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Artificial intelligence for plant-based meat alternatives: Pathways to a sustainable future
Roya Aghagholizadeh1, Mohammad Tarahi2, Pranav Gupta3
1Department of Quality Control, Institute of Cereal Research, Tehran, Iran.
Abstract:
The global shift toward sustainable food systems has accelerated the development of plant-based meat alternatives (PBMAs), which offer substantial environmental and ethical benefits compared to conventional meat. However, the industry continues to face critical challenges in formulation, processing, texture, sensory evaluation, and consumer acceptance. Traditional trial-and-error approaches are resource-intensive, requiring repeated experimentation, high material consumption, and extended development time. In this context, artificial intelligence (AI) has emerged as a transformative tool for PBMA innovation. This review provides a comprehensive, application-oriented overview of AI methodologies in PBMAs, including machine learning, hybrid mechanistic-statistical models, computer-aided molecular design, and advanced data analytics. These approaches are examined in relation to PBMA-specific challenges, such as complex ingredient interactions, multiphase structuring, and sensory optimization. AI applications in process optimization (e.g., extrusion and 3D printing), textural evaluation, and sensory prediction are critically discussed, highlighting both capabilities and limitations. Additionally, we discuss how AI-driven approaches can optimize nutritional profiles and model nutrient bioavailability, thereby enabling the targeted design of functional foods with enhanced health benefits. Furthermore, AI's role in consumer science, including sensory evaluation, acceptance modeling, sentiment analysis, and market prediction, is discussed as a pathway to improving consumer satisfaction and reducing food neophobia. Finally, future research directions are proposed, with emphasis on developing open-access multimodal databases, integrating AI with omics technologies, and advancing AI-enabled sustainability assessments. By bridging food science with computational intelligence, AI has the potential to accelerate PBMA development, enhance product quality, and promote broader consumer adoption, contributing to a more sustainable food system.
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