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

作者：Lei Li, Muhammad Adeel Hassan, Jie Song, Yongdun Xie, Awais Rasheed, Shurong Yang, Hongye Li, Peng Liu, Xianchun Xia, Zhonghu He, Yonggui Xiao · 发表于：Crop Science · 年份：2023 · DOI：10.1002/csc2.21086 · 被引用次数：26 · 研究领域：Wheat and Barley Genetics and Pathology、Genetic Mapping and Diversity in Plants and Animals、Crop Yield and Soil Fertility

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...