Analysis of the economically motivated food adulteration in China based on 6477 events from 2000 to 2020
Main Article Content
Keywords
economically motivated food adulteration, food fraud, food type, fraud means, adulteration, discovery source
Abstract
In order to investigate the epidemic characteristics of economically motivated food adulteration (EMA) in China, we analyzed the frequency and/or percentage of parameters of EMAs from 2000 to 2020. A total of 6477 EMAs were collected from a portal based in China and evaluated, the results showed that 69% of the EMAs were identified through supervisions and 95.7% EMAs were discovered in the sale process. The top three specifications of EMA information were listed as follows: the regions were Guangdong, Shandong, and Henan; the fraud means were illegal addition, substitution or dilution, and unqualified hygiene; the food types were meat, vegetable, and fruit. Our findings indicated that supervision of the production process of the main food types is of utmost importance to prevent EMA, according to adulterating phase, fraud means, and adulterer type.
References
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Zanin, L.M., et al., 2017. Knowledge, attitudes and practices of food handlers in food safety: An integrative review. Food Research International 100(Pt 1): 53–62. 10.1016/j.foodres.2017.07.042
Zhang, D., et al., 2020. FADB-China: a molecular-level food adulteration database in China based on molecular fingerprints and similarity algorithms prediction expansion. Food Chemistry 327: 127010. 10.1016/j.foodchem.2020.127010
Zhang, W.J. and Xue, J.H., 2016. Economically motivated food fraud and adulteration in China: an analysis based on 1553 media reports. Food Control 67: 192–198. 10.1016/j.foodcont.2016.03.004
Zhang, Y., et al., 2019. Water footprint of food consumption by Chinese residents. International Journal of Environmental Research and Public Health 16(20): 3979. 10.3390/ijerph16203979
Bouzembrak, Y. and Marvin, H.J.P., 2016. Prediction of food fraud means using data from Rapid Alert System for Food and Feed (RASFF) and Bayesian network modelling. Food Control 61: 180–187. 10.1016/j.foodcont.2015.09.026.
Cai, H.D., et al., 2019. Analysis and visualization of academic maps on economically motivated adulteration database of the center for food protection and defense, University of Minnesota, USA. Journal of Food Safety and Quality Inspect 10(24): 8548–8555.
Chen, Y., et al., 2021. The new evidence of China’s economic downturn: from structural bonus to structural imbalance. PLoS One 16(9): e0257456–e0257456. 10.1371/journal.pone.0257456
Chinese State Administration for Market Regulation Beijing 2020. Classification catalogue of food production license.
Esteki, M., et al., 2019. Tackling fraudsters with global strategies to expose fraud in the food chain. Comprehensive Reviews in Food Science and Food Safety 18(2): 425–440. 10.1111/1541-4337.12419
He, C., et al., 2019. Comparative study on food safety supervision system between China and Europe. Science and Technology of Food Industry 40(19): 216–220+225. 10.13386/j.issn1002-0306.2019.19.036
Kendall, H., et al., 2019. Chinese consumer’s attitudes, perceptions and behavioural responses towards food fraud. Food Control 95: 339–351. 10.1016/j.foodcont.2018.08.006
Lakade A. J., et al., 2018. Gold nanoparticle-based method for detection of calcium carbide in artificially ripened mangoes (Magnifera indica). Food Addit Contam Part A Chem Anal Control Expo Risk Assess 35(6): 1078–1084. 10.1080/19440049.2018.1449969
Li, D., et al., 2016. The united states’ experience in dealing with economically motivated adulteration and food fraud and its enlightenments to China. Shipin Kexue/Food Science 37(7): 259–263. 10.7506/spkx1002-6630-201607046
Lin, P., Tsai, H. and Ho, T., 2020a. Food safety gaps between consumers’ expectations and perceptions: development and verification of a gap-assessment tool. International Journal of Environmental Research and Public Health 17(17): 6328. 10.3390/ijerph17176328
Lin, Q., Zhu, Y. and Zhang, Y., 2020b. How does mission statement relate to the pursuit of food safety certification by food companies? International Journal of Environmental Research and Public Health 17(13): 4735. 10.3390/ijerph17134735
Miller, V., et al., 2016. Availability, affordability, and consumption of fruits and vegetables in 18 countries across income levels: findings from the Prospective Urban Rural Epidemiology (PURE) study. Lancet Global Health 4(10): e695–e703. 10.1016/s2214-109x(16)30186-3
National Bureau of Statistics. 2020. Available from: http://www.stats.gov.cn/
National People’s Congress, 2019. People’s Republic of China (PRC) product quality law. Implemented. Available from: http://www.npc.gov.cn/npc/c30834/201901/7f507d5963074e9ebc73c986e155b931.shtml
Niu, L., et al., 2021. Enterprise food fraud in China: Key factors identification from social co-governance perspective. Frontiers in Public Health 9: 752112–752112. 10.3389/fpubh.2021.752112
Pavlidis, D.E., et al., 2019. Application of data science in risk assessment and early warning. EFSA Journal 17(Suppl 2): e170908. 10.2903/j.efsa.2019.e170908
Pigłowski, M., 2020. Food hazards on the European Union market: the data analysis of the Rapid Alert System for Food and Feed. Food Science & Nutrition 8(3): 1603–1627. 10.1002/fsn3.1448
Quan, S.W., 2020. Sustainable food consumption behavior: dynamic mechanism and guiding strategy. World Agriculture (06): 25–35+79+132. 10.13856/j.cn11-1097/s.2020.06.004
Quintero-Lesmes, D.C. and Herran, O.F., 2019. Food changes and geography: Dietary transition in Colombia. Annals of Global Health 85(1): 28. 10.5334/aogh.1643
Robson, K., et al., 2021. A comprehensive review of food fraud terminologies and food fraud mitigation guides. Food Control 120: 107516. 10.1016/j.foodcont.2020.107516
Rocchi, B., et al., 2020. Assessing the economy-wide impact of food fraud: a SAM-based counterfactual approach. Agribusiness 36(2): 167–191. 10.1002/agr.21633
Shen, C., et al., 2021. A bibliometric analysis of food safety governance research from 1999 to 2019. Food Science & Nutrition 9(4): 2316–2334. 10.1002/fsn3.2220
Spink, J., et al., 2015. Introducing food fraud including translation and interpretation to Russian, Korean, and Chinese languages. Food Chemistry 189: 102–107. 10.1016/j.foodchem.2014.09.106
Taha, S., et al., 2020. Food safety performance in food manufacturing facilities: The influence of management practices on food handler commitment. Journal of Food Protection 83(1): 60–67. 10.4315/0362-028x.Jfp-19-126
Tan, Y. and Zhang, J.Y., 2019. Analysis on the impact of new urbanization on food consumption structure of Chinese residents–Based on LA/AIDS expansion model. Xinjiang State Farms Economy 04: 23–33.
Theolier, J., et al., 2021. Risk analysis approach applied to consumers’ behaviour toward fraud in food products. Trends in Food Science & Technology 107: 480–490. 10.1016/j.tifs.2020.11.017
Tibola, C.S., et al., 2018. Economically motivated food fraud and adulteration in Brazil: Incidents and alternatives to minimize occurrence. Journal of Food Science 83(8): 2028–2038. 10.1111/1750-3841.14279
US, 2009. Food and Drug Administration. Federal Register. Available from: http://www.govinfo.gov/contect/pkg/FR-2009-04-06/pdf/FR-2009-04-06.pdf [cited 29 October 2015].
Wang, L., 2021. Problems and countermeasures of grass-roots food safety supervision in new situation. Chinese Market 09: 98–99. 10.13939/j.cnki.zgsc.2021.09.098
Wang, W.Q., et al., 2019. Analysis of global economically motivated adulteration and food fraud based on the EMA database of the United States Pharmacopeia. Journal of Food Safety and Quality Inspection 10(03): 804–810.
Yang, X., 2019. Enlightenment of the American food safety standards mode to Chinese food safety supervision. Journal of Food Safety and Quality Inspection 10(16): 5556–5560.
Yang, Y., et al., 2020. The Chinese milk supply chain: A fraud perspective. Food Control 113: 107211. 10.1016/j.foodcont.2020.107211
Zanin, L.M., et al., 2017. Knowledge, attitudes and practices of food handlers in food safety: An integrative review. Food Research International 100(Pt 1): 53–62. 10.1016/j.foodres.2017.07.042
Zhang, D., et al., 2020. FADB-China: a molecular-level food adulteration database in China based on molecular fingerprints and similarity algorithms prediction expansion. Food Chemistry 327: 127010. 10.1016/j.foodchem.2020.127010
Zhang, W.J. and Xue, J.H., 2016. Economically motivated food fraud and adulteration in China: an analysis based on 1553 media reports. Food Control 67: 192–198. 10.1016/j.foodcont.2016.03.004
Zhang, Y., et al., 2019. Water footprint of food consumption by Chinese residents. International Journal of Environmental Research and Public Health 16(20): 3979. 10.3390/ijerph16203979
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Published
May 12, 2023
Article Details
How to Cite
Wang, T.- wei, Zhang, M.- li, Sun, N.- na, Chen, H.- hui, Zhang, C.- xiao, Wang, Q., & Zhang, W.- zhong. (2023). Analysis of the economically motivated food adulteration in China based on 6477 events from 2000 to 2020. Quality Assurance and Safety of Crops & Foods, 15(2), 222-231. https://doi.org/10.15586/qas.v15i2.1144
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Research Article
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
How to Cite
Wang, T.- wei, Zhang, M.- li, Sun, N.- na, Chen, H.- hui, Zhang, C.- xiao, Wang, Q., & Zhang, W.- zhong. (2023). Analysis of the economically motivated food adulteration in China based on 6477 events from 2000 to 2020. Quality Assurance and Safety of Crops & Foods, 15(2), 222-231. https://doi.org/10.15586/qas.v15i2.1144