CN112766739A - BWM-E model-based evaluation method for heavy metal pollution in meat products - Google Patents
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Abstract
The invention provides a BWM-E model-based evaluation method for heavy metal pollution in meat products. The method comprises the steps of firstly, fusing and preprocessing data, and determining an index capable of reflecting the heavy metal pollution degree in the meat product; comprehensively evaluating the heavy metal pollution condition in the meat products by combining the determined multi-attribute evaluation indexes by using an optimal worst method to obtain the heavy metal pollution indexes of various meat products; and finally, evaluating the heavy metal pollution conditions of the meat products in different regions by using an entropy method on the basis to obtain the heavy metal pollution indexes of the meat products in all regions. 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 the 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 BWM-E model-based comprehensive evaluation method for heavy metal pollution in meat products.
Background
Animal food such as livestock meat is the main source of high quality protein and micronutrient. With the improvement of the living standard of residents in China, the consumption of meat products is continuously increased, and heavy metals contained in the meat products can cause various damages to the health of human bodies. Heavy metals in food mainly come from soil, industrial three wastes, food processing and packaging and other ways, and pollutants enter human bodies through the enrichment function of food chains and are accumulated in certain organs to cause chronic poisoning. Therefore, the detection of heavy metals in meat products and the evaluation of the pollution degree are important parts in the risk monitoring work of harmful factors of food pollution. However, how to comprehensively and quantitatively evaluate the heavy metal pollution degree of various meat products and meat products in different regions according to the obtained detection result still remains a problem to be solved urgently.
The current comprehensive evaluation method for the heavy metal pollution degree in food mainly comprises two methods: one method is to adopt an internal Meiro index method, which firstly calculates the fractional indexes (single pollution indexes) of various heavy metals, then calculates the average value of each fractional index, and calculates the pollution degree of the heavy metals in the food by taking the maximum fractional index and the average value. And the other method is to adopt a single-attribute evaluation method, 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, and thus comprehensively evaluate the heavy metal pollution degree in the food. However, when the pollution degree of heavy metals in food is evaluated by adopting an internal Meiro index method and an overproof rate, the properties such as heavy metal toxicity and the like are neglected, and the pollution degree of heavy metals in food cannot be comprehensively reflected. The same sampling area can detect various foods, the heavy metal pollution degree in the foods in various areas is evaluated by using the current method, so that the influence of the food with abnormal detection conditions on the analysis of the difference of the heavy metal pollution degree of the foods in various areas and the sampling area with the abnormal heavy metal pollution condition can not be highlighted when the spatial distribution of the heavy metal pollution in the foods is further found.
Disclosure of Invention
Aiming at the defects of the existing evaluation Method, based on the Best-Worst Method and the entropy Method, the BWM-E-based comprehensive evaluation Method for heavy metal pollution in meat products is provided, and various attributes can be integrated to perform comprehensive evaluation on various meat products and heavy metal pollution conditions in different regions respectively.
The technical scheme provided by the invention is as follows:
a BWM-E model-based comprehensive evaluation method for heavy metal pollution in meat products. 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 combining the selected multi-attribute evaluation indexes by using an optimal worst method to obtain the heavy metal pollution indexes of various meat products; and finally, evaluating the heavy metal pollution degree of the meat products in different regions by using an entropy method on the basis to obtain the indexes of the heavy metal pollution of the meat products in different regions. The method integrates multiple attribute indexes, can comprehensively and objectively reflect the heavy metal pollution condition of the meat products, and can effectively highlight the difference of the heavy metal pollution degree of the meat products in different areas. The method comprises the following specific steps:
A. and integrating the data sets of the heavy metal detection results of the meat products in different regions with the data sets of the limit standard to obtain the original data sets of the heavy metal pollution of the meat products in different regions, wherein the limit standard adopts the food safety national standard food pollutant limit (GB 2762-2017). Determining an evaluation index for comprehensive evaluation of heavy metal pollution in the meat product according to the detection result and the limit standard; and counting the detection conditions (such as detection rate) of each evaluation index in various meat products in different regions according to the determined evaluation index to obtain an evaluation index value matrix I (I) for evaluating the heavy metal pollution of various meat products1,I2,..In)TWherein, IiThe evaluation index value of the ith meat product is shown, and n is the number of the meat product types.
B. According to the attributes of the evaluation index set determined in the step A, the evaluation index set is hierarchically divided, the weights of the evaluation indexes are calculated layer by using an optimal worst method, and finally a weight vector W' of each evaluation index is obtained (W ═ W1,w2,…,wn)；
C. And B, weighting and summing the weight vector W ' obtained in the step B and the index value corresponding to the weight vector W ' to obtain heavy metal pollution index sets M ' of various meat products in different regions, wherein the formula is as follows:
M′＝IW′T(formula 1)
Heavy metal pollution index set M ═ for various meat products (M ═ M)1,M2,…,Mi,…Mn) Wherein M isiThe index of heavy metal pollution of the ith meat product is expressed, and n is the number of meat product categories;
D. calculating the heavy metal pollution indexes of meat products of different types in different regions according to the steps A-C; taking various meat products subjected to spot inspection as evaluation indexes, taking the heavy metal pollution indexes of the various meat products as evaluation index values for comprehensive evaluation of heavy metal pollution in different regions, and obtaining an evaluation matrix;
E. comparing the change conditions of the heavy metal pollution indexes of various meat products in different regions by using an entropy method, and determining the importance degree of the meat products in evaluating the heavy metal pollution degree of the regions, namely index weight; and D, weighting and summing the index weight and the evaluation index value in the step D to obtain the comprehensive heavy metal pollution index of the meat products in each region.
Aiming at the BWM-E model-based comprehensive evaluation method for heavy metal pollution in meat products, the specific calculation process of the step B is as follows:
B1. according to the properties of the evaluation indexes selected in the step A, the evaluation indexes are hierarchically divided, so that the indexes are uniformly distributed in each layer, and the number of the indexes in each layer is at most 9 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 maximum toxicity, the worst index is the index with the minimum toxicity, and if a plurality of groups of optimal and worst indexes exist, one group is selected;
B2. for each layer of indexes, a 1-9 scale method is adopted, the optimal indexes of the layer and the importance degrees of all the indexes of the layer are compared pairwise to obtain a comparison vector AB＝(aB1,aB2,…,aBn) Simultaneously, the importance degrees of all indexes and the worst indexes of the layer are compared pairwise to obtain a comparison vector AW＝(a1W,a2W,…,anW) Wherein a isBiRepresents the ratio of the importance of the optimal index B to the index i, aiWA ratio of importance levels of the index i and the worst index W; n represents the number of indexes in the layer;
B3. each layer index obtains a group of comparison vectors AB、AWSetting an optimal weight set as { w1,w2,…,wnW weight for optimal indexBWeight w of all indexes in the same layeriThe ratio of (a) to (b)BiAs consistent as possible. Weight w of all indexes in the same leveliAnd the worst index weight wwThe ratio of (a) to (b)iWAs consistent as possible. Meanwhile, each index weight is not negative, and the sum of all index weights is 1. Therefore, the optimization problem can be converted into the optimization problem shown in formula (2), the comparison vector corresponding to the k-th layer index is substituted into the following formula,
obtain the index weight vector W of this layerk＝(w1,w2,…,wi,…,wn) And xik,WkComponent w ofiDenotes the ith index weight, ξ of the kth layerkFor calculating the consistency ratio corresponding to the comparison vector of the k-th layer index as CR value when CR is applied<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＝Wn TWn-1…W1(formula 3)
In the formula WnRepresenting the nth layer index weight vector. In order to facilitate the calculation of the subsequent steps, the evaluation index weight matrix W is arranged into an evaluation index weight vector W'.
Aiming at the comprehensive evaluation method for 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 comprises the following steps:
in the formula, RiThe ith sampling area for evaluation; x is the number ofijIs indicated at RiSampling the heavy metal pollution index of the jth meat product in the region; m indicates the number of sampling areas; and n refers to the number of the types of the meat products sampled in the sampling area, namely the number of the types of the meat products used for comprehensively evaluating the heavy metal pollution degree in the sampling area.
Aiming at the BWM-E model-based comprehensive evaluation method for heavy metal pollution of meat products, further, the specific calculation process of the step E is as follows:
E1. according to the change conditions of the heavy metal pollution indexes of various meat products in different regions, calculating the information amount contribution degree of the various meat products serving as the comprehensive evaluation index for the heavy metal pollution degrees in different regions, wherein the calculation formula is as follows:
in the formula rijIndicating that the jth evaluation index is used for the region RiAnd (5) carrying out comprehensive evaluation on the contribution degree.
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 is 1/lnm (formula 6)
gj＝1-ej(formula 7)
In the formula ejEntropy, g, representing the jth evaluation indexjCoefficient of variation, w, representing the jth evaluation indexjThe weight of the jth evaluation index is represented.
E3. Each evaluation index weight vector W obtained in steps E1 and E2 is (W)1,w2,…,wn) Weighting the weight vector and the corresponding value to sum E ═ XWT＝(E1,E2,…,Ei,…Em) Obtaining the sampling area RiComprehensive pollution index E of heavy metals in meat productsi。
Compared with the prior art, the invention has the advantages that:
the invention integrates various attributes, constructs a BWM-E model-based comprehensive evaluation method for heavy metal pollution in meat products, and firstly fuses and preprocesses data to determine an index capable of reflecting the degree of heavy metal pollution in the meat products; secondly, comprehensively evaluating the heavy metal pollution condition in the meat products by combining the determined multi-attribute evaluation indexes by using an optimal worst method to obtain the heavy metal pollution indexes of various meat products; and finally, evaluating the heavy metal pollution conditions in the meat products in different regions by using an entropy method on the basis to obtain the heavy metal pollution conditions in the meat products in each region. Compared with the existing two evaluation methods which are commonly used for reflecting the heavy metal pollution of food, namely an overproof rate method and an internal Merlot index method, the evaluation method can integrate multiple attributes, more comprehensively and objectively evaluate the heavy metal pollution degree in various meat products, 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, and effectively highlight the difference of the heavy metal pollution degree in different areas.
Drawings
FIG. 1 is a flow chart of the comprehensive evaluation method for heavy metal pollution of meat products;
wherein, (a) is a data fusion and pretreatment process; (b) comprehensively evaluating by adopting an optimal worst method to obtain the heavy metal pollution indexes of various meat products; (c) the comprehensive evaluation method is used for comprehensively evaluating the heavy metal pollution condition of each region by an entropy method to obtain the comprehensive pollution index of the heavy metal of meat products of each region.
FIG. 2 is an evaluation index system in the comprehensive evaluation model of heavy metal pollution of meat products of the invention;
Detailed Description
The invention will be further described by way of examples, without in any way limiting the scope of the invention, with reference to the accompanying drawings.
The invention provides a BWM-E model-based comprehensive evaluation method for heavy metal pollution in meat products. Firstly, fusing and preprocessing data, and determining an index capable of reflecting the heavy metal pollution degree in the meat product; secondly, comprehensively evaluating the heavy metal pollution condition in the meat products by combining the determined multi-attribute indexes by using an optimal worst method to obtain the heavy metal pollution indexes of various meat products; and finally, evaluating the heavy metal pollution conditions in the meat products in different regions by using an entropy method on the basis to obtain the heavy metal pollution conditions in the meat products in each region. The method integrates multiple attribute indexes, can comprehensively and objectively reflect the heavy metal pollution condition of the meat product, highlights the area 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 figure 1.
The invention integrates multiple attribute indexes, constructs a BWM-E model-based meat product heavy metal pollution comprehensive evaluation method, and comprehensively evaluates the heavy metal pollution degree in various meat products. Further obtaining the heavy metal pollution degree and the comparison result of each region. The method solves the problem that the consideration factor of the comparison method for evaluating the heavy metal pollution in the food is single.
The operation steps of the specific embodiment of the invention are as follows:
and A, integrating data and selecting indexes.
The step is to fuse a heavy metal detection result data set and a limit standard data set in the meat product to obtain a data set for evaluating the heavy metal pollution in the meat product. Data samples are shown in table 1:
table 1 original data table (part)
4 heavy metals and heavy metal pollution levels related to the detected amount are selected as indexes according to the food safety national standard food pollutant limit (GB2762-2017) and the detection data set. Wherein the 4 heavy metals are cadmium (Cd), chromium (Cr), total arsenic (As) and lead (Pb) respectively; the heavy metal pollution level is obtained by comparing the detected content of heavy metal with the Maximum Residual Limit (MRL), and is divided into 4 levels, namely level 1 pollution (ND < the detected content is less than or equal to 0.1MRL), level 2 pollution (0.1MRL < the detected content is less than or equal to 0.5MRL), level 3 pollution (0.5MRL < the detected content is less than or equal to MRL) and level 4 pollution (MRL < the detected content), wherein ND means undetected. A total of 16 evaluation indices are obtained as shown in table 2:
TABLE 2 evaluation index Table
And (4) counting the fused data according to the evaluation indexes to obtain an evaluation index value-taking table shown in table 3 and table 4. The number in the value table is the ratio (symbol is%) of the detection frequency corresponding to the index to the total detection number of the heavy metals corresponding to the index. For example, the value corresponding to the A-class meat products Cd4 in the A-class market is the ratio of the detection number corresponding to the A-class meat products Cd4 in the A-class market to the total detection number of the Cd in the A-class meat products in the A-class market.
Table 3: evaluation index value-taking table
Table 4: evaluation index value-taking meter (supplement)
B, calculating the weight of the evaluation index in the step A by using the optimal worst method
The evaluation indexes are layered (as shown in fig. 2), and the index weights of the layers are calculated layer by layer. Firstly, the optimal worst method is used for calculating the index weight of a first layer, the optimal index and the worst indexes are cadmium and chromium according to the degree of the heavy metal harming human bodies, the 1-9 scale method is adopted, the optimal index cadmium is respectively compared with chromium, lead, total arsenic and cadmium in pairs, the chromium, lead, total arsenic and cadmium are respectively compared with the worst index chromium in pairs, and a comparison vector A corresponding to the layer is obtainedB＝(9,4,3,1),AW(1,4,5, 9). Then, the optimal worst method is used for calculating the index weight of a second layer, the level 4 pollution and the level 1 pollution are respectively the optimal index and the worst index, a 1-9 scale method is adopted, the optimal index level 4 pollution is respectively compared with the level 1, the level 2, the level 3 and the level 4, the level 1, the level 2, the level 3 and the level 4 are respectively compared with the worst index level 1 pollution, and a comparison vector A corresponding to the layer is obtainedB＝(9,6,3,1),AW(1,3,6, 9). Substituting the two sets of comparison vectors into formula (2) to calculate the weight vector W of each layer1And W2And simultaneously, whether the consistency check is met is verified, and the weight and xi of each layer are shown in the table 5 and meet the consistency check.
Table 5: heavy metal weight and pollution level weight
Calculating all evaluation index weights according to formula (3):
W＝W2 TW1(formula 3)
In the formula W1As a first layer index weight vector, W2Is the second layer index weight vector, and W is the weight matrix, corresponding to the evaluation index table structure in Table 2. FinishingThe weight vector W' obtained after the above process, i.e., the weights of the 16 evaluation indexes, is shown in tables 6 and 7.
Table 6: evaluation index weight table
Table 7: evaluation index weight meter (supplement)
C. And B, weighting and summing the evaluation index weight obtained in the step B and the corresponding evaluation index values in the tables 6 and 7 to obtain the heavy metal pollution indexes of various meat products. Taking the data in the market A as an example, the heavy metal pollution indexes of the obtained meat products are shown in the table 8.
Table 8: heavy metal pollution index (Jiashi) of meat products
D. And (4) calculating the heavy metal pollution indexes of various meat products in different regions through the steps A-C, and constructing a comprehensive evaluation matrix of the heavy metal pollution in different regions.
E. And calculating the heavy metal pollution indexes of various places.
The evaluation results of the heavy metal pollution of various meat products in the 5 markets are substituted into the formulas (4) to (8), so that the weights of the various meat products in the process of carrying out comprehensive evaluation on the heavy metal pollution in different regions are obtained, and the weights are shown in a table 9.
k is 1/lnm (formula 6)
gj＝1-ej(formula 7)
rijIndicating that the jth evaluation index is used for the region RiAnd (5) carrying out comprehensive evaluation on the contribution degree. e.g. of the typejEntropy representing the j-th evaluation index, djThe coefficient of variation is the jth evaluation index.
Table 9: weight of each region heavy metal pollution evaluation index
Weighting and summing the weights of various meat products in the table 9 and the heavy metal pollution indexes of the corresponding meat products in different regions to obtain the heavy metal pollution indexes of the regions, as shown in the table 10:
table 10: index of heavy metal pollution in various regions
Through the steps, the heavy metal pollution indexes of various meat products (shown in table 8) and the heavy metal pollution indexes of various regions (shown in table 10) are obtained.
In order to show the advantages of the method of the present invention, in this embodiment, evaluation results of two traditional methods, i.e., an inner-merle index method and an over-standard rate, are provided for the same data set, and are compared with the evaluation results obtained by the present invention. And selecting two evaluation methods of an inner Meiro index method and an overproof rate as a control group, wherein the overproof rate refers to the percentage of the number of samples with the heavy metal content exceeding the maximum limit standard in the meat product samples in the total number of the meat product samples. The results of evaluation of heavy metal pollution in various meat products by using the internal Mello index method and the standard exceeding rate are shown in Table 11, and the results of evaluation of heavy metal pollution in various meat products by using the internal Mello index method and the standard exceeding rate are shown in Table 12.
And comparing the evaluation results of the inner Mero index method and the standard exceeding rate with the multi-attribute evaluation result. As shown in Table 11, the internal Meiluo index method evaluates the heavy metal pollution condition of various meat products in the market A, ranks the meat products, and comprises cooked meat products, cured meat products, sauced meat products and smoked sausage ham products from high to low; the overproof rate is combined to find that although the internal plum index of the cooked dried meat product is high, a sample with overproof heavy metal does not exist, but the overproof rate of the cured meat product and the sauced marinated meat product with lower internal plum index exceeds that of the cooked dried meat product, and different evaluation results are obtained by the two methods. The comprehensive evaluation results of various meat products by integrating various attributes show that the heavy metal pollution indexes of various meat products are from high to low, namely sauced marinated meat products, cured meat products, cooked meat dry products and smoked and cooked sausage ham products. According to the ranking result calculated by the method, the soy sauce braised meat products and the cured meat products which have the overproof phenomenon are ranked at the top, and particularly the soy sauce braised meat products which have the highest toxicity and high detection rate of the heavy metal cadmium and have the overproof phenomenon have large ranking variation.
As shown in table 12, the heavy metal pollution conditions in different regions are ranked according to the inner merlo index method and the standard exceeding rate, and the obtained ranking results are the same, namely the ranking results are from high to low in a first city, a third city, a second city, a fifth city and a fourth city, and the difference between the inner merlo index and the standard exceeding rate between different regions is small. The sequencing result of the heavy metal pollution degree of meat products in various places by the method is consistent with the sequencing result of a comparison method, but the pollution indexes of the meat products in the first city and the third city are obviously higher than those of other cities, particularly the first city, because the meat products in the first city and the third city have higher heavy metal detection rates and overproof samples, in addition, the heavy metal cadmium with the highest toxicity has higher detection rate in the meat products in the first city and overproof conditions exist, namely the abnormal condition of heavy metal detection exists, and the monitoring personnel need to pay attention.
Table 11: three methods for calculating heavy metal pollution index (Jia city) of various meat products
Table 12: three methods for calculating the index of heavy metal pollution in each market
The comprehensive evaluation method provided by the invention is used for evaluating the heavy metal pollution in meat products. By referring to the pollutant limit in national food standard for food safety (GB2762-2017) 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 integrating two attributes and designing a BWM-E model based on an optimal worst method and an entropy method, comprehensive quantitative evaluation on the heavy metal pollution degree of various meat products and various regions is realized.
It is noted that the disclosed embodiments are intended to aid in further understanding of the invention, but those skilled in the art will appreciate that: various substitutions and modifications are possible without departing from the spirit and scope of the invention and appended claims. Therefore, the invention should not be limited to the embodiments disclosed, but the scope of the invention is defined by the appended claims.
Claims (5)
1. A BWM-E based method for evaluating heavy metal pollution in meat products comprises the following steps:
A. integrating the data sets of the detection results of the heavy metal pollution in various meat products in different regions with the limit standard data sets to obtain the original data sets of the heavy metal pollution in the various meat products in different regions, determining the evaluation indexes 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 the various meat products1,I2,..In)TWherein, IiThe evaluation index value of the ith meat product is represented, and n represents the number of the meat product types;
B. according to the attributes of the evaluation index set determined in the step A, hierarchical division is carried out on the evaluation index set, the weights of the evaluation indexes are calculated layer by using the optimal worst method, and finally each evaluation index is obtainedThe target weight vector W ═ W1,w2,…,wn)；
C. And B, weighting and summing the weight vector W ' obtained in the step B and the index value corresponding to the weight vector W ' to obtain heavy metal pollution index sets M ' of various meat products in different regions, wherein the formula is as follows:
M′＝IW′T(formula 1)
Heavy metal pollution index set M ═ for various meat products (M ═ M)1,M2,…,Mi,…Mn) Wherein M isiThe index of heavy metal pollution of the ith meat product is expressed, and n is the number of meat product categories;
D. calculating the heavy metal pollution indexes of meat products of different types in different regions according to the steps A-C; taking various meat products subjected to spot inspection as evaluation indexes, taking the heavy metal pollution indexes of the various meat products as evaluation index values for comprehensive evaluation of heavy metal pollution in different regions, and obtaining an evaluation matrix;
E. comparing the change conditions of the heavy metal pollution indexes of various meat products in different regions by using an entropy method, and determining the importance degree of the meat products in evaluating the heavy metal pollution degree of the regions, namely index weight; 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 meat products in each region.
2. The method for evaluating the heavy metal pollution in meat products based on BWM-E of claim 1, wherein the specific calculation process of step B is as follows:
B1. 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 highest toxicity, the worst indexes are the indexes with the lowest toxicity, and if a plurality of groups of optimal and worst indexes exist, one group is selected;
B2. for each layer of indexes, a 1-9 scale method is adopted, the optimal indexes of the layer and the importance degrees of all the indexes of the layer are compared pairwise to obtain a comparison vector AB＝(aB1,aB2,…,aBn) Simultaneously, the importance degrees of all indexes and the worst indexes of the layer are compared pairwise to obtainCompare vector AW＝(a1W,a2W,…,anW) Wherein a isBiRepresents the ratio of the importance of the optimal index B to the index i, aiWA ratio of importance levels of the index i and the worst index W; n represents the number of indexes in the layer;
B3. each layer index obtains a group of comparison vectors AB、AWSetting an optimal weight set as { w1,w2,…,wnSubstituting the comparison vector corresponding to the k-th layer index into the following formula,
obtain the index weight vector W of this layerk＝(w1,w2,…,wi,…,wn) And xik,WkComponent w ofiDenotes the ith index weight, ξ of the kth layerkFor calculating the consistency ratio corresponding to the comparison vector of the k-th layer index as CR value when CR is applied<At 0.1, the set of comparison vectors meets the consistency test, the corresponding weight vector W can be used for subsequent analysis, otherwise, the comparison vectors need to be adjusted;
B4. an evaluation index weight matrix W is calculated by formula (3),
W＝Wn TWn-1…W1(formula 3)
In the formula WnRepresenting the nth layer index weight vector.
3. The method for evaluating the heavy metal pollution in the BWM-E based meat product of claim 1, wherein step D obtains an evaluation matrix according to the calculation results of steps A to C, wherein the evaluation matrix comprises:
in the formula, RiThe ith sampling area for evaluation; x is the number ofijIs indicated at RiSampling area jth meat processingThe index of heavy metal pollution of the product; m indicates the number of sampling areas; and n refers to the number of the types of the meat products sampled in the sampling area, namely the number of the types of the meat products used for comprehensively evaluating the heavy metal pollution degree in the sampling area.
4. The method for evaluating heavy metal contamination in meat products based on BWM-E of claim 1, wherein the specific calculation process of step E is as follows:
E1. according to the change conditions of the heavy metal pollution indexes of various meat products in different regions, calculating the information amount contribution degree of the various meat products serving as the comprehensive evaluation index for the heavy metal pollution degrees in different regions, wherein the calculation formula is as follows:
in the formula rijIndicating that the jth evaluation index is used for the region RiThe contribution degree of comprehensive evaluation is carried out;
E2. and calculating the weight of each evaluation index according to the contribution degree of the evaluation index, wherein the calculation formula is as follows:
k is 1/lnm (formula 6)
gj＝1-ej(formula 7)
In the formula ejEntropy, g, representing the jth evaluation indexjCoefficient of variation, w, representing the jth evaluation indexjA weight indicating a jth evaluation index;
E3. each evaluation index weight vector W obtained in steps E1 and E2 is (W)1,w2,…,wn) The weighted sum E of the weight vector and the corresponding value is equal toXWT＝(E1,E2,…,Ei,…Em) Obtaining the sampling area RiHeavy metal contamination index E ofi。
5. The method for evaluating the heavy metal contamination in meat products based on BWM-E of claim 2, wherein the index number of each layer in step B1 is less than 9.
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