AI-Based Decision Support System for Sustainable Agriculture in Cyprus: Integrating Data Analytics and Resource Optimization

Abstract

Agriculture in the Mediterranean regions is exposed to the pressures of climate change, limited water resources and the need for more efficient of production systems. Cyprus represents a relevant example due to the pronounced scarcity of water, the fragmented structure of farms and the significant role of irrigation in crop production. Digital technologies and artificial intelligence can contribute to the development of more efficient decision support systems in sustainable agriculture. This paper proposes a conceptual AI-based decision support system (AI-DSS) for sustainable agriculture in Cyprus, which links the analysis of agricultural data with the logic of resource allocation optimization. The proposed framework is based on publicly available and verified statistical data from the CYSTAT, Eurostat and FAOSTAT databases, while the optimization component is conceptually connected to the General Algebraic Modelling System (GAMS) platform in order to illustrate the possibility of distributing limited water resources within a decision support system.

The research relies on official data on farm structure, land use, irrigation and production of key crops in Cyprus, with a particular focus on potatoes, citrus, grapes and olives as representative crops for analytical and optimization purposes. Analytical scenarios of different levels of water availability were developed to examine how the proposed system could support adaptive planning of agricultural production under conditions of increased resource pressure. The results confirm that Cypriot agriculture combines a small average farm size with a significant dependence of certain crops on irrigation, which makes water distribution one of the key sustainability issues of the sector. The proposed AI-DSS framework shows how official statistical data, analytical processing and optimization-oriented reasoning can be combined into a single structure for decision support.