Advancing anthracnose resistance in dry beans through the transition from traditional to computational breeding efforts
Aashvi Patel, Sajal Ahlawat, Philip Lorenc, Maryam Vazin, Masoud Maleki, Mohsen Yoosefzadeh Najafabadi · 2026
Read Advancing anthracnose resistance in dry beans through the transition from traditional to computational breeding efforts by Aashvi Patel, Sajal Ahlawat, Philip Lorenc, Maryam Vazin, Masoud Maleki, Mohsen Yoosefzadeh Najafabadi (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-13220701.txt.
Description
Six authors review how breeding dry beans that resist anthracnose has changed over time, in a paper published in 2026. The disease is caused by a fungus and cuts bean yields around the world. Older methods relied on picking healthy plants by eye and crossing them, which worked but slowly. The fungus keeps changing, and weather shifts add pressure, so breeders now need faster tools.
Modern methods use gene data, large-scale plant measures, and computer analysis to find resistance genes much sooner. Machine learning and combined data types also help explain how the plant, the fungus, and the weather interact. The review argues that joining old and new methods gives the best path to beans that stay resistant.
Catalog record
| CREATOR | Aashvi Patel, Sajal Ahlawat, Philip Lorenc, Maryam Vazin, Masoud Maleki, Mohsen Yoosefzadeh Najafabadi |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 83 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |