Meat adulteration ratio detection system based on metalloporphyrin probe

Abstract

The invention discloses a meat adulteration ratio detection system based on a metalloporphyrin probe, relates to the technical field of meat detection, and solves the technical problems that the existing meat adulteration ratio is difficult to detect and the detection precision is relatively low. Comprising a central processing module, and a sample acquisition module, a data acquisition module and a user module which are connected with the central processing module, the central processing module obtains meat types needing to be detected through the user module, identifies and obtains sample information, and generates a reliability coefficient corresponding to each piece of sample information based on the sample information; calculating an adulteration ratio based on the sampling information, the type ratio corresponding to each sample and the reliability coefficient; according to the method, the samples with large particles are discarded, the reliability of the adulteration proportion of the samples is evaluated, and the reliability evaluation result is introduced into the solving process of the adulteration proportion, so that the accuracy of the adulteration proportion obtained through subsequent calculation is improved.

Description

Technical Field

[0001] The invention belongs to the field of meat detection and relates to meat detection technology, in particular to a meat adulteration ratio detection system based on metalloporphyrin probes. Background Art

[0002] Due to the continuous expansion of the meat market and the increase in consumer demand for meat products, some businesses have adulterated meat products, seriously damaging the interests and health of consumers; therefore, it is necessary to conduct meat adulteration testing to ensure the quality and safety of meat products and safeguard the legitimate rights and interests of consumers.

[0003] Existing meat adulteration detection mainly uses scientific and technological means to detect and analyze meat products to determine whether they contain adulterants, such as microscopic inspection, chromatographic analysis, spectral analysis, DNA testing, etc. These methods can detect whether meat products are adulterated and the information of adulterants. However, most detection methods are limited to detecting the types of adulterants and generally cannot accurately determine the proportion of adulterants, which makes it difficult to help consumers obtain corresponding rights and interests. Therefore, a detection system that can detect the proportion of meat adulteration is needed. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a meat adulteration ratio detection system based on metal porphyrin probes, which is used to solve the technical problem that it is difficult to accurately obtain the adulteration ratio of adulterated meat in the prior art. The present invention solves the above-mentioned problem by setting a sampling position for the detection sample and taking the sample information of the obtained sample into consideration in the process of obtaining the adulteration ratio.

[0005] To achieve the above-mentioned object, the first aspect of the present invention provides a meat adulteration ratio detection system based on metalloporphyrin probes, comprising a central processing module, and a data acquisition module and a database connected thereto;

[0006] Data acquisition module: Scan the sample through the sample acquisition device connected to it to obtain scanning information; match the probe information from the database based on the meat label corresponding to the test sample;

[0007] Central processing module: divide the detection samples into several detection areas based on the scanning information, and set sampling information for the several detection areas; wherein the sampling information includes sampling position and sampling depth; and,

[0008] Based on the sampling information and the probe information, the corresponding probe is selected to sample and test the test sample to obtain some test information; the reliability coefficient of the corresponding sample is calculated based on the sample information, and the adulteration ratio of the test sample is calculated in combination with the adulteration ratio; wherein the test information includes the sample information and the adulteration ratio.

[0009] Preferably, the central processing module is in communication and / or electrically connected with the sample acquisition module, the data acquisition module and the user module.

[0010] Preferably, the method of dividing the detection sample based on the scanning information to obtain a number of detection areas includes:

[0011] A three-dimensional model of the test sample is established according to the scanning information, a thickness difference threshold is set, a position of the test sample is set as the starting point of the divided area, other inspection points are evenly set within a fixed distance range around the starting point, and whether the difference between the thickness of the test sample at the inspection point and the thickness of the test sample at the starting point is within the thickness difference threshold;

[0012] If yes, the inspection point and the starting point are divided into the same area, and the inspection point is used as the starting point to determine whether the difference between the thickness of the test sample at other inspection points set within a fixed distance range around the starting point and the thickness of the test sample at the starting point is within the thickness difference threshold;

[0013] If not, the inspection point and the starting point are divided into different areas, and the inspection point is used as the starting point to determine whether the difference between the thickness of the detection samples at other inspection points within a fixed distance range around the starting point and the thickness of the detection samples at the starting point is within the thickness difference threshold.

[0014] Preferably, the setting of sampling information for a plurality of detection areas includes:

[0015] Analyze the three-dimensional model of each area to obtain the central position of each area, and set this position as the sampling position;

[0016] The sample detection thickness at the sampling position is obtained, and half of the detection sample thickness value at the sampling position is set as the sampling depth.

[0017] Preferably, the calculating of the reliability coefficient of the corresponding sample based on the sample information includes:

[0018] Identify the distribution of sample particle size in the sample information, set a variance threshold, calculate the actual variance of the sample particle size, and determine whether the actual variance is less than the variance threshold; wherein the sample particle size is the particle size of the meat of the sample;

[0019] If not, the sample information of the sample is discarded;

[0020] If yes, the sample information of the sample is retained, the average particle size of the sample is calculated and marked as KL;

[0021] The reliability coefficient KP of the sample is calculated using the formula KP=exp(-KL).

[0022] The present invention discards samples with a large variance in sample particle size, that is, discards samples with uneven meat particle size, and calculates samples with relatively uniform sample particle size, so that the reliability coefficient KP obtained by calculation is more accurate, thereby increasing the accuracy of the adulteration ratio obtained by subsequent calculation.

[0023] Preferably, the adulterated proportion is obtained through a database by obtaining the test results of the metal porphyrin probe corresponding to the tested meat type, querying the database for the meat proportion corresponding to the test results of the corresponding metal porphyrin probe, and outputting the meat proportion as the adulterated proportion.

[0024] Preferably, the database is obtained through several groups of experimental data, which include using experimental meats of different types and different meat ratios, detecting the experimental meats using metalloporphyrin probes corresponding to the experimental meats, recording the detection results, establishing a relationship between the detection results and different types of experimental meats and meat ratios, and thereby establishing a database.

[0025] Preferably, the method of calculating the adulteration ratio of the test sample in combination with the adulterated ratio includes:

[0026] Each sample is labeled as i, the thickness of the sample detected at each sampling position is obtained as HDi, the reliability coefficient KPi corresponding to this sampling position is obtained, and the weight coefficient Bli of this sampling position is calculated by the formula BLi=HDi×KPi / ∑(HDi×KPi);

[0027] The proportion of adulterated meat at the sampling location is obtained and marked as JCi. The adulteration proportion CB of the test sample is calculated by the formula CB=1-∑(JCi×BLi), where 0≤i≤n, n is the number of samples that have not been discarded, and i is the label of the sample.

[0028] The present invention indirectly obtains the total adulteration ratio by obtaining the ratio of the types of meat to be tested, thereby saving the step of obtaining the adulteration ratio and eliminating the need to obtain the corresponding adulteration ratios of the adulterated meats one by one.

[0029] The thickness HDi in the present invention can be the average thickness of the detection area corresponding to the sampling position, which further increases the accuracy of the adulteration ratio. At the same time, the present invention indirectly obtains the adulteration ratio of adulterated meat by detecting the ratio of the detected meat, so that the adulteration ratio can be obtained by only detecting the detected meat, which simplifies the steps of obtaining the adulteration ratio.

[0030] It is worth noting that the present invention infers the adulteration ratio by detecting the ratio of meat. If one wants to know where the adulterated meat comes from, the metal porphyrin probe corresponding to the adulterated meat can be used for detection. The single adulteration ratio of a single adulterated meat can be calculated by the formula BLi=∑(JCi×BLi). The adulteration ratios of all adulterated meats are summed up to obtain the total adulteration ratio, and the type of adulterated meat can also be determined.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. The present invention discards samples with larger particles, conducts reliability assessment on the adulteration ratio of the samples, and introduces the reliability assessment results into the process of solving the adulteration ratio, thereby increasing the accuracy of the adulteration ratio calculated subsequently. At the same time, by using the corresponding metal porphyrin probes for different types of tested meat, the accuracy of detection is increased, thereby increasing the accuracy of the adulteration ratio.

[0033] 2. The present invention reversely estimates the adulteration ratio by detecting the ratio of meat, thus saving the step of obtaining the adulteration ratio. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 It is a schematic diagram of the principle of the present invention;

[0036] Figure 2 It is a diagram of the method steps of the present invention. DETAILED DESCRIPTION

[0037] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Example 1

[0039] See also Figure 1-Figure 2 , the first aspect of the present invention provides a meat adulteration ratio detection system based on metalloporphyrin probes, comprising a central processing module, and a data acquisition module and a database connected thereto;

[0040] Data acquisition module: Scan the sample through the sample acquisition device connected to it to obtain scanning information; match the probe information from the database based on the meat label corresponding to the test sample;

[0041] Central processing module: divide the detection samples into several detection areas based on the scanning information, and set sampling information for the several detection areas; wherein the sampling information includes sampling position and sampling depth; and,

[0042] Based on the sampling information and the probe information, the corresponding probe is selected to sample and test the test sample to obtain some test information; the reliability coefficient of the corresponding sample is calculated based on the sample information, and the adulteration ratio of the test sample is calculated in combination with the adulteration ratio; wherein the test information includes the sample information and the adulteration ratio.

[0043] The method of dividing the detection sample based on the scanning information to obtain a number of detection areas includes:

[0044] A three-dimensional model of the test sample is established according to the scanning information, a thickness difference threshold is set, a position of the test sample is set as the starting point of the divided area, other inspection points are evenly set within a fixed distance range around the starting point, and whether the difference between the thickness of the test sample at the inspection point and the thickness of the test sample at the starting point is within the thickness difference threshold;

[0045] If yes, the inspection point and the starting point are divided into the same area, and the inspection point is used as the starting point to determine whether the difference between the thickness of the test sample at other inspection points set within a fixed distance range around the starting point and the thickness of the test sample at the starting point is within the thickness difference threshold;

[0046] If not, the inspection point and the starting point are divided into different areas, and the inspection point is used as the starting point to determine whether the difference between the thickness of the detection samples at other inspection points within a fixed distance range around the starting point and the thickness of the detection samples at the starting point is within the thickness difference threshold.

[0047] According to the characteristics of the total test samples, the total test samples are divided into several test areas, and sampling is performed at set positions or randomly in the corresponding test areas, ensuring the richness of the collected samples. This makes the sample data obtained by collecting samples close to the actual data of the total test samples, thereby increasing the credibility of the test results.

[0048] The step of setting sampling information for a plurality of detection areas includes:

[0049] Analyze the three-dimensional model of each area to obtain the central position of each area, and set this position as the sampling position;

[0050] The sample detection thickness at the sampling position is obtained, and half of the detection sample thickness value at the sampling position is set as the sampling depth.

[0051] The reliability coefficient of the corresponding sample is calculated based on the sample information, including:

[0052] Identify the distribution of sample particle size in the sample information, set a variance threshold, calculate the actual variance of the sample particle size, and determine whether the actual variance is less than the variance threshold; wherein the sample particle size is the particle size of the meat of the sample;

[0053] If not, the sample information of the sample is discarded;

[0054] If yes, the sample information of the sample is retained, the average particle size of the sample is calculated and marked as KL;

[0055] The reliability coefficient KP of the sample is calculated using the formula KP=exp(-KL).

[0056] The present invention discards samples with a large variance in sample particle size, that is, discards samples with uneven meat particle size, and calculates samples with relatively uniform sample particle size, so that the reliability coefficient KP obtained by calculation is more accurate, thereby increasing the accuracy of the adulteration ratio obtained by subsequent calculation.

[0057] The adulterated proportion is obtained through the database by obtaining the detection results of the metal porphyrin probes corresponding to the detected meat types, searching the database for the meat proportion corresponding to the detection results of the corresponding metal porphyrin probes, and outputting the meat proportion as the adulterated proportion.

[0058] The database is obtained through several groups of experimental data, which include using experimental meat of different types and different meat proportions, detecting the experimental meat using metal porphyrin probes corresponding to the experimental meat, recording the detection results, establishing a relationship between the detection results and different types of experimental meat and meat proportions, and thus establishing a database.

[0059] The data in the database are obtained through a large number of experiments, that is, the corresponding data in the database are extremely accurate. The test results of the samples are obtained through the historical database, making the test results more convincing.

[0060] The adulteration ratio of the test sample is calculated in combination with the adulterated ratio, including:

[0061] Each sample is labeled as i, the thickness of the sample detected at each sampling position is obtained as HDi, the reliability coefficient KPi corresponding to this sampling position is obtained, and the weight coefficient Bli of this sampling position is calculated by the formula BLi=HDi×KPi / ∑(HDi×KPi);

[0062] The proportion of adulterated meat at the sampling location is obtained and marked as JCi. The adulteration proportion CB of the test sample is calculated by the formula CB=1-∑(JCi×BLi), where 0≤i≤n, n is the number of samples that have not been discarded, and i is the label of the sample.

[0063] The present invention indirectly obtains the total adulteration ratio by obtaining the ratio of the types of meat to be tested, thereby saving the step of obtaining the adulteration ratio and eliminating the need to obtain the corresponding adulteration ratios of the adulterated meats one by one.

[0064] The thickness HDi in the present invention can be the average thickness of the detection area corresponding to the sampling position, which further increases the accuracy of the adulteration ratio. At the same time, the present invention indirectly obtains the adulteration ratio of adulterated meat by detecting the ratio of the detected meat, so that the adulteration ratio can be obtained by only detecting the detected meat, which simplifies the steps of obtaining the adulteration ratio.

[0065] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0066] Working principle of the present invention:

[0067] The tester inputs the type of meat to be tested of the sample to be tested through the user control module, and obtains the metal porphyrin probe corresponding to the corresponding type of meat to be tested; at the same time, the sample collection module samples the total test sample according to the sampling information to obtain several samples, and uses the corresponding metal porphyrin probe to test each sample, and obtains the proportion of the tested meat in each sample through the test results, and then calculates the proportion of the tested meat with a higher accuracy by comprehensively considering the thickness of the total test sample at the sampling position and the evaluation description related to the sample particle size, and indirectly obtains the adulteration ratio of the total test sample. The present invention discards samples with larger particles, conducts reliability evaluation on the adulteration ratio of the samples, and introduces the reliability evaluation results into the process of solving the adulteration ratio, thereby increasing the accuracy of the adulteration ratio calculated subsequently, and at the same time, by using the corresponding metal porphyrin probes for different types of tested meat, the accuracy of the detection is increased, thereby increasing the accuracy of the adulteration ratio.

[0068] Example 2

[0069] In this embodiment, the total detection samples are divided into four detection areas, and one sample is obtained from each detection area, including sample one, sample two, sample three, and sample four;

[0070] Set the variance threshold to 0.2 mm 2 ;

[0071] The sample information of sample 1 records the average particle size KL=1mm, and the variance of the particle size of sample 1 is 0.1mm. 2 , the actual variance is less than the variance threshold, that is, sample one is retained, the thickness of the sampling position of sample one is HD1 = 10 mm, the test result of sample one is the tested meat ratio JC1 = 0.80, and the reliability coefficient of sample one is calculated by the formula KP = exp(-KL), that is, KP1 = 0.368;

[0072] The sample information of sample 2 records the average particle size KL = 0.9 mm, and the variance of the particle size of sample 2 is 0.16 mm. 2 , the actual variance is less than the variance threshold, that is, sample 2 is retained, the thickness of the sampling position of sample 2 is HD2 = 8 mm, the test result of sample 2 is the tested meat ratio JC2 = 0.82, and the reliability coefficient of sample 2 is calculated by the formula KP = exp(-KL) KP = 0.407, that is, KP2 = 0.407;

[0073] The sample information of sample 3 records that the variance of the sample particle size of sample 3 is 0.3 mm. 2 , the actual variance is greater than the variance threshold, that is, sample three is discarded;

[0074] The average particle size KL recorded in the sample information of sample 4 is 1.5 mm, and the variance of the particle size of sample 4 is 0.08 mm. 2 , the actual variance is less than the variance threshold, that is, sample 4 is retained, the thickness of the sampling position of sample 4 is HD3 = 12 mm, and the test result of sample 2 is the tested meat ratio JC3 = 0.76. The reliability coefficient of sample 2 is calculated by the formula KP = exp(-KL) KP≈0.223, that is, KP3 = 0.223;

[0075] The proportional coefficient of sample 1 is calculated by the formula BLi = HDi × KPi / ∑ (HDi × KPi) as BL1≈0.383; the proportional coefficient of sample 2 is BL2≈0.339; the proportional coefficient of sample 4 is BL3≈0.278;

[0076] The adulteration ratio of the total tested samples, CB≈0.204, was calculated using the formula CB=1-∑(JCi×BLi); that is, the adulterated meat in the total tested samples accounted for approximately 20.4% of the total tested samples.

[0077] Example 3

[0078] The present invention can also use the method in Example 1 to obtain the single adulteration ratio of various adulterated meats in the total test sample, and then obtain the total adulteration ratio by summing the single adulteration ratios. Specifically, the proportion coefficient BLi of each sample type and the proportion JCi of the tested meat are obtained by Example 1, and the proportion of a single adulterated meat is obtained by the formula BLi=∑(JCi×BLi). Then, the adulteration ratios of all adulterated meats are summed to obtain the total adulteration ratio, and the type of adulterated meat can also be determined.

[0079] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A meat adulteration ratio detection system based on metalloporphyrin probes, including a central processing module, and a data acquisition module and database connected thereto; Features: Data acquisition module: Scans the test sample based on the sample acquisition device connected to it to obtain scanning information; obtains probe information from the database based on the meat label corresponding to the test sample; Central processing module: divide the detection samples based on the scanning information to obtain a number of detection areas, and set sampling information for the several detection areas; wherein the sampling information includes a sampling position and a sampling depth; and, Based on the sampling information and the probe information, the data acquisition module is controlled to sample the test sample to obtain a number of test information; the reliability coefficient of the corresponding sample is calculated based on the sample information, and the adulteration ratio of the test sample is calculated in combination with the adulterated ratio; wherein the test information includes the sample information and the adulterated ratio.

2. The meat adulteration ratio detection system based on metalloporphyrin probes according to claim 1, It is characterized in that The method of dividing the detection sample based on the scanning information to obtain a number of detection areas includes: A three-dimensional model of the test sample is established according to the scanning information, a thickness difference threshold is set, a position of the test sample is set as the starting point of the divided area, and other inspection points are evenly set within a fixed distance range around the starting point to check whether the difference between the thickness of the test sample at the inspection point and the thickness of the test sample at the corresponding position of the starting point is within the thickness difference threshold; If yes, the inspection point and the starting point are divided into the same area, and the inspection point is used as the starting point to determine whether the difference between the thickness of the test sample at other inspection points set within a fixed distance range around the starting point and the thickness of the test sample at the corresponding position of the starting point is within the thickness difference threshold; If not, the inspection point and the starting point are divided into different areas, and the inspection point is used as the starting point to determine whether the difference between the thickness of the detection samples at other inspection points set within a fixed distance range around the starting point and the thickness of the detection samples at the corresponding position of the starting point is within the thickness difference threshold.

3. The meat adulteration ratio detection system based on metalloporphyrin probes according to claim 1, It is characterized in that The step of setting sampling information for a plurality of detection areas includes: Analyze the three-dimensional model of each area to obtain the central position of each area, and set this position as the sampling position; The sample detection thickness at the sampling position is obtained, and half of the detection sample thickness value at the sampling position is set as the sampling depth.

4. The meat adulteration ratio detection system based on metalloporphyrin probes according to claim 1, It is characterized in that The calculating the reliability coefficient of the corresponding sample based on the sample information includes: Identify the distribution of sample particle size in the sample information, set a variance threshold, calculate the actual variance of the sample particle size, and determine whether the actual variance is less than the variance threshold; wherein the sample particle size is the particle size of the meat of the sample; If not, the sample information of the sample is discarded; If yes, the sample information of the sample is retained, the average particle size of the sample is calculated and marked as KL; The reliability coefficient KP of the sample is calculated using the formula KP=exp(-KL).

5. The meat adulteration ratio detection system based on metalloporphyrin probes according to claim 1, It is characterized in that The adulterated proportion is obtained through the database by obtaining the detection results of the metal porphyrin probes corresponding to the detected meat types, querying the database for the meat proportion corresponding to the detection results of the corresponding metal porphyrin probes, and using the meat proportion as the adulterated proportion.

6. The meat adulteration ratio detection system based on metalloporphyrin probes according to claim 1, It is characterized in that The database is obtained through several groups of experimental data, which include using experimental meat of different types and different meat ratios, detecting the experimental meat using metal porphyrin probes corresponding to the experimental meat, recording the detection results, establishing a relationship between the detection results and different types of experimental meat and meat ratios, and thus establishing a database.

7. The meat adulteration ratio detection system based on metalloporphyrin probes according to claim 4, It is characterized in that The method of calculating the adulteration ratio of the test sample in combination with the adulterated ratio includes: Each sample is labeled as i, the thickness of the sample detected at each sampling position is obtained as HDi, the reliability coefficient KPi corresponding to this sampling position is obtained, and the weight coefficient Bli of this sampling position is calculated by the formula BLi=HDi×KPi / ∑(HDi×KPi); The proportion of adulterated meat at the sampling location is obtained and marked as JCi. The adulteration proportion CB of the test sample is calculated by the formula CB=1-∑(JCi×BLi), where 0≤i≤n, n is the number of samples that have not been discarded, and i is the label of the sample.

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