Visualisation and Prediction of Phosphate Deficiency via Auto‐Glowing Plant Bioluminescent Sensors
Ching‐Wen Chiu, Ya‐Fen Zhan, Ting‐Yang Lu, Liang‐Jie Chiu, Ya‐Ru Li, Cheng‐Jiun Huang, Hao‐Jun Lu, Huai‐Ji Huang, Alexander S Mishin, Karen S Sarkisyan, Ting‐Ying Wu, Chiu‐Han Hsiao, Ming‐Jung Liu · 2026
Read Visualisation and Prediction of Phosphate Deficiency via Auto‐Glowing Plant Bioluminescent Sensors by Ching‐Wen Chiu, Ya‐Fen Zhan, Ting‐Yang Lu, Liang‐Jie Chiu, Ya‐Ru Li, Cheng‐Jiun Huang, Hao‐Jun Lu, Huai‐Ji Huang, Alexander S Mishin, Karen S Sarkisyan, Ting‐Ying Wu, Chiu‐Han Hsiao, Ming‐Jung Liu (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-13436540.txt.
Description
Ching-Wen Chiu's team built BioLumiPi in 2026, a tobacco plant that glows to show phosphate shortage in real time. Phosphorus is vital for crops but often locked in soil, driving heavy fertilizer use, while current checks are destructive, slow, or blind to living plant status. The team paired a phosphate-starvation promoter with a fungal glow system, so light output mirrors the plant's own phosphate state.
Coupled with deep learning, the glowing plants offered a low-cost, non-invasive way to visualize and predict nutrient stress, guiding fertilizer to where and when it is needed. Growers get a proof-of-concept sensor crop for sustainable feeding. Field transfer to food crops remains the next hurdle.
Catalog record
| CREATOR | Ching‐Wen Chiu, Ya‐Fen Zhan, Ting‐Yang Lu, Liang‐Jie Chiu, Ya‐Ru Li, Cheng‐Jiun Huang, Hao‐Jun Lu, Huai‐Ji Huang, Alexander S Mishin, Karen S Sarkisyan, Ting‐Ying Wu, Chiu‐Han Hsiao, Ming‐Jung Liu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 15 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |