CN112766739B - Method for evaluating heavy metal pollution in meat product based on BWM-E model - Google Patents
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- 239000011651 chromium Substances 0.000 description 6
- VYZAMTAEIAYCRO-UHFFFAOYSA-N Chromium Chemical compound [Cr] VYZAMTAEIAYCRO-UHFFFAOYSA-N 0.000 description 5
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- 229910052804 chromium Inorganic materials 0.000 description 5
- 239000003344 environmental pollutant Substances 0.000 description 4
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Abstract
The invention provides a method for evaluating heavy metal pollution in meat products based on a BWM-E model. The method comprises the steps of firstly, fusing and preprocessing data, and determining an index capable of reflecting the heavy metal pollution degree in meat products from the data; comprehensively evaluating the heavy metal pollution condition in the meat products by combining the determined multi-attribute evaluation indexes by utilizing an optimal worst method to obtain heavy metal pollution indexes of various meat products; and finally, evaluating the heavy metal pollution conditions in the meat products in different areas by using an entropy method on the basis to obtain the heavy metal pollution indexes of the meat products in each area. The method integrates multiple attribute indexes, can comprehensively and objectively reflect the heavy metal pollution conditions of various meat products and meat products in different areas, highlights areas with abnormal heavy metal pollution in the meat products, and can effectively highlight the difference of the heavy metal pollution degree of the meat products in different areas.
Description
Technical Field
The invention belongs to the field of food safety risk evaluation, and particularly relates to a comprehensive evaluation method for heavy metal pollution in meat products based on a BWM-E model.
Background
Animal foods such as livestock and poultry meat are a main source of high-quality protein and micronutrients. Along with the improvement of the living standard of residents in China, the consumption of meat products is continuously increased, and the heavy metals contained in the meat products can cause various damages to the health of human bodies. Heavy metals in food mainly originate from soil, industrial three wastes, food processing and packaging and other approaches, and the pollutants enter a human body to be accumulated in certain organs through the enrichment function of a food chain so as to cause chronic poisoning. The detection of heavy metals and the evaluation of pollution levels in meat products are already an important part of the risk monitoring work of food pollution harmful factors. However, how to comprehensively and quantitatively evaluate the heavy metal pollution degree in various meat products and meat products in different areas according to the obtained detection results is still a problem to be solved.
The current comprehensive evaluation method for the heavy metal pollution degree in food is mainly divided into two types: one is to use an internal Mei Luo index method, which firstly obtains the index of each heavy metal (single pollution index), then obtains the average value of each index, and calculates the pollution degree of the heavy metal in the food by taking the maximum index and the average value. And the other is to adopt a single attribute evaluation method, and obtain the total exceeding rate of the heavy metals in the food by counting the information such as the detection frequency, the exceeding frequency and the like of the heavy metals in the food, thereby comprehensively evaluating the pollution degree of the heavy metals in the food. However, when the pollution degree of heavy metals in food is evaluated by adopting an internal Mei Luo index method and an exceeding rate, the attributes such as heavy metal toxicity and the like are ignored, and the pollution degree of heavy metals in food cannot be comprehensively reflected. The same sampling area can detect multiple kinds of foods, and the current method is used for evaluating the heavy metal pollution degree in each area of foods, so that when the spatial distribution of the heavy metal pollution in the foods is further found, the influence of the abnormal detection condition on the foods used for analyzing the difference of the heavy metal pollution degree of each area of foods and the sampling area with the abnormal heavy metal pollution condition cannot be highlighted.
Disclosure of Invention
Aiming at the defects of the existing evaluation Method, the comprehensive evaluation Method for heavy metal pollution in meat products based on BWM-E is provided based on an optimal Worst Method (Best-world Method) and an entropy Method (Entry), and various attributes can be integrated, so that comprehensive evaluation can be performed on heavy metal pollution conditions of various meat products and different areas respectively.
The technical scheme provided by the invention is as follows:
a comprehensive evaluation method for heavy metal pollution in meat products based on BWM-E model. Firstly, fusing and preprocessing various data, and determining an evaluation index capable of reflecting the heavy metal pollution degree in the meat product; secondly, comprehensively evaluating the heavy metal pollution degree in the meat products by utilizing an optimal worst method and combining the selected multi-attribute evaluation indexes to obtain heavy metal pollution indexes of various meat products; and finally, evaluating the heavy metal pollution degree in the meat products in different areas by using an entropy method on the basis to obtain the heavy metal pollution indexes in the meat products in different areas. The method integrates multiple attribute indexes, can comprehensively and objectively reflect the heavy metal pollution condition of the meat product, and can effectively highlight the difference of the heavy metal pollution degree of the meat product in different areas. The method comprises the following specific steps:
A. and integrating the heavy metal detection result data sets in the meat products in different areas with a limit standard data set to obtain an original data set of heavy metal pollution in the meat products in different areas, wherein the limit standard adopts the limit of pollutants in food safety national standard foods (GB 2762-2017). Determining an evaluation index for comprehensively evaluating heavy metal pollution in meat products according to the detection result and the limit standard; according to the determined evaluation indexes, counting the detection conditions (such as detection rate) of each evaluation index in various meat products in different areas to obtain an evaluation index value matrix I= (I) for evaluating heavy metal pollution of various meat products 1 ,I 2 ,..I n ) T Wherein I i An evaluation index value of the i-th meat product is represented, and n represents the number of meat product types.
B. And C, carrying out hierarchical division on the evaluation index set according to the attribute of the evaluation index set determined in the step A, and calculating the weight of the evaluation index layer by using an optimal worst method to finally obtain a weight vector W' = (W) of each evaluation index 1 ,w 2 ,…,w n )；
C. And B, carrying out weighted summation on the weight vector W ' obtained in the step B and the index value corresponding to the weight vector W ' to obtain a heavy metal pollution index set M ' of various meat products in different areas, wherein the formula is as follows:
M′＝IW′ T (1)
Heavy metal pollution index set M' = (M) of various meat products 1 ,M 2 ,…,M i ,…M n ) Wherein M is i The heavy metal pollution index of the i-th meat product is represented, and n is the number of meat product categories;
D. calculating the heavy metal pollution indexes of different types of meat products in different areas according to the steps A-C; taking the heavy metal pollution indexes of various meat products as evaluation indexes, and taking the heavy metal pollution indexes of various meat products as evaluation index values for comprehensively evaluating the heavy metal pollution in different areas to obtain an evaluation matrix;
E. comparing the change conditions of heavy metal pollution indexes of various meat products in different areas by using an entropy method, and determining the importance degree, namely index weight, of the meat products for evaluating the heavy metal pollution degree in the areas; and D, weighting and summing the index weight and the evaluation index value in the step D to obtain the heavy metal comprehensive pollution index of the meat products in each region.
Aiming at the comprehensive evaluation method of heavy metal pollution in the meat product based on the BWM-E model, the specific calculation process in the step B is as follows:
B1. b, dividing the evaluation indexes into layers according to the properties of the evaluation indexes selected in the step A, so that the indexes are uniformly distributed on each layer, and the number of the indexes of each layer is 9 at most in order to reduce errors; and determining the optimal index and the worst index in each layer of index set. The optimal index is the index with the largest toxicity, the worst index is the index with the smallest toxicity, and if a plurality of groups of optimal worst indexes exist, one group is selected;
B2. for each layer of indexes, adopting a 1-9 scale method, and comparing the optimal indexes of the layer with the importance degrees of all indexes of the layer in pairs to obtain a comparison vector A B ＝(a B1 ,a B2 ,…,a Bn ) Simultaneously, all indexes of the layer are compared with the importance degree of the worst indexes in pairs to obtain a comparison vector A W ＝(a 1W ,a 2W ,…,a nW ) Wherein a is Bi A represents the ratio of the importance of the optimal index B to the index i iW The ratio of the importance of index i to the worst index W; n represents the index number of the layer;
B3. each layer of indexes obtains a group of comparison vectors A B 、A W Setting the optimal weight set as { w } 1 ,w 2 ,…,w n Weight w for optimal index B Weights w of all indexes of the same layer i The ratio of a to a Bi As consistent as possible. Weights w of all indexes of the same layer i And the worst index weight w w The ratio of a to a iW As consistent as possible. Meanwhile, each index weight should meet non-negative, and the sum of all index weights is 1. Thereby, the optimization problem can be converted as shown in the formula (2), the comparison vector corresponding to the index of the k layer is brought into the following formula,
obtaining the index weight vector W of the layer k ＝(w 1 ,w 2 ,…,w i ,…,w n ) With xi k ,W k The component w of (2) i Represents the ith index weight of the kth layer, and xi k For calculating the consistency ratio corresponding to the comparison vector of the k-layer index as CR value, when CR<At 0.1, the set of comparison vectors satisfies the consistency check, and their corresponding weight vectors W can be used for subsequent analysis, otherwise the comparison vectors need to be adjusted.
B4. The evaluation index weight matrix W is calculated by the following formula.
W＝W n T W n-1 …W 1 (3)
W in the formula n Representing the n-th layer index weight vector. To facilitate the calculation of the subsequent step, the evaluation index weight matrix W is sorted into an evaluation index weight vector W'.
Aiming at the comprehensive evaluation method of heavy metal pollution in the meat product based on the BWM-E model, further, the step D obtains an evaluation matrix according to the calculation results from the step A to the step C, wherein the evaluation matrix is as follows:
wherein R is i Refers to the i-th sampling area for evaluation; x is x ij Is indicated at R i Heavy metal pollution index of the j-th meat product in the sampling area; m refers to the number of sampling areas; n refers to the number of the sampled meat products in the sampling area, namely the number of the meat products for comprehensively evaluating the heavy metal pollution degree in the sampling area.
Aiming at the comprehensive evaluation method of the heavy metal pollution of the meat product based on the BWM-E model, the specific calculation process of the step E is as follows:
E1. according to the change condition of heavy metal pollution indexes of various meat products in different areas, calculating the information contribution degree of the various meat products when the various meat products are used as comprehensive evaluation indexes for the heavy metal pollution degrees in different areas, wherein the calculation formula is as follows:
wherein r is ij Indicating that the j-th evaluation index is used for the region R i And carrying out contribution degree of comprehensive evaluation.
E2. And calculating the weight of each evaluation index according to the contribution degree of the evaluation index. The calculation formula is as follows:
k=1/lnm (6)
g j ＝1-e j (7)
In e j Entropy value g representing j-th evaluation index j A difference coefficient, w, representing the j-th evaluation index j The weight of the j-th evaluation index is represented.
E3. Obtaining weight vector w= (W) of each evaluation index through steps E1 and E2 1 ,w 2 ,…,w n ) Weighted sum of the weight vector and its corresponding value e=xw T ＝(E 1 ,E 2 ,…,E i ,…E m ) Obtaining the sampling region R i Comprehensive pollution index E of heavy metals of meat products i 。
Compared with the prior art, the invention has the advantages that:
the method is characterized by integrating various attributes, constructing a comprehensive evaluation method of heavy metal pollution in meat products based on a BWM-E model, firstly fusing and preprocessing data, and determining indexes capable of reflecting the heavy metal pollution degree in the meat products from the data; secondly, comprehensively evaluating the heavy metal pollution condition in the meat products by combining the determined multi-attribute evaluation indexes by utilizing an optimal worst method to obtain heavy metal pollution indexes of various meat products; and finally, evaluating the heavy metal pollution conditions in the meat products in different areas by using an entropy method on the basis to obtain the heavy metal pollution conditions in the meat products in each area. Compared with the existing two methods for evaluating the heavy metal pollution of foods commonly used for reflecting the heavy metal pollution of foods by the overstandard rate and the internal Mei Luo index method, the method can integrate various attributes, evaluate the heavy metal pollution degree in various meat products more comprehensively and objectively, and can highlight the areas with abnormal heavy metal pollution by measuring the change condition of the heavy metal pollution degree of various meat products in different areas, thereby effectively highlighting the difference of the heavy metal pollution degree in different areas.
Drawings
FIG. 1 is a flow chart of a comprehensive evaluation method for heavy metal pollution of meat products;
wherein, (a) is a data fusion and preprocessing process; (b) The heavy metal pollution index of various meat products is obtained by comprehensively evaluating by adopting an optimal worst method; (c) In order to comprehensively evaluate the heavy metal pollution conditions of all areas by an entropy method, the comprehensive pollution index of the heavy metal of the meat products of all areas is obtained.
FIG. 2 is an evaluation index system in the comprehensive evaluation model of the heavy metal pollution of the meat product;
Detailed Description
The invention is further described by way of examples in the following with reference to the accompanying drawings, but in no way limit the scope of the invention.
The invention provides a comprehensive evaluation method for heavy metal pollution in meat products based on a BWM-E model. Firstly, fusing and preprocessing data, and determining an index capable of reflecting the degree of heavy metal pollution in meat products from the data; secondly, comprehensively evaluating the heavy metal pollution condition in the meat products by combining the determined multi-attribute indexes by utilizing an optimal worst method to obtain heavy metal pollution indexes of various meat products; and finally, evaluating the heavy metal pollution conditions in the meat products in different areas by using an entropy method on the basis to obtain the heavy metal pollution conditions in the meat products in each area. The method integrates multiple attribute indexes, can comprehensively and objectively reflect the heavy metal pollution condition of the meat product, highlight the areas with abnormal heavy metal pollution in the meat product, and can effectively highlight the difference of the heavy metal pollution degree of the meat product in different areas. The process flow is shown in fig. 1.
The method for comprehensively evaluating the heavy metal pollution in the meat products is constructed by integrating multiple attribute indexes and constructing a BWM-E model-based comprehensive evaluation method for the heavy metal pollution degree in various meat products. And further obtaining the heavy metal pollution degree and comparison result of each region. The method solves the problem that the consideration factors of the comparison method for evaluating the heavy metal pollution in the food are single.
The operation steps of the specific embodiment of the invention are as follows:
and A, data integration and index selection.
The step fuses the heavy metal detection result data set and the limit standard data set in the meat product to obtain the data set for evaluating the heavy metal pollution in the meat product. Data samples are shown in table 1, for example:
table 1 raw data table (section)
According to the pollutant limit in food safety national standard food (GB 2762-2017) and the detection data set, 4 heavy metals and the heavy metal pollution level related to the detected amount are selected as indexes. Wherein the 4 heavy metals are cadmium (Cd), chromium (Cr), total arsenic (As) and lead (Pb) respectively; the heavy metal pollution levels are obtained by comparing the detected content of the heavy metal with the Maximum Residual Limit (MRL), and are divided into 4 levels, namely 1 level pollution (ND < detected content less than or equal to 0.1 MRL), 2 level pollution (ND < detected content less than or equal to 0.5 MRL), 3 level pollution (0.5 MRL < detected content less than or equal to MRL) and 4 level pollution (MRL < detected content), wherein ND is not detected. The total 16 evaluation indexes are shown in table 2:
TABLE 2 evaluation index Table
And counting the fused data according to the evaluation indexes to obtain an evaluation index value table, as shown in table 3 and table 4. The number in the value table is the ratio (symbol is%) of the detected frequency corresponding to the index to the total number of heavy metal detections corresponding to the index. If the value corresponding to the meat product Cd4 in the A city is the ratio of the detected number corresponding to the meat product Cd4 in the A city to the detected total number of the meat product Cd in the A city.
Table 3: evaluation index value table
Table 4: evaluation index value table (supplement)
B, calculating the evaluation index weight in the step A by using an optimal worst method
The evaluation index is layered (as shown in fig. 2), and index weights of the layers are calculated layer by layer. Firstly, calculating the weight of a first layer of indexes by using an optimal worst method, determining the optimal indexes and the worst indexes as cadmium and chromium according to the harm degree of heavy metals to human bodies, adopting a 1-9 scale method, respectively comparing the optimal indexes of cadmium with chromium, lead, total arsenic and cadmium in pairs, respectively comparing the optimal indexes of chromium, lead, total arsenic and cadmium with the worst indexes of chromium in pairs to obtain a comparison vector A corresponding to the layer B ＝(9,4,3,1),A W = (1,4,5,9). Then makeCalculating the weight of the index of the second layer by using an optimal worst method, wherein the 4-level pollution and the 1-level pollution are respectively the optimal index and the worst index, comparing the 4-level pollution of the optimal index with the 1-level pollution, the 2-level pollution, the 3-level pollution and the 4-level pollution by using a 1-9 scale method, and comparing the 1-level pollution, the 2-level pollution, the 3-level pollution and the 4-level pollution with the 1-level pollution of the worst index by two to obtain a comparison vector A corresponding to the layer B ＝(9,6,3,1),A W = (1, 3,6, 9). Bringing the two sets of comparison vectors into formula (2) to calculate the weight vector W of each layer 1 And W is 2 And meanwhile, whether the consistency test is satisfied is verified, and the weight and the xi of each layer are shown in the table 5, so that the consistency test is satisfied.
Table 5: heavy metal weight and pollution grade weight
All evaluation index weights are calculated according to the formula (3):
W＝W 2 T W 1 (3)
W in the formula 1 For the first layer index weight vector, W 2 And W is a weight matrix corresponding to the evaluation index table structure in table 2. The weights W' obtained after the sorting, that is, the weights of the 16 evaluation indexes are shown in tables 6 and 7.
Table 6: evaluation index weight table
Table 7: evaluation index weight table (supplement)
C. And B, carrying out weighted summation on the evaluation index weight obtained in the step B and the corresponding evaluation index values in the table 6 and the table 7 to obtain heavy metal pollution indexes of various meat products. Taking the data of the first city as an example, the heavy metal pollution indexes of various meat products are shown in table 8.
Table 8: heavy metal pollution index of various meat products (Jia city)
D. And C, calculating heavy metal pollution indexes of various meat products in different areas through the steps A-C, and constructing comprehensive evaluation matrixes of heavy metal pollution in different areas.
E. And calculating the heavy metal pollution index of each place.
And (3) introducing the evaluation results of the heavy metal pollution of various meat products in the market 5 into formulas (4) to (8) to obtain the weight of the various meat products in the comprehensive evaluation process of the heavy metal pollution in different areas, wherein the weight is shown in a table 9.
k=1/lnm (6)
g j ＝1-e j (7)
r ij Indicating that the j-th evaluation index is used for the region R i And carrying out contribution degree of comprehensive evaluation. e, e j Entropy value d representing j-th evaluation index j And the difference coefficient is the j-th evaluation index.
Table 9: weight of evaluation index of heavy metal pollution in each place
The heavy metal pollution indexes of each region are obtained by weighted summation of the weights of various meat products in table 9 and the heavy metal pollution indexes of the corresponding meat products in different regions, and are shown in table 10:
table 10: index of heavy metal pollution in various places
Through the above steps, the heavy metal pollution index (shown in table 8) and the heavy metal pollution index (shown in table 10) of each type of meat product are obtained.
In order to demonstrate the advantages of the method of the present invention, in this embodiment, two conventional methods of the internal Mei Luo index method and the superscalar rate are provided for the same data set, and the evaluation results are compared with the evaluation results obtained by the present invention. And selecting an internal Mei Luo index method and an exceeding rate as a control group, wherein the exceeding rate refers to the percentage of the number of samples with the heavy metal content exceeding the maximum limit standard detected in the sampled meat samples to the total number of the meat samples. The evaluation results of heavy metal pollution of various meat products by using the internal Mei Luo index method and the exceeding rate are shown in table 11, and the evaluation results of heavy metal pollution of various meat products by using the internal Mei Luo index method and the exceeding rate are shown in table 12.
And comparing the evaluation results of the internal Mei Luo index method and the superscalar rate with the multi-attribute evaluation results. As shown in table 11, the heavy metal pollution condition of various meat products in the first city is evaluated by an internal Mei Luo index method, and the meat products are ranked from high to low to cooked meat dry products, cured meat products, sauced meat products and smoked and boiled sausage ham products; the method is combined with the exceeding rate, and the method finds that the exceeding rate of the cured meat product and the sauced meat product with lower internal Mei Luo index exceeds that of the cured meat product although the Mei Luo index in the cured meat product is high, and no sample with exceeding heavy metal exists, so that different evaluation results are obtained by the two methods. The comprehensive evaluation result of various meat products by combining various attributes shows that the heavy metal pollution index of various meat products is from high to low, namely sauced and braised meat products, salted and cured meat products, cooked and dried meat products and smoked and cooked sausage ham products. In the ranking result calculated by the method, the sauced braised meat products and the salted and preserved meat products with the phenomenon of exceeding standards are ranked at the front, particularly the detection rate of the heavy metal cadmium with the largest toxicity is higher, and the ranking change of the sauced braised meat products with the phenomenon of exceeding standards is quite large.
As shown in table 12, the heavy metal pollution conditions in different regions are ranked according to the inner Mei Luo index method and the overstandard ratio, and the obtained ranking results are the same, namely, the high-to-low ranking results are the first city, the third city, the second city, the fifth city and Ding Shi, and the difference between the inner Mei Luo index and the overstandard ratio between different regions is smaller. The sequencing result of the heavy metal pollution degree of the meat products in each place is consistent with the sequencing result of the comparison method, but the pollution indexes of the first city and the third city are obviously higher than those of other cities, especially the first city, because the heavy metal detection rate of the meat products in the first city and the third city is higher and the overstandard samples exist, and in addition, the heavy metal cadmium with the largest toxicity has higher detection rate in the meat products in the first city and the overstandard condition exists, namely the abnormal condition of the heavy metal detection is needed to be attended by inspectors.
Table 11: three methods calculate heavy metal pollution indexes (Jia city) of various meat products
Table 12: three methods calculate heavy metal pollution index of each market
The comprehensive evaluation method provided by the invention is used for evaluating the heavy metal pollution in the meat product. By referring to the pollutant limit in food safety national standard food (GB 2762-2017) and the heavy metal detection result, two attributes of heavy metal and pollution level which can be used for quantitatively evaluating the heavy metal pollution degree in meat products are obtained. By combining the two attributes, a BWM-E model is designed based on an optimal worst method and an entropy value method, so that the degree of heavy metal pollution of various meat products and various areas is comprehensively and quantitatively evaluated.
It should be noted that the purpose of the disclosed embodiments is to aid further understanding of the present invention, but those skilled in the art will appreciate that: various alternatives and modifications are possible without departing from the spirit and scope of the invention and the appended claims. Therefore, the invention should not be limited to the disclosed embodiments, but rather the scope of the invention is defined by the appended claims.
Claims (5)
1. A method for evaluating heavy metal pollution in meat products based on BWM-E comprises the following steps:
A. integrating the detection result data sets of the heavy metal pollution in various meat products in different areas with the limit standard data sets to obtain the original data sets of the heavy metal pollution in various meat products in different areas, determining the evaluation index for comprehensively evaluating the heavy metal pollution in the meat products, and obtaining an evaluation index value matrix I= (I) for evaluating the heavy metal pollution of various meat products 1 ,I 2 ,..I n ) T Wherein I i An evaluation index value indicating an i-th meat product, n indicating the number of meat product types;
B. and C, carrying out hierarchical division on the evaluation index set according to the attribute of the evaluation index set determined in the step A, and calculating the weight of the evaluation index layer by using an optimal worst method to finally obtain a weight vector W' = (W) of each evaluation index 1 ,w 2 ,…,w n )；
C. And B, carrying out weighted summation on the weight vector W ' obtained in the step B and the index value corresponding to the weight vector W ' to obtain a heavy metal pollution index set M ' of various meat products in different areas, wherein the formula is as follows:
M′＝IW′ T (1)
Heavy metal pollution index set M' = (M) of various meat products 1 ,M 2 ,…,M i ,…M n ) Wherein M is i The heavy metal pollution index of the i-th meat product is represented, and n is the number of meat product categories;
D. calculating the heavy metal pollution indexes of different types of meat products in different areas according to the steps A-C; taking the heavy metal pollution indexes of various meat products as evaluation indexes, and taking the heavy metal pollution indexes of various meat products as evaluation index values for comprehensively evaluating the heavy metal pollution in different areas to obtain an evaluation matrix;
E. comparing the change conditions of heavy metal pollution indexes of various meat products in different areas by using an entropy method, and determining the importance degree, namely index weight, of the meat products for evaluating the heavy metal pollution degree in the areas; and D, weighting and summing the index weight and the evaluation index value in the step D to obtain the comprehensive pollution index of the heavy metal of the meat product in each region.
2. The method for evaluating heavy metal pollution in a meat product based on BWM-E as set forth in claim 1, wherein the specific calculation process in step B is as follows:
B1. b, according to the properties of the evaluation indexes selected in the step A, carrying out hierarchical division on the evaluation indexes, determining the optimal indexes and the worst indexes in the index sets of each layer, wherein the optimal indexes are the indexes with the largest toxicity, and the worst indexes are the indexes with the smallest toxicity, and if a plurality of groups of optimal worst indexes exist, taking one group;
B2. for each layer of indexes, adopting a 1-9 scale method, and comparing the optimal indexes of the layer with the importance degrees of all indexes of the layer in pairs to obtain a comparison vector A B ＝(a B1 ,a B2 ,…,a Bn ) Simultaneously, all indexes of the layer are compared with the importance degree of the worst indexes in pairs to obtain a comparison vector A W ＝(a 1W ,a 2W ,…,a nW ) Wherein a is Bi A represents the ratio of the importance of the optimal index B to the index i iW The ratio of the importance of index i to the worst index W; n represents the index number of the layer;
B3. each layer of indexes obtains a group of comparison vectors A B 、A W Setting the optimal weight set as { w } 1 ,w 2 ,…,w n Bringing the comparison vector corresponding to the index of the k layer into the following formula,
obtaining the index weight vector W of the layer k ＝(w 1 ,w 2 ,…,w i ,…,w n ) With xi k ,W k The component w of (2) i Represents the ith index weight of the kth layer, and xi k For calculating the consistency ratio corresponding to the comparison vector of the k-layer index as CR value, when CR<When 0.1, the set of comparison vectors satisfies consistency test, the corresponding weight vector W can be used for subsequent analysis, otherwise, the comparison vectors need to be adjusted;
B4. calculating an evaluation index weight matrix W by the formula (3),
W＝W n T W n-1 …W 1 (3)
W in the formula n Representing the n-th layer index weight vector.
3. The method for evaluating heavy metal pollution in a meat product based on BWM-E of claim 1, wherein step D obtains an evaluation matrix according to the calculation results of steps a to C as follows:
wherein R is i Refers to the i-th sampling area for evaluation; x is x ij Is indicated at R i Heavy metal pollution index of the j-th meat product in the sampling area; m refers to the number of sampling areas; n refers to the number of the sampled meat products in the sampling area, namely the number of the meat products for comprehensively evaluating the heavy metal pollution degree in the sampling area.
4. The method for evaluating heavy metal pollution in a meat product based on BWM-E as set forth in claim 1, wherein the specific calculation process of step E is:
E1. according to the change condition of heavy metal pollution indexes of various meat products in different areas, calculating the information contribution degree of the various meat products when the various meat products are used as comprehensive evaluation indexes for the heavy metal pollution degrees in different areas, wherein the calculation formula is as follows:
wherein r is ij Indicating that the j-th evaluation index is used for the region R i Performing comprehensive evaluation on the contribution degree;
E2. according to the evaluation index contribution degree, calculating the weight of each evaluation index, wherein the calculation formula is as follows:
k=1/lnm (6)
g j ＝1-e j (7)
In e j Entropy value g representing j-th evaluation index j A difference coefficient, w, representing the j-th evaluation index j A weight indicating a j-th evaluation index;
E3. obtaining weight vector w= (W) of each evaluation index through steps E1 and E2 1 ,w 2 ,…,w n ) Weighted sum of the weight vector and its corresponding value e=xw T ＝(E 1 ,E 2 ,…,E i ,…E m ) Obtaining the sampling region R i Heavy metal pollution index E of (2) i 。
5. The method for evaluating heavy metal pollution in a BWM-E-based meat product according to claim 2, wherein the number of indices of each layer in step B1 is less than 9.
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