人工智能驱动的优化和牛奶透再循环,为创新的芝麻牛奶提供增强的益生菌活力和感官吸引力
Ibrahim A A Abou Ayana1, Mohamed R Elgarhy1, Fatimah O Al-Otibi2
1Dairy Research Department, Food Technology Research Institute (FTRI), Agricultural Research Center, Giza 12619, Egypt.
ACS omega
|June 17, 2024
概括
研究人员使用人工神经网络 (ANN) 和乳透剂开发了一种新的芝麻牛奶. 这一创新提高了生产产量,并为改善营养和味道的益生菌饮料创造了有希望的基础.
科学领域:
- 食品科学与技术 食品科学与技术
- 生物技术是生物技术.
- 乳制品科学 乳制品科学
背景情况:
- 越来越多的消费者对植物性非乳制品饮料的需求推动了创新.
- 芝麻奶是一个潜在的替代品,但需要优化以提高功能.
- 作为乳制品副产品的乳透,为新的食品应用提供了营养潜力.
研究的目的:
- 使用人工神经网络 (ANN) 优化开发一种新的,功能性的芝麻奶.
- 调查牛奶透物的整合,以提高芝麻牛奶的生产.
- 评估基于透性的芝麻奶 (PSM) 在益生菌应用中的潜力.
主要方法:
- 人工神经网络 (ANN) 建模以优化基于水的芝麻奶 (WSM) 提取总固体 (TS) 的提取. 恢复,恢复,恢复,恢复.
- 在5:1的比例上将乳透与WSM集成,以创建基于透的芝麻牛奶 (PSM).
- 对乳酸细菌 (LAB) 的生长,营养价值和感官特征进行PSM的评估.
主要成果:
- 安恩模型准确地预测和优化了TS. 在WSM的收益率 (预测为99.65%,实际为95.18%).
- PSM配方支持乳酸细菌的生长,表明益生菌的潜力.
- 与WSM相比,PSM的营养含量和感官属性都更高.
结论:
- 基于ANN的优化和牛奶透集成是开发创新的芝麻牛奶替代品的有效策略.
- 对于增强益生菌活力和改善感官吸引力,PSM显示出显著的前景.
- 对ANN优化,LAB发酵和消费者偏好进行进一步的研究对于商业化至关重要.
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