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• Plant-based protein is considered healthy for human well-being • The green procedure can enhance the extraction yield of protein • Green solvents can produce high yields with an eco-friendly environment • Artificial intelligence and machine learning can advance the green extraction procedure • Protein extraction by the green procedure can promote the circular economy to achieve sustainable development goals Plant-based proteins as alternatives for traditional animal-derived sources have increased due to the rising need for wholesome, sustainable, and environmentally friendly food ingredients. However, more environmentally friendly, data-driven methods are needed to effectively extract, improve the functionality, and use plant proteins on a big scale. By enabling accurate prediction of extraction yields, process behaviour, and energy consumption, artificial intelligence (AI) and machine learning (ML) are becoming potent tools for optimizing green extraction technologies such as membrane filtration, enzymatic treatment, ultrasound-assisted extraction, and natural deep eutectic solvents. These green technologies aid in the development of eco-friendly processes that minimize the use of solvents, shorten processing times, and improve the techno-functional characteristics of proteins. Artificial intelligence drives the advancement of plant-based foods at the industrial scale by enhancing nutritional value, optimizing texture and sensory quality, and improving process monitoring, scalability, and product consistency. Health benefits of plant proteins are better digestibility, fewer allergies, and the supply of bioactive chemicals that help prevent disease. There are still challenges with data accessibility, model generalization, and integrating AI-driven green technologies with various plant matrices. Future perspectives center on creating circular bioeconomy frameworks that are in line with the Sustainable Development Goals (SDGs) and energy-efficient processing technologies.
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Izza Faiz ul Rasool
Hyrije Koraqi
Muhammad Adil
Applied Food Research
South China University of Technology
Leibniz University Hannover
University of Castilla-La Mancha
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Rasool et al. (Fri,) studied this question.
www.synapsesocial.com/papers/6a080acea487c87a6a40cd34 — DOI: https://doi.org/10.1016/j.afres.2026.102131
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