Haplotype analysis from unmanned aerial vehicle imagery of rice MAGIC population for the trait dissection of biomass and plant architecture

© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Bibliographische Detailangaben
Veröffentlicht in:Journal of experimental botany. - 1985. - 72(2021), 7 vom: 29. März, Seite 2371-2382
1. Verfasser: Ogawa, Daisuke (VerfasserIn)
Weitere Verfasser: Sakamoto, Toshihiro, Tsunematsu, Hiroshi, Kanno, Noriko, Nonoue, Yasunori, Yonemaru, Jun-Ichi
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2021
Zugriff auf das übergeordnete Werk:Journal of experimental botany
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Biomass GWAS MAGIC QTL haplotype high-throughput phenotyping rice unmanned aerial vehicle (UAV) vegetation fraction
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520 |a Unmanned aerial vehicles (UAVs) are popular tools for high-throughput phenotyping of crops in the field. However, their use for evaluation of individual lines is limited in crop breeding because research on what the UAV image data represent is still developing. Here, we investigated the connection between shoot biomass of rice plants and the vegetation fraction (VF) estimated from high-resolution orthomosaic images taken by a UAV 10 m above a field during the vegetative stage. Haplotype-based genome-wide association studies of multi-parental advanced generation inter-cross (MAGIC) lines revealed four quantitative trait loci (QTLs) for VF. VF was correlated with shoot biomass, but the haplotype effect on VF was better correlated with that on shoot biomass at these QTLs. Further genetic characterization revealed the relationships between these QTLs and plant spreading habit, final shoot biomass and panicle weight. Thus, genetic analysis using high-throughput phenotyping data derived from low-altitude, high-resolution UAV images during early stages of rice growing in the field provides insights into plant growth, architecture, final biomass, and yield 
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650 4 |a Research Support, Non-U.S. Gov't 
650 4 |a Biomass 
650 4 |a GWAS 
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650 4 |a haplotype 
650 4 |a high-throughput phenotyping 
650 4 |a rice 
650 4 |a unmanned aerial vehicle (UAV) 
650 4 |a vegetation fraction 
700 1 |a Sakamoto, Toshihiro  |e verfasserin  |4 aut 
700 1 |a Tsunematsu, Hiroshi  |e verfasserin  |4 aut 
700 1 |a Kanno, Noriko  |e verfasserin  |4 aut 
700 1 |a Nonoue, Yasunori  |e verfasserin  |4 aut 
700 1 |a Yonemaru, Jun-Ichi  |e verfasserin  |4 aut 
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