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. 2020 Oct 20;10(1):17800.
doi: 10.1038/s41598-020-73707-8.

Evaluation of the impact of heat on wheat dormancy, late maturity α-amylase and grain size under controlled conditions in diverse germplasm

Jose M Barrero  1 , Luciana Porfirio  2 , Trijntje Hughes  3 , Jing Chen  4 , Shannon Dillon  3 , Frank Gubler  3 , Jean-Philippe F Ral  3
Affiliations

Evaluation of the impact of heat on wheat dormancy, late maturity α-amylase and grain size under controlled conditions in diverse germplasm

Jose M Barrero et al. Sci Rep. .

Abstract

In the Australian wheat belts, short episodes of high temperatures or hot spells during grain filling are becoming increasingly common and have an enormous impact on yield and quality, bringing multi-billion losses annually. This problem will become recurrent under the climate change scenario that forecast increasing extreme temperatures, but so far, no systematic analysis of the resistance to hot spells has yet been performed in a diverse genetic background. We developed a protocol to study the effects of heat on three important traits: grain size, grain dormancy and the presence of Late Maturity α-Amylase (LMA), and we validated it by analysing the phenotypes of 28 genetically diverse wheat landraces and exploring the potential variability existing in the responses to hot spells. Using controlled growth environments, the different genotypes were grown in our standard conditions until 20 days after anthesis, and then moved for 10 days into a heat chamber. Our study showed that our elevated temperature treatment during mid-late filling triggered multiple detrimental effects on yield and quality. We observed a reduction in grain size, a reduction in grain dormancy and increased LMA expression in most of the tested genotypes, but potential resistant lines were identified for each analyzed trait opening new perspectives for future genetic studies and breeding for heat-insensitive commercial lines.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Shift in maximum temperatures during grain filling in the Australian wheat belt. Data of maximum temperatures for the period of September–October for the winter cereal region in Australia (grey area on the map). The colours and hatched vertical lines indicate values that depart one or two standard deviations from the baseline period mean (21.7 °C). (A) The curve-bells show climatologies of maximum temperature for the baseline period (1951–1980). The light red area represents high temperatures between 1 and 2 standard deviations and the red area represents temperatures over 2 standard deviations. The light blue area represents low temperatures between 1 and 2 standard deviations and the blue area represents temperatures below 2 standard deviations. The map was obtained from the Australian Land Use and Management (ALUM) Classification system version 8 (https://data.gov.au/dataset/ds-dga-a7d50fb8-b353-4bb4-a7ca-1a2f38f44abc/details), selecting only the pixels classified as ‘winter cereals’ using the Raster R Package. (B) Climatologies of maximum temperatures for the period 2003–2013, which includes the period known as Millennium drought. (C) Future projections of maximum temperatures for the period 2021–2050 from the Australian Earth System Model, Access 1.3, based on the high carbon emissions Representative Concentration Pathway scenario (RCP 8.5).
Figure 2
Figure 2
Impact of hot spells on grain dormancy, LMA and grain size. (A) Germination percentage of fresh-harvested samples. (B) LMA expression based on enzymatic assays. (C) Grain size analysis. Blue circles represent the values of the control samples. Orange circles represent heat stressed samples. Yellow lines were added to facilitate the comparison between treatments. Mean values with their SEs are shown. nd: not determined.
Figure 3
Figure 3
Genetic diversity analysis of the landraces in comparison to the Vavilov collection. Representation of the PCA of the genotyping results for the core landrace collection and the Vavilov diversity panel. The first two orthogonal axes (coordinates) produced following PCA on pairwise distance among varieties are plotted, illustrating the spread of diversity captured in the broader global collection (Vavilov set) relative to the landraces chosen for this study. The diversity seen in the landraces covers proportionally the diversity present in the Vavilov panel.
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