Image-based quantitative root phenotyping enables reliable origin classification of wild-simulated ginseng

Do-Sin Lee, Yeong-Bae Yun, Jun-Seo Yi, Dong-Young Kim, Sung-Hwan Jo, Yurry Um

Open source

DOI
10.1016/j.jafr.2026.103110
Published
2026-07
Container
Journal of Agriculture and Food Research
Publisher
Elsevier BV
Open access
unknown

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BibTeX

@article{allodium:10.1016/j.jafr.2026.103110,
  title = {Image-based quantitative root phenotyping enables reliable origin classification of wild-simulated ginseng},
  author = {Do-Sin Lee and Yeong-Bae Yun and Jun-Seo Yi and Dong-Young Kim and Sung-Hwan Jo and Yurry Um},
  year = {2026},
  journal = {Journal of Agriculture and Food Research},
  doi = {10.1016/j.jafr.2026.103110},
  url = {https://doi.org/10.1016/j.jafr.2026.103110}
}

RIS

TY  - JOUR
TI  - Image-based quantitative root phenotyping enables reliable origin classification of wild-simulated ginseng
AU  - Do-Sin Lee
AU  - Yeong-Bae Yun
AU  - Jun-Seo Yi
AU  - Dong-Young Kim
AU  - Sung-Hwan Jo
AU  - Yurry Um
PY  - 2026
JO  - Journal of Agriculture and Food Research
DO  - 10.1016/j.jafr.2026.103110
UR  - https://doi.org/10.1016/j.jafr.2026.103110
ER  - 

APA

Lee, D., Yun, Y., Yi, J., Kim, D., Jo, S., & Um, Y. (2026). Image-based quantitative root phenotyping enables reliable origin classification of wild-simulated ginseng. Journal of Agriculture and Food Research. https://doi.org/10.1016/j.jafr.2026.103110

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