Huang Xiang, Wang Feng, Rehman Obaid Ur, Hu Xinjuan, Zhu Feifei, Wang Renxia, Xu Ling, Cui Yi, Huo Shuhao
School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
School of Life Sciences, Jiangsu University, Zhenjiang 212013, China.
Foods. 2025 Jul 17;14(14):2500. doi: 10.3390/foods14142500.
Microalgal biomass has emerged as a valuable and nutrient-rich source of novel plant-based foods of the future, with several demonstrated benefits. In addition to their green and health-promoting characteristics, these foods exhibit bioactive properties that contribute to a range of physiological benefits. Photoautotrophic microalgae are particularly important as a source of food products due to their ability to biosynthesize high-value compounds. Their photosynthetic efficiency and biosynthetic activity are directly influenced by light conditions. The primary goal of this study is to track the changes in the light requirements of various high-value microalgae species and use advanced systems to regulate these conditions. Artificial intelligence (AI) and machine learning (ML) models have emerged as pivotal tools for intelligent microalgal cultivation. This approach involves the continuous monitoring of microalgal growth, along with the real-time optimization of environmental factors and light conditions. By accumulating data through cultivation experiments and training AI models, the development of intelligent microalgae cell factories is becoming increasingly feasible. This review provides a concise overview of the regulatory mechanisms that govern microalgae growth in response to light conditions, explores the utilization of microalgae-based products in plant-based foods, and highlights the potential for future research on intelligent microalgae cultivation systems.
微藻生物质已成为未来一种有价值且营养丰富的新型植物性食物来源，具有多项已证实的益处。除了其绿色和促进健康的特性外，这些食物还具有生物活性，能带来一系列生理益处。光合自养微藻作为食品来源尤为重要，因为它们能够生物合成高价值化合物。它们的光合效率和生物合成活性直接受光照条件影响。本研究的主要目标是追踪各种高价值微藻物种光照需求的变化，并使用先进系统来调节这些条件。人工智能（AI）和机器学习（ML）模型已成为智能微藻培养的关键工具。这种方法包括持续监测微藻生长，以及实时优化环境因素和光照条件。通过培养实验积累数据并训练AI模型，智能微藻细胞工厂的开发变得越来越可行。本综述简要概述了光照条件对微藻生长的调控机制，探讨了微藻基产品在植物性食物中的应用，并强调了智能微藻培养系统未来研究的潜力。
