Maize ( Zea mays L.) plays a crucial role in feeding the world’s growing population. Among its various traits, plant height is particularly important as it affects yield, lodging resistance and ecological adaptability. However, traditional methods for measuring plant height often lack cost-efficiency and accuracy.
In a study published in Journal of Integrative Agriculture , a team of researchers from China used a light detection and ranging (LiDAR) sensor mounted on an unmanned aerial vehicle (UAV) to collect point cloud data from 270 doubled haploid (DH) lines.
“We constructed high-density genetic maps and assessed plant height at both single-plant and row scales across multiple developmental stages and genetic backgrounds,” explains corresponding author Jun Zheng at Gansu Agricultural University & Chinese Academy of Agricultural Sciences. “We found that for many varieties and small areas, single-plant-scale estimation accuracy was superior to row-scale estimation, with R ² values of 0.67 vs . 0.56 and RMSE values of 0.12 m vs . 0.17 m, respectively.”
“We constructed two high-density genetic maps based on SNP markers,” shares co-corresponding author Xiuliang Jin at Chinese Academy of Agricultural Sciences. “In Sanya and Xinxiang, the F1DH and F2DH populations identified 12 and 20 QTLs (quantitative trait loci) for plant height, respectively.”
Notably, the study highlights the potential of UAV-based remote sensing to advance precision agriculture by enabling efficient, large-scale phenotyping and gene discovery in maize breeding programs.
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Contact Authors:
Correspondence Jun Zheng, E-mail: zhengjun02@caas.cn;
Xiuliang Jin, E-mail: jinxiuliang@caas.cn;
Hongwu Wang, E-mail: wanghongwu@caas.cn
The publisher KeAi was established by Elsevier and China Science Publishing & Media Ltd to unfold quality research globally. In 2013, our focus shifted to open access publishing. We now proudly publish more than 200 world-class, open access, English language journals, spanning all scientific disciplines. Many of these are titles we publish in partnership with prestigious societies and academic institutions, such as the National Natural Science Foundation of China (NSFC).
Journal of Integrative Agriculture
Experimental study
Not applicable
QTL mapping of maize plant height based on a population of doubled haploid lines using UAV LiDAR high-throughput phenotyping data.
The authors declare that they have no conflict of interest.