UAV‐based RGB imagery and ground measurements for high‐throughput phenotyping of senescence and QTL mapping in bread wheat

数量性状位点 生物 遗传力 衰老 天蓬 人口 遗传学 植物 基因 社会学 人口学
作者
Lei Li,Muhammad Adeel Hassan,Jie Song,Yi Xie,Awais Rasheed,Shurong Yang,Hongye Li,Peng Liu,Xianchun Xia,Zhonghu He,Yonggui Xiao
出处
期刊:Crop Science [Wiley]
卷期号:63 (6): 3292-3309
标识
DOI:10.1002/csc2.21086
摘要

Abstract Sustainable wheat production is challenged by climate change events such as drought, salinity, and heat stress. Senescence is a gradual programmed cell death trait occurring post anthesis in wheat ( Triticum aestivum ), with significant affecting stability of yield and quality‐related traits under climate severities. Phenotyping of complex traits is increasingly perceived as a bottleneck due to elevated labor costs and time in large field conditions. Unmanned aerial vehicle (UAV)‐based platforms using RGB imagery and ground phenotyping–based novel traits can facilitate the repeated nondestructive measurements of crop canopy traits cost‐effectively. Here, we described combined application of UAV‐based RGB imaging and ground measurements based novel trait to quantify canopy senescence in wheat. We reported senescence related traits with high heritability in a recombinant inbred line population derived from the cross Zhongmai 175/Lunxuan 987. Our results showed that the selection of slow senescence genotypes using UAV‐based vegetation indices (VIs) was equally effective as ground‐based traits and illustrated significant variations among the genotypes. We also identified five quantitative trait loci (QTL) for canopy senescence in both UAV and ground‐based datasets using a 50K single‐nucleotide polymorphism array. QTL for UAV‐based VIs from RGB imaging and ground measurements based traits were mapped on chromosomes 1B, 2B, 3A, and 4B. The integration of both datasets with genetic analysis identified an important slow senescence/stay‐green related locus on chromosome 4B that explained phenotypic variation up to 23.07% for both UAV and ground traits at late grain‐ filling stage. Three QTL ( QTL‐caas.1B , QTL‐caas.3A , and QTL‐caas.4B2 ) on chromosomes 1B, 3A, and 4B were also validated for slow senescence with high chlorophyll level and cool canopy temperature in a natural population of 160 lines by developing kompetitive allele‐specific PCR markers. QTL‐caas.4B1 was validated not only for senescence but also for plant height. Our findings suggest that UAV‐based RGB imagery is advantageous for precise and rapid assessment of senescence related traits and genetic studies of senescence in wheat.
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