<![CDATA[The role of fractal geometry in analyzing growth patterns of tropical plants and its application in precision agriculture has become an emerging interdisciplinary topic in the modern era. Tropical plants often exhibit complex and irregular structures that cannot be fully described by conventional Euclidean geometry. This study aims to examine fractal-based mathematical models to identify self-similar patterns in tropical leaves and to explore their potential for optimizing precision farming practices. The methodology employs image-based mathematical analysis, using digital images of tropical plants to measure fractal dimensions and quantify growth complexity. The findings reveal that consistent fractal patterns can be observed across different species of tropical plants, particularly in leaf venation and branching structures, indicating a universal growth principle. Such patterns demonstrate high predictive potential for estimating biomass, monitoring plant health, and assessing responses to environmental changes. Furthermore, the study highlights how fractal-based approaches, when combined with precision agriculture technologies, can improve resource efficiency by supporting accurate irrigation scheduling, soil quality monitoring, and yield forecasting. The implications extend to sustainable agricultural development, as fractal analysis provides a scientific foundation for balancing productivity with environmental preservation. In conclusion, this research underscores the significance of fractals not only as mathematical concepts but also as powerful analytical tools with practical benefits, offering new pathways to advance digital farming, ecological monitoring, and sustainable food security in the modern era.]]>
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