Editorial: Innovative and sustainable management of organic food and beverage wastes

anaerobic decomposition generates CH4, a GHG with a GWP 28 times that of CO2 per unit mass over a 100-year horizon (Yip, Cook et al. 2025).The food recovery hierarchy provides a well-established framework for prioritizing foodwaste management strategies based on environmental, economic, and social benefits placing prevention and food donation at the top of preferred interventions. Within this framework, the healthcare sector offers a representative example of practical implementation challenges, as food waste from patient services and retail operations can account for up to 20-30% of total hospital waste. Evidence from hospital food services (Yip et al., 2025) shows that the GHG emission reduction potential varies substantially across management options, with donation offering the highest relative benefits but is constrained by the availability of surplus edible food, whereas composting and anaerobic digestion enable the treatment of large and heterogeneous waste streams underscoring the need for integrated strategies that balance environmental performance with operational constraints (Yip, Cook et al. 2025).Artificial intelligence (AI) and digital technologies are emerging as transformative tools for reducing food waste generation and management. While traditional lean management approaches like "Value Stream Mapping" have been useful for expert-driven diagnostics, AI extends these capabilities through real-time, scalable, and automated analysis across supply chains (Girotto and Beggio 2025). Digital and analytical innovations operate across multiple, interconnected levels, supporting prevention and redistribution decisions, industrial process optimization, and fine-scale tuning of valorization operations. However, widespread adoption remains hindered by fragmented data infrastructures, elevated costs, and uneven digital readiness.Where data availability or system complexity limits the application of advanced machine learningbased optimization tools, advanced mathematical modeling approaches still play a crucial role in optimizing upcycling processes. However, in specific applications, AI-assisted approaches have been shown to enhance process optimization beyond conventional statistical methods. Xiao et al. (2025) applied an artificial neural network-genetic algorithm (ANN-GA) framework to optimize extraction parameters for plant protein recovery from safflower seed meal, outperforming RSM (Xiao, Wang et al. 2025). Similar data-driven optimization principles are increasingly being explored across other valorization domains, including biological and energy recovery technologies.Frontier technologies are expanding the possibilities for energy recovery from the organic waste fraction. Bioelectrochemical and solar-driven reforming technologies are emerging as pathways for energy recovery from organic food waste, enabling the conversion of organic substrates into hydrogen or electricity. Despite their potential for low-carbon energy production, these technologies remain largely at the pre-commercial stage, facing challenges related to scaleup, process stability, and techno-economic feasibility (Girotto and Beggio 2025). Traditional waste-to-energy approaches, including anaerobic digestion, continue to evolve, while insect-based upcycling enables the biological conversion of organic waste into protein-and lipid-rich biomass for feed, biofuels, and high-value compound recovery (Girotto and Beggio 2025).Lignocellulosic residues from fruit and vegetable processing, including peels, pomace, husks, wheat straw, and bagasse, have strong potential as reinforcing agents in polymer or cementitious matrices, contributing to improved mechanical performance and enhanced end-oflife degradability (Frumuzachi, Nicolescu et al. 2025, Girotto andBeggio 2025). This potential can be further optimized through chemical or physical treatments of natural fibers and the incorporation of nanofillers, which enhance interfacial adhesion with matrix materials and improve tensile strength, impact resistance, and thermal stability. As a result, these biocomposites are increasingly explored for applications in sustainable packaging, automotive interior components, construction materials, and 3D-printed prototypes. However, the absence of unified material standards limits commercial adoption (Girotto and Beggio 2025). Proteinaceous by-products such as feathers, fish scales, and dairy residues represent additional renewable resources, providing keratin, casein, and collagen as functional additives or reinforcing agents.The conversion of slaughterhouse by-products into biomaterials for regenerative medicine represents a paradigm shift in waste valorization. Corridon et al. (2025) proposed a hypothesis-driven strategy for developing sustainable keratoplasty models by repurposing bovine, porcine, or ovine corneal tissues and bladder-derived urine stem cells (USCs) from meatprocessing waste. This strategy addresses the critical global shortage of donor corneas, with only one donor cornea available for every 70 patients requiring transplantation worldwide (Corridon, Mobin et al. 2025). (v) investigation of cascade approaches that anticipate and valorize secondary waste streams generated during primary valorization processes.