Meat-Borne Bacterial Pathogen Detection: Conventional, Molecular and Emerging AI-Based Strategies
Athar Hussain, Qindeel Abbas, Muhammad Nadeem, Aquib Nazar, Ali Athar, Hafiz Ubaid Ur Rahman · 2026
Read Meat-Borne Bacterial Pathogen Detection: Conventional, Molecular and Emerging AI-Based Strategies by Athar Hussain, Qindeel Abbas, Muhammad Nadeem, Aquib Nazar, Ali Athar, Hafiz Ubaid Ur Rahman (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13164157.txt.
Description
Athar Hussain and co-authors review ways to find germs in meat in a paper from 2026. Meat is rich in protein and water, so germs grow fast and cause much food-borne illness. The review covers the main germs of concern, from Salmonella to Listeria and Campylobacter.
Older lab tests are set next to newer DNA-based tools. The newer set includes CRISPR tests, fast copying methods, and full gene scans of a sample. Sensors that give quick readouts get close study too. A final part looks at how AI can read signals and images on its own. Food plants can weigh speed, cost, and trust for each method.
Catalog record
| CREATOR | Athar Hussain, Qindeel Abbas, Muhammad Nadeem, Aquib Nazar, Ali Athar, Hafiz Ubaid Ur Rahman |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 104 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |