<![CDATA[Agricultural systems face increasing challenges related to resource depletion, climate variability, and food insecurity, requiring innovative and sustainable solutions. This study examines the impact of intelligent agriculture on sustainability performance and food security outcomes. A quantitative comparative design was employed, involving several farms categorized into intelligent agriculture adopters and conventional farmers. Data were analyzed using a sliding time-window approach, Structural Equation Modeling (SEM), and predictive machine learning techniques to evaluate direct and mediated effects. The findings reveal that intelligent agriculture significantly improves yield (33% increase), reduces water and fertilizer use (approximately 25%), and decreases production variability by more than 50%. Sustainability performance strongly mediates the relationship between intelligent agriculture and food security, resulting in a 27% improvement in the Food Security Index. These results confirm that intelligent agriculture enhances long-term agricultural resilience and resource efficiency, providing empirical support for policies promoting digital farming technologies to achieve sustainable food systems.]]>
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