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High-throughput phenotyping of physiological traits for wheat resilience to high temperature and drought stress

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F86652079%3A_____%2F22%3A00561388" target="_blank" >RIV/86652079:_____/22:00561388 - isvavai.cz</a>

  • Result on the web

    <a href="https://academic.oup.com/jxb/article/73/15/5235/6572012?login=true" target="_blank" >https://academic.oup.com/jxb/article/73/15/5235/6572012?login=true</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1093/jxb/erac160" target="_blank" >10.1093/jxb/erac160</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    High-throughput phenotyping of physiological traits for wheat resilience to high temperature and drought stress

  • Original language description

    Interannual and local fluctuations in wheat crop yield are mostly explained by abiotic constraints. Heatwaves and drought, which are among the top stressors, commonly co-occur, and their frequency is increasing with global climate change. High-throughput methods were optimized to phenotype wheat plants under controlled water deficit and high temperature, with the aim to identify phenotypic traits conferring adaptative stress responses. Wheat plants of 10 genotypes were grown in a fully automated plant facility under 25/18 degrees C day/night for 30 d, and then the temperature was increased for 7 d (38/31 degrees C day/night) while maintaining half of the plants well irrigated and half at 30% field capacity. Thermal and multispectral images and pot weights were registered twice daily. At the end of the experiment, key metabolites and enzyme activities from carbohydrate and antioxidant metabolism were quantified. Regression machine learning models were successfully established to predict plant biomass using image-extracted parameters. Evapotranspiration traits expressed significant genotype-environment interactions (GxE) when acclimatization to stress was continuously monitored. Consequently, transpiration efficiency was essential to maintain the balance between water-saving strategies and biomass production in wheat under water deficit and high temperature. Stress tolerance included changes in carbohydrate metabolism, particularly in the sucrolytic and glycolytic pathways, and in antioxidant metabolism. The observed genetic differences in sensitivity to high temperature and water deficit can be exploited in breeding programmes to improve wheat resilience to climate change.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10611 - Plant sciences, botany

Result continuities

  • Project

    <a href="/en/project/LO1415" target="_blank" >LO1415: CzechGlobe 2020 – Development of the Centre of Global Climate Change Impacts Studies</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of Experimental Botany

  • ISSN

    0022-0957

  • e-ISSN

    1460-2431

  • Volume of the periodical

    73

  • Issue of the periodical within the volume

    15

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    17

  • Pages from-to

    5235-5251

  • UT code for WoS article

    000813474400001

  • EID of the result in the Scopus database

    2-s2.0-85144731827