Adoption of Blockchain Technology for Enhanced Traceability of Livestock-Based Products
Abstract
:1. Introduction
2. Traceability in the Agri-Food Industry
3. Adaptation of Technology and Policy in the ASEAN Agri-Food Industry
3.1. Radio Frequency Identification (RFID)
3.2. Near Field Communication (NFC)
3.3. Wireless Sensor Networks (WSN)
3.4. Cloud Computing Technology (CCT)
3.5. DNA Barcoding
4. Blockchain Technology
4.1. Blockchain and Traceability System
4.2. Adoption of Blockchain for Agri-Food Traceability in the ASEAN
5. Challenges and Opportunities
- Accessibility: this is a significant challenge because blockchain technology underlies multiple digital technologies, such as IoT, RFID, sensors and actuators, robots, biometric data, and big data [55].
- Matching the physical to the digital: although blockchain can be used to create credibility and highly effective digital assets, participants need to be convinced that it represents what is happening in the physical world. Building robust digital infrastructure of IoT devices, sensors, and on-site integrations is critical for providing physical verification [66].
- Incentives and cooperation: supply chains are networks of diverse participants with widely varying interests. The right incentives need to be provided by way of efficiency gain, improved liquidity, and data security in order to ensure that decision makers will buy in across the entire network [66].
- Gold standards: blockchain technology can be subject to fraud. There needs to be confidence in data inputs and certifying standards in order to ensure that blockchains are not only immutable, but also accurate [66].
- On the other hand, a few opportunity areas have been identified as follows:
- Benefit and cost: while small-scale farmers produce over 80% of commodities in developing countries, they tend to lack access to financial schemes, including insurance [67]. The transparency allowed by blockchain technology can help to minimize corruption, raise social capital [68], and foster effective supply chains based on enhanced reputation. Overall, Perboli et al. [69] suggest that implementation costs for blockchain technology are sustainable and worthy vis-à-vis its benefits.
6. Implications of Blockchain Integration into the Livestock-Based Products Supply Chains in Thailand
- Ranchers record information on animal well-being during the husbandry stage, according to standards such as nutrition, pasture environments, special treatment, and other relevant practices.
- Processors record all standard processes required for quality assurance.
- Retailers provide information on livestock products and product shelf life to consumers.
- Consumers are the end of the chain, and can retrieve information from all previous stages in order to help make the purchase decision.
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Technologies | Advantages | Disadvantages |
---|---|---|
RFID |
|
|
NFC |
|
|
WSN |
|
|
CCT |
|
|
DNA barcoding |
|
|
Characteristics | RFID | NFC | WSN | CCT | DNA Barcoding |
---|---|---|---|---|---|
1. Security | - | ● | - | ● | ● |
2. Traceability | ● | ● | ● | ● | ● |
3. Transparency | - | - | - | ● | - |
4. Decentralization | - | - | - | - | - |
5. Information Sharing | ● | ● | ● | ● | ● |
Ref. No. | Author(s) | Year | Blockchain Technology | Traceability System/Supply Chain Management | Food Supply Chain/ Agriculture |
---|---|---|---|---|---|
[1] | World Health Organization | 2020 | ● | ||
[2] | Caporale et al. | 2001 | ● | ||
[3] | GS1 Thailand | 2019 | ● | ● | ● |
[4] | Aday et al. | 2020 | ● | ||
[5] | OECD | 2001 | ● | ||
[6] | Choi et al. | 2020 | ● | ||
[7] | Seok-beom et al. | 2022 | ● | ||
[8] | Khan | 2021 | ● | ||
[9] | Pal | 2023 | ● | ||
[10] | Sarkar et al. | 2022 | ● | ||
[11] | Research Drive | 2020 | ● | ||
[12] | Jabbar | 2016 | ● | ||
[13] | Ioris | 2016 | ● | ||
[14] | Azzi et al. | 2019 | ● | ||
[15] | Aung and Chang | 2014 | ● | ● | |
[16] | Opara and Mazaud | 2001 | ● | ● | |
[17] | Opara | 2003 | ● | ● | |
[18] | Shankar et al. | 2018 | ● | ● | |
[19] | Bosch et al. | 2018 | ● | ||
[20] | Department of Livestock | 2003 | ● | ||
[21] | FAO and WHO | 2012 | ● | ||
[22] | Food Chain Strategy Division and Food Standards Agency | 2002 | ● | ● | |
[23] | Zheng et al. | 2021 | ● | ● | |
[24] | Iftekhar et al. | 2021 | ● | ● | ● |
[25] | Yong and Montesclaros | 2017 | ● | ||
[12] | Jabbar | 2016 | ● | ||
[26] | Kumperščak et al. | 2019 | ● | ● | |
[27] | Tian | 2016 | ● | ● | ● |
[28] | Odintsov et al. | 2021 | ● | ||
[29] | Kelepouris et al | 2007 | ● | ● | |
[30] | Badia-Melis et al. | 2015 | ● | ● | |
[31] | Ortiz | 2006 | ● | ||
[32] | Haselsteiner and Breitfuß | 2016 | ● | ||
[33] | Banerjee et al. | 2020 | ● | ||
[34] | Anand | 2015 | ● | ||
[35] | Attaran | 2017 | ● | ||
[36] | Singh et al. | 2015 | ● | ||
[37] | Tinacci et al. | 2018 | ● | ||
[38] | Zhang et al. | 2019 | ● | ● | |
[39] | Hu et al. | 2018 | ● | ||
[40] | Ahmad et al. | 2021 | ● | ||
[41] | Mougayar | 2016 | ● | ||
[42] | Xu et al. | 2017 | ● | ||
[43] | IBM | 2017 | ● | ||
[44] | Azaria et al. | 2016 | ● | ||
[45] | Casey et al. | 2017 | ● | ||
[46] | Christidis and Devetsikiotis | 2016 | ● | ||
[47] | Condliffe | 2017 | ● | ||
[48] | Sloane and Bhargav | 2021 | ● | ||
[49] | Zhao et al. | 2019 | ● | ● | |
[50] | United Nations Global Compact | 2016 | ● | ||
[51] | Berman | 2018 | ● | ||
[52] | Townsend | 2018 | ● | ||
[53] | EU | 2002 | ● | ||
[54] | Sander at al. | 2018 | ● | ● | ● |
[55] | Kamilaris | 2019 | ● | ● | |
[56] | Caro | 2018 | ● | ● | ● |
[57] | ICT4Ag | 2017 | ● | ||
[58] | AgriDigital | 2018 | ● | ● | |
[59] | Hoffman and Munsterman | 2018 | ● | ● | |
[60] | Bai et al. | 2017 | ● | ● | |
[61] | Hu et al. | 2009 | ● | ● | |
[62] | Lewis and Boyle | 2017 | ● | ● | |
[63] | Patelli and Mandrioli | 2020 | ● | ● | ● |
[64] | Vu and Trinh | 2021 | ● | ● | |
[65] | Thu | 2021 | ● | ● | |
[66] | Sylvester | 2019 | ● | ● | |
[73] | Yuan et al. | 2019 | ● | ||
[74] | Pearson et al. | 2019 | ● | ● | |
[75] | Creydt and Fischer | 2019 | ● | ● | ● |
[70] | Lee et al. | 2017 | ● | ||
[67] | Chinaka | 2016 | ● | ||
[68] | Rejeb | 2018 | ● | ● | |
[69] | Perboli et al. | 2018 | ● | ||
[71] | Mohapatra et al. | 2021 | ● | ● | |
[72] | Neethirajan et al. | 2021 | ● | ● | |
[76] | Surasak et al. | 2019 | ● | ● | ● |
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Kampan, K.; Tsusaka, T.W.; Anal, A.K. Adoption of Blockchain Technology for Enhanced Traceability of Livestock-Based Products. Sustainability 2022, 14, 13148. https://doi.org/10.3390/su142013148
Kampan K, Tsusaka TW, Anal AK. Adoption of Blockchain Technology for Enhanced Traceability of Livestock-Based Products. Sustainability. 2022; 14(20):13148. https://doi.org/10.3390/su142013148
Chicago/Turabian StyleKampan, Khwanchol, Takuji W. Tsusaka, and Anil Kumar Anal. 2022. "Adoption of Blockchain Technology for Enhanced Traceability of Livestock-Based Products" Sustainability 14, no. 20: 13148. https://doi.org/10.3390/su142013148
APA StyleKampan, K., Tsusaka, T. W., & Anal, A. K. (2022). Adoption of Blockchain Technology for Enhanced Traceability of Livestock-Based Products. Sustainability, 14(20), 13148. https://doi.org/10.3390/su142013148