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Peer-reviewedCC BYPlants (Basel, Switzerland)

RGB-Based Non-Destructive Measurement of Greenhouse Tomato Fruit Traits Using High-Fidelity Segmentation

  • Ke Zhang1
  • Aoxue Shen1
  • Ruocheng Gao1
  • Hong Cheng1
  • Jie Zhu2
  • Guan Pang1
  • Yu Wang1
  • Xia Yao2
  • Pei Zhang3
  • Jin Sun1
  1. 1College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China; (A.S.); (R.G.); (H.C.); (G.P.); (Y.W.)
  2. 2National Engineering and Technology Center for Information Agriculture, MARA Key Laboratory of Crop System Analysis and Decision Making, MOE Engineering Research Center of Smart Agriculture, Jiangsu Key Laboratory for Information Agriculture, Institute of Smart Agriculture, Nanjing Agricultural University, Nanjing 210095, China; (J.Z.); (X.Y.)
  3. 3Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA;
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Cite

BibTeXRIS
BibTeX
@article{zhang2026rgbbased,
  title = {{RGB-Based Non-Destructive Measurement of Greenhouse Tomato Fruit Traits Using High-Fidelity Segmentation}},
  author = {Ke Zhang and Aoxue Shen and Ruocheng Gao and Hong Cheng and Jie Zhu and Guan Pang and Yu Wang and Xia Yao and Pei Zhang and Jin Sun},
  journal = {Plants (Basel, Switzerland)},
  year = {2026},
  month = sep,
  url = {https://europepmc.org/article/PMC/PMC13666750},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - RGB-Based Non-Destructive Measurement of Greenhouse Tomato Fruit Traits Using High-Fidelity Segmentation
AU  - Ke Zhang
AU  - Aoxue Shen
AU  - Ruocheng Gao
AU  - Hong Cheng
AU  - Jie Zhu
AU  - Guan Pang
AU  - Yu Wang
AU  - Xia Yao
AU  - Pei Zhang
AU  - Jin Sun
PY  - 2026
DA  - 2026/09/28
JO  - Plants (Basel, Switzerland)
UR  - https://europepmc.org/article/PMC/PMC13666750
SN  - 2223-7747
ER  -