Artificial Intelligence-Powered Optimization and Milk Permeate Upcycling for Innovative Sesame Milk with Enhanced Probiotic Viability and Sensory Appeal

利用人工智能优化和牛奶渗透液升级再造,打造益生菌活力和感官吸引力增强的创新芝麻奶

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作者:Ibrahim A A Abou Ayana, Mohamed R Elgarhy, Fatimah O Al-Otibi, Mohamed M Omar, Mohamed Z El-Abbassy, Salah A Khalifa, Yosra A Helmy, WesamEldin I A Saber

Abstract

Consumer demand for plant-based alternatives drives innovation in nondairy beverages. This study explores the development of a novel sesame milk with enhanced functionality using an artificial neural network (ANN) and milk permeate integration. An ANN model effectively optimized water-based sesame milk (WSM) extraction, maximizing total solids (T.S.) recovery. The ANN model's predicted T.S. yield (99.65%) closely matched the actual value (95.18%), demonstrating its potential for optimizing high-yield production. Furthermore, milk permeate was incorporated (5:1 ratio) to create permeate-based sesame milk (PSM), which supported the growth of lactic acid bacteria, suggesting its potential as a growth medium for future probiotic applications. PSM also displayed superior nutritional value and sensory characteristics compared to WSM. These findings highlight the promise of ANN-powered optimization and milk permeate integration for creating innovative sesame milk alternatives with enhanced probiotic viability and sensory appeal. Future research should focus on ANN optimization of alternative-based-plant milk, including permeate-based sesame milk production, the health benefits of LAB fermentation, and consumer preferences for flavors and textures. Optimizing fermentation and LAB selection remain key for commercial success.

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