Connecting Sustainability and Agricultural Strategy With Digital Twin Technology: Sustainable Agriculture Digital Twin Framework
Abstract
The agricultural sector faces an escalating strategic challenge: reconciling the imperative to increase food production with the need to mitigate environmental impacts amid accelerating climate change. Although Digital Twin (DT) technology is a promising tool for agricultural management, existing models remain anchored in operational optimization, treating sustainability merely as a constrained parameter rather than a core strategic principle. This paper proposes the Sustainable Agriculture Digital Twin Framework (SADTF), a conceptual architecture advancing three original contributions to the smart agriculture literature. First, it models the sustainability-productivity dynamic as a formally defined strategic paradox, operationalizing this inherent tension as a bi-criteria optimization problem with a Pareto-optimal solution space rather than a conventional single-objective trade-off. Second, it introduces a dedicated Sustainability Layer designed exclusively to generate trade-off matrices across competing objectives aligned with the United Nations Sustainable Development Goals, marking a fundamental architectural departure from prior agricultural DT models. Third, it advocates a paradigm shift in the DT's role, moving it from an operational instrument to a strategic governance tool. It embeds Life Cycle Management (LCM) as the central mechanism, translating simulation outputs into strategic directives within a continuous PDCA improvement cycle. Developed through a systematic literature review and formally specified using a mathematical data flow pipeline, the framework is demonstrated concretely through a hypothetical soybean production scenario. Ultimately, the SADTF establishes a structured foundation for next-generation agricultural systems, moving beyond short-term optimization to govern the strategic transition toward practices that reconcile high productivity with long-term environmental sustainability.
Fields of Study & Subjects
Digital Transformation in Industry
Smart Agriculture and AI
IoT and Edge/Fog Computing
Publication details
- Journal / source
- IEEE Access
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- 14
- Pages
- 72799–72817
- Publication date
- 1 January 2026
- Language
- EN