High-throughput field phenotyping reveals that selection in breeding has affected the phenology and temperature response of wheat in the stem elongation phase


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Date

2024-03-27

Publication Type

Journal Article

ETH Bibliography

yes

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Data

Abstract

Crop growth and phenology are driven by seasonal changes in environmental variables, with temperature as one important factor. However, knowledge about genotype-specific temperature response and its influence on phenology is limited. Such information is fundamental to improve crop models and adapt selection strategies. We measured the increase in height of 352 European winter wheat varieties in 4 years to quantify phenology, and fitted an asymptotic temperature response model. The model used hourly fluctuations in temperature to parameterize the base temperature (Tₘᵢₙ), the temperature optimum (rₘₐₓ), and the steepness (lrc) of growth responses. Our results show that higher Tₘᵢₙ and lrc relate to an earlier start and end of stem elongation. A higher rₘₐₓ relates to an increased final height. Both final height and rₘₐₓ decreased for varieties originating from the continental east of Europe towards the maritime west. A genome-wide association study (GWAS) indicated a quantitative inheritance and a large degree of independence among loci. Nevertheless, genomic prediction accuracies (GBLUPs) for Tₘᵢₙ and lrc were low (r≤0.32) compared with other traits (r≥0.59). As well as known, major genes related to vernalization, photoperiod, or dwarfing, the GWAS indicated additional, as yet unknown loci that dominate the temperature response.

Publication status

published

Editor

Book title

Volume

75 (7)

Pages / Article No.

2084 - 2099

Publisher

Oxford University Press

Event

Edition / version

Methods

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Date created

Subject

Correlated response to selection; genetic correlation; genomic prediction; growth dynamic; GWAS; modeling; trait extraction

Organisational unit

03894 - Walter, Achim / Walter, Achim check_circle

Notes

Funding

200756 - PHENOFLOW: A multifaceted workflow of high-throughput field phenotyping for improved prediction of wheat performance in future climate scenarios based on assessment of dynamic changes of phenology (SNF)
169542 - PhenoCOOL: Wheat and soybean phenotyping under cold conditions using growth as a dynamic trait (SNF)

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