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

Author:

Li Lei1,Hassan Muhammad Adeel12ORCID,Song Jie3,Xie Yongdun1,Rasheed Awais145,Yang Shurong1,Li Hongye1,Liu Peng2,Xia Xianchun1ORCID,He Zhonghu14,Xiao Yonggui1

Affiliation:

1. Institute of Crop Sciences, National Wheat Improvement Centre Chinese Academy of Agricultural Sciences (CAAS) Beijing China

2. Dezhou Academy of Agricultural Sciences Dezhou China

3. College of Agriculture, Henan Key Laboratory of Hybrid Wheat Henan Institute of Science and Technology Xinxiang China

4. International Maize and Wheat Improvement Centre (CIMMYT) China Office, c/o Chinese Academy of Agricultural Sciences (CAAS) Beijing China

5. Department of Plant Science Quaid‐i‐Azam University Islamabad Pakistan

Abstract

AbstractSustainable 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.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Wiley

Subject

Agronomy and Crop Science

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