putrefaction degree of the fish body in the area to be tested comprises:
marking the corruption level of each corruption area, randomly selecting a corruption area level1, carrying out correlation judgment on the corruption levels of adjacent areas, and carrying out area division; the rules are as follows:
if level e (level1, level2) → reaching the association condition
if level ∈ (level3, level4, level5) → skip
if level e (level1, level2) → reaching the association condition
Randomly selecting a corruption area level 2:
if level e (level1, level2) → reaching the association condition
if level e (level2, level3) → reaching the association condition
if level ∈ (level3, level4, level5) → skip
Randomly selecting a corruption area level 3:
if level e (level2, level3) → reaching the association condition
Spanning the fresh and putrefactive stages: if level ∈ (level3, level4) → skip over
if level ∈ (level1, level5) → skip over
Randomly selecting a corruption area level 4:
if level ∈ (level3, level4) → skip over
if level e (level4, level5) → reaching the association condition
if level ∈ (level1, level2) → skip over
Randomly selecting a corruption area level 5:
if level e (level4, level5) → reaching the association condition
if level ∈ (level1, level2, level3) → skip
Judging the meat quality putrefaction state of the area reaching the correlation condition by using a two-parameter comparable distance P value model; the two parameters are subjected to comparable conversion, and comparable conversion formulas of the impedance and the actual measured value of TVB-N are respectively as follows:
the comparable conversion formulas of the impedance and any two corruption level thresholds of TVB-N are respectively as follows:
wherein Z0、N0Respectively, the initial values of the comparably transformed impedance and TVB-N, ZnFor each corruption level impedance threshold, ZlFor the actual measured impedance value, N, at the level of corruptionnFor each corruption level TVB-N threshold, NlFor the actual measured TVB-N value, Z, at this level of spoilagen+1 ZnFor each corruption level impedance threshold, Nn+1 NnFor each corruption level TVB-N threshold, Zi NiResults of measurements after comparable conversions; zT、NTThreshold results after comparable conversion; after transformation, the value range of each parameter under five freshness degrees is (0, 1);
by passing
Calculating the corruption distance of the area impedance to be correlated and the TVB-N:
the two-parameter comparable distance P value model is:
F(x)＝PR-PT
comparing F (x), if F (x) is ≧ 0, PR≥PTThe level of the corruption area after correlation is the lower level of the two areas to be correlated;
if F (x) < 0, i.e. PR＜PTAnd the level of the corruption area after correlation is the higher level of the two areas to be correlated, and the corruption area is subjected to correlation integration to realize prediction of the overall corruption state of the fish body.
8. A meat quality deterioration detection system considering multi-layer spatio-temporal-impedance differences, the system comprising:
at least one user module, which is used for user registration and login functions and is used for system management;
at least one integrated database for storing data of each module;
the visual output display interface is used for visually displaying the corruption region division data, the fish body impedance reconstruction data, the region association data and the fish body corruption grade data;
the system early warning module is used for carrying out system monitoring on the information of each module, analyzing the information of each module according to early warning conditions preset by the system and sending an alarm to a user by the system when the early warning conditions are met; if the user does not react to the early warning, the system continues to operate after marking the current early warning information, and data without problems are stored in a database in real time;
the corruption area dividing module is used for dividing the area to be detected of the fish body and installing a flexible impedance electrode; the impedance and TVB-N measuring module is used for measuring the impedance and TVB-N of each divided corruption area; the space-time impedance difference calculation module is used for calculating the fish body time-impedance difference and the space-impedance difference according to a preset model; the fish body impedance reconstruction module is used for reconstructing the impedance of each putrefactive area of the fish body by taking the calculated fish body time-impedance difference and space-impedance difference as coefficients and preliminarily judging the grade of each putrefactive area; the corruption area association module is used for carrying out association judgment on each preliminarily divided corruption area grade according to a preset association rule; and the fish body putrefaction area grade calculation module is used for performing relevance integration of putrefaction areas of the putrefaction areas reaching relevance conditions according to a preset two-parameter comparable distance P value model and predicting the overall putrefaction state of the fish body.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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| CN202210346126.9A CN114705727A (en) | 2022-04-02 | 2022-04-02 | Meat quality corruption detection method considering multilayer space-time impedance difference |
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| JP2006030083A (en) * | 2004-07-20 | 2006-02-02 | Aska Corp | Decision system of meat quality of fish |
| WO2006070169A1 (en) * | 2004-12-23 | 2006-07-06 | Institut National De La Recherche Agronomique | Multi-electrode sensor for measuring the electric anisotropy of a biological material and the use of said sensor |
| US20060292550A1 (en) * | 2005-06-24 | 2006-12-28 | Cox Marlin K | Method for determining fish composition using bioelectrical impedance analysis |
| CN105372299A (en) * | 2015-12-01 | 2016-03-02 | 南京农业大学 | Rapid method for determination of pork freshness |
| CN111861132A (en) * | 2020-06-24 | 2020-10-30 | 浙江海洋大学 | Fish analysis system |
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| JP2006030083A (en) * | 2004-07-20 | 2006-02-02 | Aska Corp | Decision system of meat quality of fish |
| WO2006070169A1 (en) * | 2004-12-23 | 2006-07-06 | Institut National De La Recherche Agronomique | Multi-electrode sensor for measuring the electric anisotropy of a biological material and the use of said sensor |
| US20060292550A1 (en) * | 2005-06-24 | 2006-12-28 | Cox Marlin K | Method for determining fish composition using bioelectrical impedance analysis |
| CN105372299A (en) * | 2015-12-01 | 2016-03-02 | 南京农业大学 | Rapid method for determination of pork freshness |
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