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Life sciences · Journal article
Cabi Reviews · November 4, 2026
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Abstract Obesity is a multifactorial metabolic disorder associated with insulin resistance, type 2 diabetes mellitus, cardiovascular diseases, and chronic low-grade inflammation. Conventional management strategies, including lifestyle modification and pharmacological interventions, remain central; however, their long-term efficacy is often limited by poor adherence, weight regain, and adverse side effects. These constraints have driven increasing interest in preventive, food-based approaches with improved safety and consumer acceptability. Edible flowers have emerged as promising functional ingredients due to their high content of bioactive compounds such as polyphenols, flavonoids, and anthocyanins, which exhibit anti-obesity potential. Evidence from in vitro, in vivo, and in silico studies indicates that floral bioactives, particularly from Rhododendron and Rosa species, modulate key metabolic pathways involved in obesity. These mechanisms include inhibition of digestive enzymes (pancreatic lipase, α-amylase, and α-glucosidase), reduction of nutrient absorption, attenuation of postprandial glycemic responses, regulation of adipocyte differentiation, and improvement of metabolic homeostasis. Advances in artificial intelligence (AI), including molecular docking, machine learning, and nutrigenomics, have enhanced the identification of bioactive-target interactions and supported the design of optimized functional formulations. Additionally, incorporation of floral bioactives into delivery systems such as functional beverages, dairy products, bakery items, and encapsulated formulations improves stability, bioavailability, and consumer acceptance. Challenges remain regarding clinical validation, standardization of bioactive composition, safety evaluation, and regulatory approval, which are essential for successful translation into evidence-based obesity management strategies. This review highlights the anti-obesity potential of Rhododendron and Rosa flowers, emphasizing their bioactive compounds, mechanistic pathways, and emerging AI-assisted applications in functional food development.