Peer review

Open Access

Non-destructive time-series assessment of chlorophyll content in flag-leaf (FLC) accurately mimics the senescence rate and the identification of genetic loci associated with senescence provides valuable knowledge to improve yield stability under stressed environments. In this study, we employed both unmanned aerial vehicles (UAVs) equipped with red-green-blue (RGB) camera and ground-based SPAD-502 instrument to conduct temporal phenotyping of senescence. A total of 262 recombinant inbred lines derived from the cross of Zhongmai 578/ Jimai 22 were evaluated for senescence-related traits across three environments, spanning from heading to 35 d post-anthesis. The manual senescence rate (MSR) was quantified using the FLC and the active accumulated temperature, and UAV derived vegetation index were utilized to assess the stay-green rate (USG) facilitating the identification of senescent and stay-green lines. Results indicated that higher senescence rates significantly impacted grain yield, primarily by influencing thousand-kernel weight, and plant height. Quantitative trait loci (QTL) mapping for FLC, USG, and MSR using the 50K SNP array identified 38 stable loci associated with RGB-based vegetation indices and senescence-related traits: among which 19 loci related to senescence traits from UAV and FLC were consistently detected across at least two growth stages, with nine loci likely representing novel QTL. This study highlights the potential of UAV-based high-throughput phenotyping and phenology in identifying critical loci associated with senescence rates in wheat, validating the relationship between senescence rates and yield-related traits in wheat, offering valuable opportunities for gene discovery and significant applications in breeding programs.

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National Key Research and Development Program Natural Science Foundation of China (NSFC) Beijing Joint Research Program for Germplasm Innovation and New Variety Breeding Breeding for Tomorrow

https://hdl.handle.net/10568/179266