4.5 Article

Acute High Temperature Response in Wheat

Journal

AGRONOMY JOURNAL
Volume 110, Issue 4, Pages 1296-1308

Publisher

WILEY
DOI: 10.2134/agronj2017.07.0392

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Funding

  1. Australian Grains Research and Development Corporation
  2. Agriculture Victoria, Dep. of Economic Development, Jobs, Transport and Resources

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Heat waves have a significant impact on crop production and quality of many staple grains including wheat. Under climate change, changing weather patterns including greater temperature volatility are also likely to further affect yield stability. Simulation modeling provides a powerful tool to investigate the interactive effects of abiotic factors and develop adaptive strategies; however, many of these models do not adequately account for the step change response to high temperature occurring during the crop reproductive phase. Empirical response data will support the development of robust algorithms for crop models. We present results from three experiments on the response of wheat to a range of acute high-temperature treatments. For 35, 37, and 42 degrees C and 1, 3, and 5 d of exposure (similar to 6 h d(-1)), expressed as heat sum, degrees Cxh (above 32 degrees C), high temperature applied 5 d prior to anthesis reduced grain number and yield by 0.16 and 0.15% per degrees Cxh respectively, whereas individual grain weight and grain nitrogen concentration increased by 0.03 and 0.06% per degrees Cxh, respectively. For high temperature applied after anthesis, individual grain weight decreased by 0.05% per degrees Cxh, grain nitrogen concentration increased by 0.03% per degrees Cxh, and yield was reduced by 0.07% per degrees Cxh. The often asymptotic response meant exponential functions provided a superior fit. Water availability prior to anthesis attenuated wheat response to high temperature. Such algorithms could contribute to improving our prediction of the step change response of wheat to high temperature within crop models and more broadly contribute to developing strategies for crop adaptation to climate change using a modeling approach.

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