Guo Bingbing, Lu Xingyu, Jiang Xiaoyu, Shen Xiao-Li, Wei Zihao, Zhang Yifeng
College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China.
School of Public Health, Zunyi Medical University, Zunyi 563000, China.
Foods. 2025 May 17;14(10):1783. doi: 10.3390/foods14101783.
Microalgae are capable of synthesizing a diverse range of biologically active compounds, including omega-3 fatty acids, carotenoids, proteins, and polysaccharides, which demonstrate significant value in the fields of functional foods, innovative pharmaceuticals and high-value cosmetics. With advancements in biotechnology and the increasing demand for natural products, studies on the functional components of algae have made significant strides. However, the commercial utilization of algal bioactives still faces challenges, such as low cultivation efficiency, limited component identification, and insufficient health evaluation. Artificial intelligence (AI) has recently emerged as a transformative tool to overcome these technological barriers in the production, characterization, and application of algal bioactive ingredients. This review examines the multidimensional mechanisms by which AI enables and optimizes these processes: (1) AI-powered predictive models, integrated with machine learning algorithms (MLAs), Industry 4.0, and other advanced digital systems, support real-time monitoring and control of intelligent bioreactors, allowing for accurate forecasting of cultivation yields and market demand. (2) AI facilitates in-depth analysis of gene regulatory networks and key metabolic pathways, enabling precise control over the biosynthesis of targeted compounds. (3) AI-based spectral imaging and image recognition techniques enable rapid and reliable identification, classification, and quality assessment of active components. (4) AI accelerates the transition from mass production to the development of personalized medical and functional nutritional products. Collectively, AI demonstrates immense potential in enhancing the yield, refining the characterization, and expanding the application scope of algal bioactives, unlocking new opportunities across multiple high-value industries.
微藻能够合成多种生物活性化合物，包括omega-3脂肪酸、类胡萝卜素、蛋白质和多糖，这些化合物在功能性食品、创新药物和高价值化妆品领域具有重要价值。随着生物技术的进步和对天然产品需求的增加，对藻类功能成分的研究取得了重大进展。然而，藻类生物活性物质的商业利用仍面临挑战，如培养效率低、成分鉴定有限和健康评估不足。人工智能（AI）最近已成为一种变革性工具，可克服藻类生物活性成分生产、表征和应用中的这些技术障碍。本综述探讨了人工智能实现和优化这些过程的多维度机制：（1）由人工智能驱动的预测模型，与机器学习算法（MLA）、工业4.0和其他先进数字系统集成，支持对智能生物反应器的实时监测和控制，从而准确预测培养产量和市场需求。（2）人工智能有助于深入分析基因调控网络和关键代谢途径，从而精确控制目标化合物的生物合成。（3）基于人工智能的光谱成像和图像识别技术能够快速、可靠地识别、分类和评估活性成分的质量。（4）人工智能加速了从大规模生产到个性化医疗和功能性营养产品开发的转变。总体而言，人工智能在提高藻类生物活性物质的产量、完善其表征和扩大其应用范围方面显示出巨大潜力，为多个高价值行业带来了新机遇。
