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Blockchain Application:The Dairy Supply Chain
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The safety and quality of the food supply chain is of utmost importance to producers, processors, regulators, and consumers. Many foods are tested when harvested and at many intermediate points during their processing, but in the case of the dairy supply chain in the United States (US), the testing labs are often owned by or connected with the producers and processors, creating a potential conflict of interest. The system described in this paper uses blockchain technology as a tool to ensure that the test results from milk analysis cannot be adjusted or changed without the knowledge of the other stakeholders, most notably the regulatory agency. This provides increased protection not just for the consumer but also the producer as a means of protecting their reputation in case of any food-related problems downstream.
Keywords
Blockchain, Dairy, Food Supply Chain.
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- Akkerman, R., Farahani, P., & Grunow, M. (2010), Quality, safety and sustainability in food distribution: A review of quantitative operations management approaches and challenges. OR Spectrum, 32, 863–904. doi:10.1007/s00291-010-0223-2
- American Public Health Association. (2004). Standard methods for the examination of dairy products (17th ed). American Public Health Association.
- Apte, S., & Petrovsky, N. (2016). Will blockcjain technology revolutionize excipient supply chain management? Journal of Excipients Food Chem, 7(3), 76–78.
- Berti, R., & Semprebon, M. (2018). Food traceability in China. European Food and Feed Law Review, 6, 522.
- Bucek, P., Zottl, K., Kyntäjä, J., Trejo, C., Miglior, F., Leclerc, H., .... Bradley, A. (2017). Management of milk recording organizations – current problems and future challenges. In S. Niklitschek et al. (Eds.), A Global Perspecive on Performance Recording and Animal Identification: Proceedings of the 40th ICAR Bienniel Session (pp. 235–258). Puerto Varas, Chile.
- Cabrera, V. E. (2018). Invited review: Helping dairy farmers to improve economic performance utilizing data-deriving decision support tools. Animal, 12(1), 134–144. doi:10.1017/S17551731117001665
- Dabbene, F., Gay, P., & Tortia, C. (2014). Traceability issues in food supply chain management: A review. Biosystems Engineering, 120, 65–80. doi:10.1016/j.biosystemseng.2013.09.006
- Ding, H., Fu, Y., Zheng, L., & Yan, Z. (2019). Determinants of the competitive advantage of dairy supply chains: Evidence from the Chinese dairy industry. International Journal of Production Economics, 209, 360–373. doi:10.1016/j.ijpe.2018.02.013
- Drescher, D. (2017). Blockchain basics. New York, NY: Apress.
- Hermans, K. et al. (2018). Promises and challenges of big data associated with automated dairy cow welfare assessment. In A. Butterworth (Ed.), Animal Welfare in a Changing World (pp. 199–207). CAB International.
- Hevner, A. R., March, S. T., & Park, J. (2004). Design science in information science research. MIS Quarterly, 28, 75–105.
- Hughes, L., Dwivedi, Y., Misra, S., Rana, N., Raghavan, V., & Akella, V. (2019). Blockchain research, practice and policy: Applications, benefits, limitations, emerging research themes and research agenda. International Journal of Information Management, 49, 114–129. doi:10.1016/j.ijinfomgt.2019.02.005
- Indulska, M., & Recker, J. (2010). Design science in IS research: A literature analysis. In S. Gregor (Ed.), Information science foundations: The role of design science (pp. 285). ANU E Press.
- Kshetri, N. (2018). Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80–89. doi:10.1016/j.ijinfomgt.2017.12.005
- Lai, K. (2018, January 30). DEAL: First agricultural commodity blockchain transaction. International Financial Law Review.
- Lambe, C. J., Wittman, C. M., & Spekman, R. E. (2001). Social exchange theory and research on business-tobusiness relational exchange. Journal of Business-toBusiness Marketing, 8(3), 1–36.
- Leng, K., Bi, Y., Jing, L., & Fu, H. C. (2018). Research on agricultural supply chain system with double chain architecture based on blockchain technology. Future Generation Computer Systems, in press. doi:10.1016/j.future.2018.04.061
- Lin, Y. P., Petway, J. R., Anthony, J., Mukhtar, H., Liao, S.-W., Chou, C.-F., & Ho, Y.-F. (2017). Blockchain: The evolutionary next step for ICT e-agriculture. Environments, 4 , 50. doi:10.3390/environments4030050
- Logar, B., & Jeretina, J. (2015). Web advisory tools to support dairy production in Slovenian herds. In Z. Kowalski et al. (Eds.), Performance recording in the genotyped world: Proceedings of the ICAR technical meeting (pp. 73–78). Krakow, Poland.
- Manski, S. (2017). Building the blockchain world: Technological commonwealth or just more of the same? Strategic Change, 26, 511–522. doi:10.1002/jsc.2151
- Min, H. (2019). Blockchain technology for enhancing supply chain resilience. Business Horizons, 62, 35–45. doi:10.1016/j.bushor.2018.08.012
- Monardes, H. (2017). Implementing milk recording and dairy herd management services in developing countries. In S. Niklitschek et al. (Eds.), A global perspecive on performance recording and animal identification: Proceedings of the 40th ICAR Bienniel Session (pp.1–4). Puerto Varas, Chile.
- Monardes, H., Lefebvre, D., Christen, A.-M., Coté, C., & Beaurivage, M. (2017). Implementation of dairy herd services in Ukraine. In S. Niklitschek et al. (Eds.), A global perspecive on performance recording and animal identification: Proceedings of the 40th ICAR Bienniel Session (pp. 31–34). Puerto Varas, Chile.
- Murphy, M. D., Upton, J., & Scully, T. (2018), Machinelearning algorithms for predicting on-farm direct water and electricity consumption on pasture based dairy farms. Computers and Electronics in Agriculture, 150, 74–87. doi:10.1016/j.compag/2018.03.023
- Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Retrieved 2018, July 12 from www.bitcoin.org/bitcoin.pdf
- Park, J. J. et al. (Eds.), Advances in Computer Science and Ubiquitous Computing, Lecture Notes in Electrical Engineering, 474. doi:10.1007/978-981-10-7605-3_185
- Pfaeffle, V. (2019). Stino Da Napoli recalls various meat products produced without benefit of inspection. Retrieved 2019, March 27 from https://www.fsis.usda.gov/wps/portal/fsis/topics/recalls-and-public-health-alerts/recall-case-archive/archive/2019/recall-006-2019-release
- Polim, R., Hu, Q., & Tirupatikumara, S. R. (2017). Blockchain in megacity logistics. In Proceedings of IIE Annual Conference. Institute of Industrial and systems Engineers (IISE), 1589–1594.
- Queiroz, M. M., & Wamba, S. F. (2019). Blockchain adoption challenges in supply chain: An empirical investigation of the main drivers in India and the USA. International Journal of Information Management, 46, 70–82. doi:10.1016/j.ijinfomgt.2018.11.021
- Rajan, N. (2018). 3 of the worst dairy recalls of 2017. Retrieved 2019, March 27 from https://xtalks.com/3-of-the-worst-dairy-recalls-of-2017/
- Regattieri, A., Gamberi, M., & Manzini, R. (2007), Traceability of food products: General framework and experimental evidence. Journal of Food Engineering, 81, 347–356. doi:10.1016/j.jfoodeng.2006.10.032
- Susanty, A., Bakhtiar, A., Jie, F., & Muthi, M. (2017). The empirical model of trust, loyalty, and business performance of the dairy milk supply chain. British Food Journal, 119, 2765–2787. doi:10.1108/BFJ-10-2016-0462
- Tian, F. (2016). An agri-food supply chain traceability for China based on RFID & blockchain technology. In Proceedings of 13th International Conference on Service systems and Service Management (ICSSSM), 1–6.
- Tse, D., Zhang, B., Yang, Y., Cheng, C., & Mu, H. (2017). Blockchain application in food supply information security. In Proceedings of the 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). Singapore.
- United States Food and Drug Administration. (2019). FDA Continues Investigation into Source of E. coli O157:H7 Outbreak Linked to Romaine Lettuce Grown in CA; CDC Reports End to Associated Illnesses. Retrieved 2019, March 27 from https://www.fda.gov/Food/RecallsOutbreaksEmergencies/Outbreaks/ucm626330.htm
- Wang, L., Kwok, S. K., & Ip, W. H. (2010). A radio frequency identification and sensor-based system for the transportation of food. Journal of Food Engineering, 101, 120–129. doi:10.1016/j.jfoodeng.2010.06.020
- Wang, Y. et al. (2019). Making sense of blockchain technology: How will it transform supply chains? International Journal of Production Economics, 211, 221–236. doi:10.1016/j.ijpe.2019.02.002
- Wang, Y., Han, J. H., & Beynon-Davies, P. (2019). Understanding blockchain technology for future supply chains: A systematic literature review and research agenda. Supply Chain Management: An International Journal, 24, 62–84.
- Xie, C., Sun, Y. L., & Luo, H. (2017). Secured data storage scheme based on block chain for agricultural products tracking. In Proceedings of the 3rd International Conference on Big Data Computing and Communications. Chengdu, China. doi:10.1109/BIGCOM.2017.43
- Xu, X., Pautasso, C., Zhu, L., Gramoli, V., Ponomarev, A., Tran, A. B., & Chen, S. (2016). The blockchain as a software connector. Proceedings of the 2016 13th Working IEEE/IFIP Conference on Software Architecture. doi:10.1109/WICSA.2016.21
- Ying, W., Jia, S., & Du, W. (2018). Digital enablement of blockchain: Evidence from the HNA group. International Journal of Information Management, 39, 1–4. doi:10.1016/j.ijinfomgt.2017.10.004
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