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Combining self-organizing maps and biplot analysis to preselect maize phenotypic components based on UAV high-throughput phenotyping platform

文献类型： 外文期刊

作者： Han, Liang 1 ; Yang, Guijun 1 ; Dai, Huayang 4 ; Yang, Hao 1 ; Xu, Bo 1 ; Li, Heli 3 ; Long, Huiling 1 ; Li, Zhenhai 3 ; Yan 1 ;

作者机构： 1.Beijing Res Ctr Informat Technol Agr, Minist Agr, Key Lab Quantitat Remote Sensing Agr, Beijing 100097, Peoples R China

2.Shanxi Datong Univ, Coll Architecture & Geomat Engn, Datong 037003, Peoples R China

3.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

4.China Univ Min & Technol Beijing, Coll Geosci & Surveying Engn, Beijing 100083, Peoples R China

关键词： SOM; Biplot; UAV; Maize; High-throughput phenotyping

期刊名称：PLANT METHODS （ 影响因子：4.993； 五年影响因子：5.312 ）

ISSN： 1746-4811

年卷期： 2019 年 15 卷

页码：

收录情况： SCI

摘要： BackgroundWith environmental deterioration, natural resource scarcity, and rapid population growth, mankind is facing severe global food security problems. To meet future needs, it is necessary to accelerate progress in breeding fornew varieties with high yield and strong resistance. However, the traditional phenotypic screening methods have some disadvantages, such as destructive, inefficient, low-dimensional, labor-intensive and cumbersome, which seriously hinder the development of field breeding. Breeders urgently need a high-throughput technique for acquiring and evaluating phenotypic data that can efficiently screen out excellent phenotypic traits from large-scale genotype populations.ResultsIn the present study, we used an unmanned aerial vehicle (UAV) high-throughput phenotyping (HTP) platform to collect RGB and multispectral images for a breeding program and acquired multiple phenotypic components (or traits), such as plant height, normalized difference vegetation index, biomass accumulation, plant-height growth rate, lodging, and leaf color. By implementing self-organizing maps and principal components analysis biplots to establish phenotypic map and similarity, we proposed an UAV-assisted HTP framework for preselecting maize (Zee mays L.) phenotypic components (or traits).ConclusionsThis framework gives breeders additional information to allow them to quickly identify and preselect plants that have genotypes conferring desirable phenotypic components out of thousands of field plots. The present study also demonstrates that remote sensing is a powerful tool with which to acquire abundant phenotypic components. By using these rich phenotypic components, breeders should be able to more effectively identify and select superior genotypes.

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