Abstract
Pork safety incidents happened frequently in China even if the traditional traceability system was established, which declines the consumers’ confidence rapidly. Thus, this paper aims to explore a trustworthy traceability of quality and safety for the pig supply chain. We then proposed a framework for traceability of pig supply chain based on blockchain. In our research, we found that HACCP is suitable for screening key information in every link of pig supply chain, and GS1 can achieve the series connection of information on the pig supply chain, which reduces the isolated information and increases the transparency of the supply chain. However, information provided by traditional traceability system failed to guarantee the authenticity and credibility because of its hidden troubles such as monopoly, corruption, counterfeit, hacker attack and so on. To tackle this problem, we verified the validity and credibility of pig traceability information by deploying the smart contract on a consortium blockchain and analyzing its operating mechanism from the perspective of consumers.
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References
National Bureau of Statistics of the People’s Republic of China: China Statistical Yearbook. Beijing: China Statistics Press (2017). http://www.stats.gov.cn/tjsj/ndsj/2017/indexch.htm
Liu, Z.J.: Study on Operating Mechanism of Pork Traceability System in China Based on Food Safety: Taking Beijing City as an Example. China Agricultural University, Beijing (2015)
Steiner, J., Baker, J., Wood, G., Meiklejohn, S.: Blockchain: The Solution for Transparent in Product Supply Chains. A white paper was written by Project Provenance Ltd. (2016)
Nakamoto, S.: Bitcoin: A Peer-to-Peer Electronic Cash System. Consulted (2008)
Yli-Huumo, J., Ko, D., Choi, S., Park, S., Smolander, K.: Where is current research on blockchain technology?—a systematic review. PLoS ONE 11(10), e0163477 (2016). https://doi.org/10.1371/journal.pone.0163477
Xie, J., Lu, C., Li, B., et al.: Implementation of pork traceability system based on .NET framework. Trans. Chin. Soc. Agric. Eng. 22(6), 218–220 (2006)
Hai, X.B., Qing‐Yao, L., Liang, Y., et al.: A practical web-based tracking and traceability information system for the pork products supply chain. In: International Conference on Computers and Computing Technologies in Agriculture, pp. 725–733 (2007)
Zadernowski, M.R., Verbeke, W., Verhé, R., Babuchowski, A.: Toward meat traceability critical control point analysis in the Polish pork chain. J. Int. Food Agribus. Mark. 12(4), 5–23 (2008). https://doi.org/10.1300/J047v12n04_02
Serikawa, S., Lu, H.: Underwater image dehazing using joint trilateral filter. Comput. Electr. Eng. 40(1), 41–50 (2014)
Lu, H., Li, B., Zhu, J., Li, Y., Li, Y., Xu, X., et al.: Wound intensity correction and segmentation with convolutional neural networks. Concurr. & Comput. Pract. Exp. 29(6) (2016)
Yang, X., Qian, J., Sun, C., et al.: Key technologies for establishment agricultural products and food quality safety traceability systems. Trans. Chin. Soc. Agric. Mach. 45(11), 212–222 (2014)
Bai, H., Zhou, G.H., Hu, Y., Sun, A., Xu, X.-L., Liu, X., Lu, C.: Traceability technologies for farm animals and their products in China. Food Control 79, 35–43 (2017). https://doi.org/10.1016/j.foodcont.2017.02.040
Badia-Melis, R., Mishra, P., Ruiz-García, L.: Food traceability: new trends and recent advances. A review. Food Control 57, 393–401 (2015)
Swan, M.: Blockchain: Blueprint for a New Economy. O’Reilly Media, Inc. (2015)
Jeppsson, A., Olsson, O.: Blockchains as a solution for traceability and transparency. MSE thesis, Department of Design Sciences, Lund University, Lund, Sweden (2017)
Kshetri, N.: 1 Blockchain’s roles in meeting key supply chain management objectives. Int. J. Inf. Manage. 39, 80–89 (2018)
del Castillo, M.: Microsoft Unveils Project Manifest, A Plan for Blockchain Product Tracking (2017)
Lu, Q., Xu, X.: Adaptable blockchain-based systems: a case study for product traceability. IEEE Softw. 34(6), 21–27 (2017)
Tian, F.: An agri-food supply chain traceability system for China based on RFID & blockchain technology. In: International Conference on Service Systems and Service Management, pp. 1–6. IEEE (2016)
Tian, F.: A supply chain traceability system for food safety based on HACCP, blockchain & Internet of things. In: International Conference on Service Systems and Service Management, pp. 1–6. IEEE (2017)
Leng, K., Bi, Y., Jing, L., et al.: Research on agricultural supply chain system with double chain architecture based on blockchain technology. Futur. Gener. Comput. Syst. (2018)
Yang, T.H., Chu, B.J.: Study on control system of food safety from farm to table. Food Sci. 26(3), 264–268 (2005)
Ye, Y.: Research on Technology for Optimizing Agricultural Product Quality Traceability System. South Agricultural University, Guangzhou (2016)
Fu, Z., Xing, S.H.: Development trend of food quality safety traceability technology. Trans. Chin. Soc. Agric. Mach. 44(7), 144–153 (2013)
Poumeyrol, G., Rosset, P., Noel, V., Morelli, E.: HACCP methodology implementation of meat pâté hazard analysis in pork butchery. Food Control 21(11), 1500–1506. ISSN 0956-7135. https://doi.org/10.1016/j.foodcont.2010.03.017
Liu, S.C., Zhao, C.J., Yang, X.T., et al.: Microbiological hazard analysis and critical control points in the processing of chilled pork. Food Sci. (2013)
Cao, W., Zheng, L., Zhu, H., et al.: General framework for animal food safety traceability using GS1 and RFID. In: Computer and Computing Technologies in Agriculture III, Third IFIP TC 12 International Conference, CCTA 2009, Beijing, China, October 14–17, 2009, Revised Selected Papers, pp. 297–304. DBLP (2009)
Lu, H., Li, Y., Chen, M., Kim, H., Serikawa, S.: Brain intelligence: go beyond artificial intelligence. Mob. Netw. Appl. 23(2), 368–375 (2018)
Lu, H., Li, Y., Uemura, T., Kim, H., Serikawa, S.: Low illumination underwater light field images reconstruction using deep convolutional neural networks. Futur. Gener. Comput. Syst. 82 (2018)
Lu, H., Li, Y., Mu, S., Wang, D., Kim, H., Serikawa, S.: Motor anomaly detection for unmanned aerial vehicles using reinforcement learning. IEEE Internet Things J. PP(99), 1 (2017)
Ge, W., Zhao, C.: State-of-the-art and developing strategies of agricultural internet of things. Trans. Chin. Soc. Agric. Mach. 45(7), 222–230+277 (2014)
Chen, X.D., Yuan, X.Y., Guo, P.Y., et al.: Progress and prospect in agricultural internet of things. J. Agric. Sci. Technol. (2015)
Yan, B., Shi, P., Huang, G.: Development of traceability system of aquatic foods supply chain based on RFID and EPC internet of things. Trans. Chin. Soc. Agric. Eng. 29(15), 172–183 (2013)
Jiang, L.H., Yan, S.Q., Xie, J., et al.: Design of traceability system for the safety production entire processes of pork. Sci. Technol. Food Ind. (2008)
Yuan, Y., Wang, F.Y.: Blockchain: the state of the art and future trends. Acta Automatica Sinica (2016)
Underwood, S.: Blockchain beyond bitcoin. ACM (2016)
Feng, T.: A quality and safety control system for China’s dairy supply chain based on HACCP & GS1. In: International Conference on Service Systems and Service Management, pp. 1–6. IEEE (2016)
Tian, F.: An information system for food safety monitoring in supply chains based on HACCP, blockchain and Internet of things. Doctoral thesis, WU Vienna University of Economics and Business (2018)
Foroglou, G., Tsilidou, A.L. Further applications of the blockchain. In: Student Conference on Managerial Science and Technology (2015)
Barcelo, J.: USER Privacy in the Public Bitcoin Blockchain (2014)
Acknowledgements
The research presented in this paper is supported by State Key Program for Research and Development of China (2016YFD0401205) and Beijing Science and Technology Program (Z161100001616004).
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Yuan, Y., Liu, X., Hong, K., Song, S., Gao, W. (2020). Trustworthy Traceability of Quality and Safety for Pig Supply Chain Based on Blockchain. In: Lu, H. (eds) Cognitive Internet of Things: Frameworks, Tools and Applications. ISAIR 2018. Studies in Computational Intelligence, vol 810. Springer, Cham. https://doi.org/10.1007/978-3-030-04946-1_34
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