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| A multi-factor comprehensive method based on the AHP-E model for evaluating pesticide residue pollution |
| Received:May 30, 2018 Revised:July 20, 2018 |
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| KeyWord:pesticide residue pollution;comprehensive evaluation method;multi-factor;analytic hierarchy process;entropy method |
| Author Name | Affiliation | | CHEN Yi | Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China | | CHEN Xing-ru | Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China | | CHANG Qiao-ying | Chinese Academy of Inspection Quarantine, Beijing 100176, China | | FAN Chun-lin | Chinese Academy of Inspection Quarantine, Beijing 100176, China |
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| Abstract: |
| To evaluate the degree of pesticide residue pollution in different agricultural products and over different time periods, a comprehensive evaluation method based on the analytic hierarchy process (AHP)-entropy (E)model for pesticide residue pollution was proposed. With this method, the evaluation factors were first selected from the results of pesticide residue detection, in which many factors, including pesticide toxicity, the frequency of which pesticides were detected, the pesticide content, and the level of exceeding the MRL (Maximum Residue Limit), were considered. Then, the AHP was applied to assess the degree of pesticide residue pollution in different agricultural products, and the entropy method was applied to assess the degree of pesticide residue pollution over different time periods. The case study used in this study was from the results of pesticide residue detection on six agricultural products in City A from March to June in 2013. For the degree of pesticide residue pollution in the different agricultural products, the ranking of results from higher to lower by two factors,i.e., the detection rate of pesticide residue and the rate of exceedance of the MRL, were cucumber, apple, tomato, green pepper, celery, leek, and celery, leek, cucumber, apple, tomato, green pepper, respectively. However, the ranking of results from higher to lower by the comprehensive evaluation value proposed by this study was leek, celery, cucumber, green pepper, tomato, apple. For the degree of pesticide residue pollution over different time periods,the ranking of results from higher to lower by both the pesticide residue detection rate and the rate of exceeding the MRL were May, April, March, and June, the ranking of results by the method of this study is also the same with evaluation result by the single-factor. Comparing above ranking results by single-factor and multi-factor evaluation, the same and different aspects were found. The reason for the discrepancy was that the evaluation method based on a single factor had limitations in terms of the completeness of evaluation. Our evaluation model in this study can evaluate the degree of pesticide residue pollution more comprehensively and effectively, and can highlight the difference in degree of pesticide residue pollution among different agricultural products. |
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