Exploring the superiority of solar-induced chlorophyll fluorescence data in predicting wheat yield using machine learning and deep learning methods

Yuanyuan Liu, Shaoqiang Wang, Xiaobo Wang, Bin Chen, Jinghua Chen, Junbang Wang, Mei Huang, Zhaosheng Wang, Li Ma, Pengyuan Wang, Muhammad Amir, Kai Zhu. Exploring the superiority of solar-induced chlorophyll fluorescence data in predicting wheat yield using machine learning and deep learning methods. Computers and Electronics in Agriculture, 192:106612, 2022. [doi]

@article{LiuWWCCWHWMWAZ22,
  title = {Exploring the superiority of solar-induced chlorophyll fluorescence data in predicting wheat yield using machine learning and deep learning methods},
  author = {Yuanyuan Liu and Shaoqiang Wang and Xiaobo Wang and Bin Chen and Jinghua Chen and Junbang Wang and Mei Huang and Zhaosheng Wang and Li Ma and Pengyuan Wang and Muhammad Amir and Kai Zhu},
  year = {2022},
  doi = {10.1016/j.compag.2021.106612},
  url = {https://doi.org/10.1016/j.compag.2021.106612},
  researchr = {https://researchr.org/publication/LiuWWCCWHWMWAZ22},
  cites = {0},
  citedby = {0},
  journal = {Computers and Electronics in Agriculture},
  volume = {192},
  pages = {106612},
}