@article{72cfe43c60cd443cab8df69f9c4272cd,
title = "Editorial: State-of-the-Art Technology and Applications in Crop Phenomics",
keywords = "AI-driven phenotypic analysis, high-throughput phenotyping, hyperspectral, UAV (unmanned aerial vehicle), X-ray micro-CT",
author = "Wanneng Yang and Doonan, {John H.} and Hawkesford, {Malcolm J.} and Tony Pridmore and Ji Zhou",
note = "Funding Information: This editorial was supported by grants from the National Key Research and Development Program (2020YFD1000904-1-3), the National Natural Science Foundation of China (31770397 and 32070400), Major Science and Technology Projects in Hubei Province, Fundamental Research Funds for the Central Universities (2662020ZKPY017 and 2021ZKPY006), Cooperative funding between Huazhong Agricultural University and Shenzhen Institute of Agricultural Genomics (SZYJY2021005 and SZYJY2021007), Natural Science Foundation of the Jiangsu Province (BK20191311), UK-China grant the Biotechnology and Biological Sciences Research Council (BBSRC; BB/R02118X/1), the Designing Future Wheat programme (BB/P016855/1), and PhenomUK (MR/R025746/1).",
year = "2021",
month = oct,
day = "5",
doi = "10.3389/fpls.2021.767324",
language = "English",
volume = "12",
journal = "Frontiers in Plant Science",
issn = "1664-462X",
publisher = "Frontiers Media SA",
}