Artificial intelligence and machine learning applications for cultured meat.

IF 3 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Frontiers in Artificial Intelligence Pub Date : 2024-09-24 eCollection Date: 2024-01-01 DOI:10.3389/frai.2024.1424012
Michael E Todhunter, Sheikh Jubair, Ruchika Verma, Rikard Saqe, Kevin Shen, Breanna Duffy
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Abstract

Cultured meat has the potential to provide a complementary meat industry with reduced environmental, ethical, and health impacts. However, major technological challenges remain which require time-and resource-intensive research and development efforts. Machine learning has the potential to accelerate cultured meat technology by streamlining experiments, predicting optimal results, and reducing experimentation time and resources. However, the use of machine learning in cultured meat is in its infancy. This review covers the work available to date on the use of machine learning in cultured meat and explores future possibilities. We address four major areas of cultured meat research and development: establishing cell lines, cell culture media design, microscopy and image analysis, and bioprocessing and food processing optimization. In addition, we have included a survey of datasets relevant to CM research. This review aims to provide the foundation necessary for both cultured meat and machine learning scientists to identify research opportunities at the intersection between cultured meat and machine learning.

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人工智能和机器学习在养殖肉类中的应用。
养殖肉类有可能成为肉类产业的补充,减少对环境、道德和健康的影响。然而,重大的技术挑战依然存在,需要时间和资源密集型的研发工作。机器学习有可能通过简化实验、预测最佳结果以及减少实验时间和资源来加速养殖肉类技术的发展。然而,机器学习在养殖肉类中的应用还处于起步阶段。本综述涵盖了迄今为止机器学习在肉类养殖中的应用,并探讨了未来的可能性。我们讨论了培养肉研究与开发的四个主要领域:建立细胞系、细胞培养基设计、显微镜和图像分析以及生物加工和食品加工优化。此外,我们还对与中药研究相关的数据集进行了调查。本综述旨在为培养肉和机器学习科学家提供必要的基础,以确定培养肉和机器学习交叉领域的研究机会。
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来源期刊
CiteScore
6.10
自引率
2.50%
发文量
272
审稿时长
13 weeks
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