Artificial intelligence and machine learning applications for cultured meat
Fuente:
arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866912082797002752 |
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| author | Todhunter, Michael E. Jubair, Sheikh Verma, Ruchika Saqe, Rikard Shen, Kevin Duffy, Breanna |
| author_facet | Todhunter, Michael E. Jubair, Sheikh Verma, Ruchika Saqe, Rikard Shen, Kevin Duffy, Breanna |
| contents | 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. 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_09982 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Artificial intelligence and machine learning applications for cultured meat Todhunter, Michael E. Jubair, Sheikh Verma, Ruchika Saqe, Rikard Shen, Kevin Duffy, Breanna Computers and Society Artificial Intelligence 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. 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. |
| title | Artificial intelligence and machine learning applications for cultured meat |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2407.09982 |