迈向智能养殖/养殖肉类工厂:人工智能、3D生物打印和自动化在下一代食品制造中的协同作用

Q1 Computer Science
Saumya Saraswat, Twinkle Bhargava, Juhi Landge, Kamalnayan Tibrewal
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引用次数: 0

摘要

全球人口增长、城市化和收入增长增加了对蛋白质的需求,迫切需要可持续的替代传统畜牧业,这带来了严重的伦理、可扩展性和环境问题。通过在受控环境下培养动物细胞制成的人造肉是一种可能的替代品,可以减少温室气体排放、土地使用和动物痛苦。然而,大规模生产具有与传统肉类相同质地,结构和活力的培养肉仍然具有很高的挑战性。尽管三维(3D)生物打印已经成为一项关键技术,用于精确地制造类肉组织,但现有的系统在自动化、可重复性和吞吐量方面存在障碍。本文研究了主要来自再生医学和组织工程领域的自动化、机器学习(ML)和人工智能(AI)最近(2020-2025)进步的潜力,以及它与大规模培养肉生物打印的相关性。人工智能驱动的过程优化、细胞活力和生长的预测建模、基于传感器的控制系统的实时反馈、材料处理和后处理的机器人集成、自动化生物反应器集成以及公司早期采用人工智能和自动化是一些主要主题。研究强调了其优点,包括减少试错,提高机器人系统的精度,基于计算机视觉的实时打印调整,以及需要更少人工参与的闭环反馈。这些技术为智能化、高通量的“智能生物打印工厂”奠定了基础。该分析通过结合人工智能、机器学习和机器人技术的进步,为可扩展的、负担得起的培养肉生产指明了一条道路,该生产在工业用途和可持续蛋白质供应方面具有重大前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards intelligent cultivated/cultured meat factories: The synergy of AI, 3D bioprinting and automation in next-gen food manufacturing
Global population growth, urbanization, and growing incomes have increased the need for protein, stressing the urgent need for sustainable alternatives to conventional livestock farming, which presents serious ethical, scalability, and environmental issues. Cultured meat, made by culturing animal cells under a controlled environment, is a possible alternative that can lower greenhouse gas emissions, land use, and animal suffering. However, large-scale production of cultured meat with the same texture, structure, and viability as conventional meat remains highly challenging. Even though three-dimensional (3D) bioprinting has become a crucial technique for precisely engineering meat-like, organized tissues, existing systems have hurdles with automation, repeatability, and throughput. The potential of recent (2020–2025) advancements in automation, Machine Learning (ML), and Artificial Intelligence (AI), primarily from the fields of regenerative medicine and tissue engineering, is examined in this paper along with its relevancy to large-scale cultured meat bioprinting.AI-driven process optimization, predictive modelling of cell viability and growth, real-time feedback through sensor-based control systems, robotic integration for material handling and post-processing, automated bioreactor integration, and early company adoption of AI and automation are some of the main topics. Research highlights advantages including less trial-and-error, improved accuracy with robotic systems, computer vision-based real-time print adjustments, and closed-loop feedback that requires less human engagement. The groundwork for intelligent, high-throughput "smart bioprinting factories" is laid by these technologies. This analysis maps out a route toward scalable, affordable cultured meat production with significant promise for industrial use and sustainable protein supply by combining advancements in AI, ML, and robotics.
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来源期刊
Bioprinting
Bioprinting Computer Science-Computer Science Applications
CiteScore
11.50
自引率
0.00%
发文量
72
审稿时长
68 days
期刊介绍: Bioprinting is a broad-spectrum, multidisciplinary journal that covers all aspects of 3D fabrication technology involving biological tissues, organs and cells for medical and biotechnology applications. Topics covered include nanomaterials, biomaterials, scaffolds, 3D printing technology, imaging and CAD/CAM software and hardware, post-printing bioreactor maturation, cell and biological factor patterning, biofabrication, tissue engineering and other applications of 3D bioprinting technology. Bioprinting publishes research reports describing novel results with high clinical significance in all areas of 3D bioprinting research. Bioprinting issues contain a wide variety of review and analysis articles covering topics relevant to 3D bioprinting ranging from basic biological, material and technical advances to pre-clinical and clinical applications of 3D bioprinting.
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