Helianthus annuus exhibits complex morphological structures, including leaves, stems, and flower heads, which often display self-similarity and multiscale organization. Understanding these patterns is essential for insights into plant development, growth dynamics, and ecological adaptation. Fractal geometry and fractional calculus provide robust frameworks for analyzing such structural complexity and modeling the spatial and temporal dynamics of plant morphology. This work explores the application of fractal measures and fractional-order modeling techniques to Helianthus annuus morphology, emphasizing their ability to capture multiscale patterns, symmetry, and memory effects in growth processes. Different approaches reported in the literature, including fractal dimension estimation and fractional modeling, are conceptually compared in terms of biological interpretability, analytical robustness, and potential applications in plant growth studies. Special attention is given to how non-integer order operators can represent adaptive structural development, variability in leaf and flower arrangement, and complex spatial correlations. Furthermore, the discussion includes potential implications for agricultural optimization and ecological research. The synthesis identifies key methodological trends, advantages, and current limitations of fractal and fractional approaches in plant morphogenesis research. By integrating theoretical frameworks with observed sunflower structures, this work provides a coherent perspective on plant morphology and supports the broader use of advanced mathematical tools in quantitative botany.