Hybridization in Meat-Based Dual Protein Foods: Mechanisms, Challenges, and Consumer Insights.

As the global demand for protein-rich foods continues to rise, developing innovative solutions to enhance sustainability and nutritional quality in meat production has become increasingly important. Meat is a tasty source of high-quality protein and micronutrients, whose integration with alternative proteins offers new avenues to address technical and consumer-driven challenges. Meat-based hybrids, also called dual-protein foods, combine meat with alternative proteins like plant proteins, edible insects, microalgae, and nutritional yeast, offering a promising solution by improving resource efficiency while retaining familiar taste and nutritional benefits of meat. However, challenges remain regarding protein compatibility, functionality, and consumer acceptance. This review critically examines recent advances in hybridizing meat with alternative proteins, highlighting the pivotal roles of pH, temperature, and salt concentration in modulating protein-protein interactions and functionalities essential for cohesive hybrid systems. Emerging protein combinations, such as plant-yeast or microalgae-yeast blends, offer promising but underexplored opportunities in hybrid systems to enhance nutritional value and functional performance. Additionally, this review synthesizes recent consumer studies, highlighting that taste, texture, visual appeal, perceived nutritional and environmental benefits are primary drivers of acceptance and willingness to pay for hybrid products. Processing technologies, including high-moisture extrusion, high-pressure treatments, and ultrasound, are discussed for their potential to improve hybrid product quality through structural modification. Finally, this review introduces the HYBRID meat framework-a holistic systems-based roadmap for innovating dual-protein meat products by integrating raw materials, hybridization mechanisms, processing, consumer insights, and enabling tools like artificial intelligence and machine learning to guide future innovations in meat-based dual-protein foods.