The global rise in chronic inflammatory diseases has fueled an increased demand for functional beverages containing bioactive compounds with anti-inflammatory properties. This review synthesizes trends in research output, technological innovation, and consumer behavior related to such beverages from 2006 to 2025. A total of 1635 peer-reviewed articles were analyzed using bibliometric tools and content analysis. Results indicate a thirteenfold increase in publications, with China, India, the USA, and Brazil leading in research output. Key themes include polyphenols, curcuminoids, fermentation, encapsulation, and non-thermal processing. The review identifies four major research clusters: antioxidant mechanisms, metabolic and cytokine regulation, plant-derived flavonoids, and phytochemical profiling. Consumer behavior analysis reveals that taste, clean-label appeal, and health claims influence market success. While technological advances such as nanoencapsulation and high-pressure processing improve bioavailability and sensory quality, gaps persist in clinical validation and regulatory harmonization. This study offers integrated insights for researchers, industry professionals, and policymakers to guide innovation and evidence-based development of anti-inflammatory functional beverages.

Accurate classification of marine species is critical for sustainable fisheries management, biodiversity conservation, and aquaculture optimization. This study leverages remote sensing data and a Kolmogorov–Arnold Networks-enhanced ResNet (ResNet-KAN) model to classify fish, shrimp, and seaweed distributions with high precision. A multi-spectral feature set, including sea surface temperature, chlorophyll concentration, oxygen availability, and salinity gradients, was utilized to enhance classification performance. Through an ablation study, temperature was identified as a key determinant, with its removal causing a 14.3% accuracy drop for fish and shrimp. Similarly, omitting chlorophyll concentration led to an 11.8% increase in seaweed misclassification, highlighting its role in distinguishing autotrophic from heterotrophic organisms. The proposed ResNet-KAN model demonstrated superior performance compared to conventional deep learning architectures, achieving an overall classification accuracy of 94.6%. Computational efficiency analysis revealed a complexity of \(O\left({N}^{2}L+DL\right)\), with processing times scaling predictably across species categories. These findings underscore the importance of integrating remote sensing-derived environmental predictors for robust marine classification. The proposed approach provides a scalable, high-accuracy solution for marine resource monitoring, with potential applications in ecosystem management and precision aquaculture. Additionally, this study includes an exploration of the economic and nutritional implications of the Free Nutritious Meals (MBG) program in Indonesia, assessing alternative strategies for improving its impact on public health and food security.

This study analyzes the spatiotemporal dynamics of cocoa cultivation areas across 25 Indonesian provinces from 1975 to 2023 using a Random Forest Clustering approach and t-SNE visualization. The analysis identifies five distinct regional clusters that reveal long-term disparities in cocoa development—ranging from areas of consistent decline and stagnation to regions experiencing rapid growth or sharp contraction. These clusters reflect varying local challenges and opportunities linked to land-use change, policy shifts, and environmental conditions. Beyond mapping agricultural trends, the study underscores the importance of managing land-use instability as a form of systemic food loss and highlights opportunities for circular interventions—such as transforming cocoa by-products into organic fertilizer, animal feed, and bioenergy. The resulting cluster-based typology provides a data-driven foundation for region-specific policies aimed at improving resource efficiency, reducing waste, strengthening farmer livelihoods, and advancing national food security within a circular and sustainable food systems framework.