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The relationships between genotype, yield, and environmental factors on protein distribution in the wheat endosperm

Savill, G. P. (2018) The relationships between genotype, yield, and environmental factors on protein distribution in the wheat endosperm. PhD thesis, University of Reading

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Within a generation, climate change will no longer be a subject for political debate. By 2080, average summer temperatures in the UK are predicted to rise by up to 4.2°C, snowfall will all but cease, and heatwaves will become increasingly common (Jenkins et al. 2009). Whilst high temperatures are known to be detrimental to wheat crop yields (Shah et al. 2003; Asseng et al. 2011; Asseng 2015), the effect on the distribution of protein within the wheat grain is yet to be discovered. Distinct gradients exist in the distribution of protein within the wheat endosperm (Cobb 1905; Kent 1966; Tosi et al. 2011), with protein accumulation concentrated towards the outer endosperm, an effect which is increased by nitrogen fertilisation (He et al. 2013). Due to these gradients in protein concentration, during milling mill streams of differing protein content are produced (Wang et al. 2007). Furthermore, when milling for while flour, a portion of the outer endosperm remains adhered to the aleurone layer, resulting in a disproportionate reduction in the protein content of the flour. Therefore understanding the effects that determine the distribution of protein within the wheat endosperm is of great importance. This research has identified a combined effect of nitrogen supply and elevated temperature on the gradient in grain protein concentration and size-distribution of protein bodies in the wheat endosperm, and also how these qualities vary between genotypes. Furthermore, data for grain yield and yield components, protein composition, and gluten storage protein synthesis gene expression are also presented. The results of this study lay the foundation for future work on the effect of climate change on wheat grain quality. This study also makes available an image analysis tool capable of the high-throughput spatial analysis of images, which can be applied to a range of future experiments.

Item Type:Thesis (PhD)
Thesis Supervisor:Tosi, P.
Thesis/Report Department:School of Agriculture, Policy and Development
Identification Number/DOI:
Divisions:Life Sciences > School of Agriculture, Policy and Development
ID Code:84837
Additional Information:The published article filed at the end of this thesis is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. A link to the article is available via the Related URL.


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