Date Received: 11-08-2025
Date Accepted: 12-03-2026
Date Published: 27-05-2026
##submissions.doi##: https://doi.org/10.31817/tckhnnvn.2026.24.5.10
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Theoretical Perspectives on the Application of Digital Technology in Agriculture
Keywords
Digital technology, digital transformation in agriculture, digital agriculture, sustainable agriculture
Abstract
This paper focused on systematizing the theoretical issues related to the application of digital technologies in agriculture. The study employeda comprehensive review combined with content analysis and synthesis of studies on digital agriculture. The findings indicated that digital technologies in agriculture should not be viewed as a collection of standalone technical solutions but as an integrated system in which data play a central role, connecting technologies such as IoT, AI, Big Data, UAVs, and Blockchain along the agricultural value chain. Digital technologies can be functionally categorized into three main groups: enhancing production efficiency, strengthening resilience to risks, and promoting sustainable agricultural development. The application of digital technologies in agriculture is influenced by multiple factors, including institutional and policy frameworks, digital infrastructure, farmers’ capabilities, investment costs, natural conditions, and coordination mechanisms among stakeholders. The study provides a theoretical foundation for developing analytical frameworks and suggests directions for future empirical research to inform policies that promote effective and sustainable digital transformation in agriculture.
References
Araújo S.O., Peres R.S., Barata J., Lidon F. & Ramalho J.C. (2021). Characterising the Agriculture 4.0 Landscape-Emerging Trends, Challenges and Opportunities. Agronomy. 11: 667. Casino F., Dasaklis T.K. & Patsakis C. (2019). A systematic literature review of blockchain-based applications: Current status, classification and open issues. Telematics and Informatics. 36: 55-81. https://doi.org/10.1016/j.tele.2018.11.006. Chính phủ (2020). Quyết định số 749/QĐ-TTg Phê duyệt “Chương trình Chuyển đổi số quốc gia đến năm 2025, định hướng đến năm 2030”. Clapp J. & Ruder S.L. (2020). Precision technologies for agriculture: digital farming, gene-edited crops, and the politics of sustainability Global Environ. Polit. 20(3): 49-69. Connolly A. (2022). 10 Digital Technologies That Are Transforming Agriculture. Retrieved from https://www.forbes.com/sites/forbestechcouncil/2022/04/26/10-digital-technologies-that-are-transforming-agriculture/?sh=640472857baf. on Oct 20, 2022. Eastwood C., Klerkx L., Ayre M. & Dela Rue B. (2019). Managing Socio-Ethical Challenges in the Development of Smart Farming: From a Fragmented to a Comprehensive Approach for Responsible Innovation. Journal of Agricultural and Environmental Ethics. 32: 741-768. https://doi.org/10.1007/s10806-017-9704-5. FAO (2021). Digital Agriculture Report. Rome: Food and Agriculture Organization of the United Nations. https://doi.org/10.4060/cb4476en. Ghimire R. (2019). Rural development and technology: Opportunities and challenges. Development Studies Quarterly. Hossain M.S., Muhammad G. & Alamri A. (2020). Smart agriculture: Sustainable energy, precision agriculture, and security challenges. IEEE Communications Magazine. 58(10): 88-93. https://doi.org/10.1109/MCOM.001.2000267. Jiang, Z. (2020). Climate-adaptive technologies for agriculture: Integrating digital solutions. Environmental Sustainability in Agriculture. Kamilaris A. & Prenafeta-Boldú F.X. (2018). Deep learning in agriculture: A survey. Science Direct. 147: 70-90. doi.org/10.1016/j.compag.2018.02.016. Klerkx L. & Rose D. (2020). Dealing with the game-changing technologies of Agriculture 4.0: How do we manage diversity and responsibility in food system transition pathways? Global Food Security. 24: 100347. doi.org/10.1016/j.gfs.2019.100347. Klerkx L., Jakku E. & Labarthe P. (2019). A review of social science on digital agriculture. NJAS - Wageningen Journal of Life Sciences. Lajoie-O’Malley K.. Bronson S. & van der Burg L. Klerkx (2020). The future(s) of digital agriculture and sustainable food systems: an analysis of high-level policy documents Ecosystem Services. 45: Article 101183, 10.1016/j.ecoser.2020.101183. Liakos K.G., Busato P., Moshou D., Pearson S. & Bochtis D. (2018). Machine Learning in Agriculture: A Review. Sensors. 18(8): 2674. https://doi.org/10.3390/s18082674 Lin Q., Wang H., Pei X. & Wang J. (2021). Food safety traceability system based on blockchain and EPCIS. IEEE Access. 7: 20698-20707. https://doi.org/10.1109/ACCESS.2019.2892070. Liu Y. (2020). The role of internet connectivity in advancing agricultural productivity. Information Systems for Agriculture.
Luu Van Duy & Le Thi Thu Huong (2025). Determinants of Farmers’ Understanding of Digital Transformation in Agriculture: Evidence from the Red River Delta, Vietnam. Asian Journal of Agriculture and Development. 22(1): 57-74. https://doi.org/10.37801/ajad2025.22.1.4.
Lưu Văn Duy & Đỗ Kim Chung (2024). Chuyển đổi số trong nông nghiệp: Những vấn đề lý luận và một số đề xuất cho tỉnh Thái Bình. Tạp chí Nghiên cứu Kinh tế. 7(554): 97-108.
Lưu Văn Duy, Hà Thị Thanh An & Vũ Khánh Toàn (2025). Thực trạng chuyển đổi số trong sản xuất nông nghiệp ở tỉnh Thái Bình. Tạp chí Khoa học & Công nghệ Việt Nam. 67(4): 28-34.
Lưu Văn Duy, Nguyễn Hữu Nhuần, Nguyễn Thị Thu Quỳnh, Nguyễn Minh Đức, Trần Mạnh Hải & Hồ Ngọc Cường (2022). Chuyển đổi số trong nông nghiệp và hàm ý chính sách cho Việt Nam. Tạp chí Khoa học & Công nghệ Việt Nam. Mehmet & Ufuk (2021). Digital Transformation for Sustainable Future - Agriculture 4.0: A review. Journal of Agricultural Sciences. 27(4): 373-399. Miles C. (2019). The combine will tell the truth: on precision agriculture and algorithmic rationality. Big Data & Society. Parra-López C., Abdallah C.B., Garcia-Garcia G., Hassoun A., Sánchez-Zamora P., Trollman H., Jagtap S. & Carmona-Torres C. (2024). Integrating digital technologies in agriculture for climate change adaptation and mitigation: State of the art and future perspectives. Computers and Electronics in Agriculture. 226: 109412. https://doi.org/10.1016/j.compag.2024.109412. Rose D.C., Parker C. & Maynard D.S. (2021). Data governance in agriculture: Towards a new research agenda. Journal of Rural Studies. 82: 481-490. https://doi.org/10.1016/j.jrurstud.2021.01.004. Rotz S., Gravely E., Mosby I., Duncan E., Finnis E., Horgan M., LeBlanc J., Martin R., Neufeld H.T., Nixon A., Pant L., Shalla V. & Fraser E.D.G. (2021). Automated pastures and the digital divide: How agricultural technologies are shaping labor and rural communities. Journal of Rural Studies. 82: 176-187. doi.org/10.1016/j.jrurstud.2020.08.004. Shamshiri R.R., Kalantari F., Ting K.C., Thorp K.R., Hameed I.A., Weltzien C. & Balasundram, S.K. (2018). Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture. International Journal of Agricultural and Biological Engineering. 11(1): 1-22. https://doi.org/10.25165/j.ijabe.20181101.3210. Tian F. (2017). A supply chain traceability system for food safety based on HACCP, blockchain & Internet of things. 2017 International Conference on Service Systems and Service Management (ICSSSM). pp. 1-6. doi.org/10.1109/ICSSSM.2017.7996119. Wolfert S., Ge L., Verdouw C. & Bogaardt M.J. (2017). Big Data in Smart Farming - A review. Agricultural Systems. 153: 69-80. Zhang Y., Wang G. & Wang J. (2020). Precision Agriculture - a worldwide overview. Computers and Electronics in Agriculture. 178: 105759. https://doi.org/10.1016/j.compag.2020.105759.