Editorial: Remote sensing for field-based crop phenotyping

Jiangang Liu; Zhenjiang Zhou; Bo Li

doi:10.3389/fpls.2024.1368694

Editorial: Remote sensing for field-based crop phenotyping

Front Plant Sci. 2024 Jan 26:15:1368694. doi: 10.3389/fpls.2024.1368694. eCollection 2024.

Authors

Jiangang Liu¹, Zhenjiang Zhou², Bo Li³

Affiliations

¹ State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China.
² College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.
³ Syngenta, Jealott's Hill International Research Centre, Bracknell, United Kingdom.

No abstract available

Keywords: computer vision; crop phenotyping; data fusion; machine learning; remote sensing; smart agriculture.

Publication types

Editorial

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work is supported by National Key R&D Program of China (2023YFD2302100), National Natural Science Foundation of China (32372232), Key scientific and technological projects of Heilongjiang province in China (2021ZXJ05A05-03) awarded to Jiangang Liu, also Science and Technology Department of Ningxia - The Key Research and Development Program (2023BCF01017).