PanicleNeRF: Low-Cost, High-Precision In-Field Phenotyping of Rice Panicles with Smartphone
Xin Yang, Xuqi Lu, Pengyao Xie, Ziyue Guo, Hui Fang, Haowei Fu, Xiaochun Hu, Zhenbiao Sun, Haiyan Cen · 2024
Read PanicleNeRF: Low-Cost, High-Precision In-Field Phenotyping of Rice Panicles with Smartphone by Xin Yang, Xuqi Lu, Pengyao Xie, Ziyue Guo, Hui Fang, Haowei Fu, Xiaochun Hu, Zhenbiao Sun, Haiyan Cen (2024) 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-11617619.txt.
Description
A rice panicle, the branching head that carries the grains, holds the clues to yield, but measuring it in a muddy field is slow work. Xin Yang and co-authors turn a smartphone video into a precise 3D model of the panicle. Their method, PanicleNeRF, pairs two vision models to cut the panicle out of each frame cleanly.
A neural technique then rebuilds the head in three dimensions from the cut frames. The resulting point cloud beat the standard photogrammetry tools clearly. Panicle length came out within about three percent of hand measures. Cloud volume tracked grain count and grain weight closely in both major rice types. The authors pitch the phone-based method as cheap, fast phenotyping for breeding programs.
Catalog record
| CREATOR | Xin Yang, Xuqi Lu, Pengyao Xie, Ziyue Guo, Hui Fang, Haowei Fu, Xiaochun Hu, Zhenbiao Sun, Haiyan Cen |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 38 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |