English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

High-throughput phenotyping systems with unmanned aerial vehicles (UAVs) enable observation of crop lines in the field. In this study, we show the ability of time-course monitoring of canopy height (CH) to identify quantitative trait loci (QTLs) and to characterise their pleiotropic effect on various traits. We generated a digital surface model from low-altitude UAV-captured colour digital images and investigated CH data of rice multi-parental advanced generation inter-cross (MAGIC) lines from tillering and heading to maturation. Genome-wide association studies (GWASs) using the CH data and haplotype information of the MAGIC lines revealed 11 QTLs for CH. Each QTL showed haplotype effects on different features of CH such as stage-specificity and constancy. Haplotype analysis revealed relationships at the QTL level between CH and, vegetation fraction and leaf colour [derived from UAV red–green–blue (RGB) data], and CH and yield-related traits. Noticeably, haplotypes with canopy lowering effects at  qCH1-4, qCH2 , and  qCH10-2  increased the ratio of panicle weight to leaf and stem weight, suggesting biomass allocation to grain yield or others through growth regulation of CH. Allele mining using gene information with eight founders of the MAGIC lines revealed the possibility that  qCH1-4  contains multiple alleles of  semi-dwarf 1  ( sd1 ), the IR-8 allele of which significantly contributed to the “green revolution” in rice. This use of remote-sensing-derived phenotyping data into genetics using the MAGIC lines gives insight into how rice plants grow, develop, and produce grains in phenology and provides information on effective haplotypes for breeding with ideal plant architecture and grain yield.

Remote-Sensing-Combined Haplotype Analysis Using Multi-Parental Advanced Generation Inter-Cross Lines Reveals Phenology QTLs for Canopy Height in Rice