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Artificial intelligence-enabled cellular Agriculture: Multiscale modeling, process optimization, and future directions

delete2025-07-30
delete0
PRE
AI
高
高文丽 (Wenli Gao)
R
Runnan Bai
凌
凌盛杰 (Shengjie Ling) *
DOI：10.1016/j.tifs.2025.105193delete
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Abstract

Abstract

En 中文
• AI enables predictive modeling across culture media, tissue structure, and nutrition. • Digital twin systems dynamically optimize cell–scaffold–bioreactor interactions. • Graph neural networks map cellular differentiation and metabolic heterogeneity. • Machine learning enhances flavor, texture, and nutritional profile prediction. • Multimodal AI and explainable modeling are shaping intelligent cellular agriculture.
Keywords:
AI
digital twin
graph neural networks
machine learning
cellular agriculture

Journal

T
Trends in Food Science and Technology
IF:
15.4
Papers:
5.0K
Citations:
5.6W

Organization

A
Anhui Agricultural University
Scholars:
1.2W
Papers: 5.7K
Citations: 1.0W
F
fudan university
Scholars:
11.7W
Papers: 7.7W
Citations: 121
S
ShanghaiTech University
Scholars:
9.6K
Papers: 5.9K
Citations: 1.6W
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