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University of Nottingham (2018)

Identifying rooting traits and their genetic bases for improved drought tolerance in winter wheat

Slack, Shaunagh

Titre : Identifying rooting traits and their genetic bases for improved drought tolerance in winter wheat.

Auteur : Slack, Shaunagh

Université de soutenance : University of Nottingham

Grade : Doctor of Philosophy (PhD) 2018

Résumé partiel
Winter wheat (Triticum aestivum L.) is one of the mostly widely grown arable crops worldwide, with a total annual global production of approximately 716 million tonnes. In the UK, around 14.5 million tonnes of wheat is produced annually on roughly 1.8 million hectares of land ; however, 15-30% of this annual wheat yield production is lost to drought. Two field experiments were conducted in 2013-14 and 2014-15 to characterise a doubled-haploid (DH) population of 94 lines derived from a cross between the winter wheat cultivars, Rialto and Savannah, at the University of Nottingham Sutton Bonington Campus, UK (52o 50’ N, 1o 15’ W). This population was selected due to the genetic variation observed in previous field experiments in stay-green traits under drought and nitrogen stress in the UK and France (Foulkes et al., unpublished). A shovelomics methodology was developed for phenotyping wheat crown root traits of the mapping population and validation on soil core samples (extraction of roots by washing and root scanning using WinRHIZO software) was carried out on a subset of 14 DH lines and the two parents. In addition, two 50-cm soil column glasshouse experiments examining the two parental genotypes and the subset of 14 Rialto x Savannah DH population lines, and one 100 cm soil column glasshouse experiment examining the two parental genotypes and two Rialto x Savannah DH lines using micro-computed tomography (µCT) scanning, were carried out under well-watered and drought conditions. Two further glasshouse experiments were carried out to quantify root anatomical traits on the two parental genotypes under well-watered and drought conditions. The main objectives were to quantify genetic variation in root traits and associations with water uptake and drought tolerance in the Rialto x Savannah doubled-haploid population, to quantify mechanisms underlying associations between root traits and water capture and drought tolerance and to identify quantitative trait loci (QTL) associated with root traits and drought tolerance through genetic analysis in the Rialto x Savannah DH population. In the field experiments, drought reduced grain yield by 16.7% in 2014 and 14.9% in 2015. Amongst the DH lines, genetic variation for crown root angle, roots plant-1, roots shoot-1 and length was observed Under unirrigated conditions, root length density (RLD) at depth (40-60 cm) was positively associated with crown root angle and crown roots shoot-1 in 2014 and 2015. RLD at depth was also positively correlated with grain yield. Amongst the 94 R x S DH lines, crown root angle (greater angle = steeper root) and crown roots shoot-1 were positively associated with post-anthesis canopy stay-green as indicated by the Normalised Difference Vegetation Index (NDVI) spectral reflectance index and grain yield under unirrigated conditions. Later onset and end of flag-leaf senescence were associated with increased grain yield in 2014, but not in 2015. In the x-ray µCT soil column experiment, there were positive relationships amongst genotypes between steeper crown root angle at 5, 10 and 15 cm depths measured using µCT and RLD at 60-80 cm depth measured directly (WinRHIZO root scanning) under drought, but negative relationships under well-watered conditions. RLD at 60-80 cm was associated with water uptake and number of grains plant 1 under drought. There were positive associations between the total root length plant-1 measured using µCT and direct measurement of this trait (WinRHIZO root scanning) and between µCT root number and direct measurement of RLD in each soil horizon. In addition, there were associations between root angle in the µCT soil column experiment and crown root angle in the field measured using shovelomics techniques.


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