The proposed methodology can effectively account for the complex interactions and interdependencies between various digital agriculture technologies and their required infrastructures through a systematic and functionalist approach. This involves several key steps:
Functional Analysis: By adopting a functionalist perspective, the methodology can categorize different digital agriculture technologies based on the specific functions they serve (e.g., monitoring, data analysis, automation). This allows for a comparative assessment of how different technologies can fulfill similar agricultural needs.
Systemic Modeling: The development of parametric models that simulate the interactions between various ICT systems and their infrastructures can help visualize and analyze the interdependencies. These models can incorporate variables such as data flow, energy consumption, and resource allocation, providing insights into how changes in one technology may affect others.
Boundary Definition: Clearly defining the boundaries of the assessment is crucial. This includes identifying the geographical area, agricultural systems, and temporal perspectives involved. By establishing these boundaries, the methodology can focus on relevant interactions and avoid oversimplification.
Case Studies: Utilizing real-world case studies to gather data on existing digital agriculture implementations can provide empirical evidence of interactions and interdependencies. Field surveys and inventory studies can help identify how different technologies coexist and influence each other in practice.
Multi-Indicator Assessment: Incorporating a range of environmental indicators, as previously discussed, allows for a holistic evaluation of the impacts of interconnected technologies. This multi-faceted approach ensures that the assessment captures the complexity of digital agriculture systems.
By integrating these elements, the proposed methodology can provide a comprehensive understanding of the environmental impacts of digital agriculture technologies, considering their interrelated nature and the broader implications for sustainability.