The fact that Sonora carries the day length sensitivity allele may seem surprising as it originates from Mexico. However, Sonora is thought to have been selected from a landrace that was brought over to the Americas from Europe with Columbus in 1492 and Shcherban et al. showed that 91% of spring wheat cultivars in Europe contain the photoperiod sensitive allele Ppd-D1b. A second consistent QTL for days to heading was identified on chromosome arm 5AL in the SF and CF populations. In SF the QTL covered a 4.4 cM region with a peak at 163 cM between markers 5A_10843 and 5A_24477 and explaining 20-21 % of the phenotypic variation. The QTL in the CF population covered a 10.4 cM region with its peak at 92 cM between the markers 5A_1737 and 5A_12135 explaining 18-28 % of the phenotypic variation. Although the markers are not identical they map within a couple of cM of one another in the consensus map of Wang et al. strongly suggesting that this is indeed the same QTL. The third QTL for days to heading was on the long arm of chromosome 5B in the SF and CF populations. In SF the QTL covers a region of 2.2 and 10.1 with peaks at 120 and 126 being that there was a slight shift between years from 5B_3483 and 5B_9459 in 2013 to 5B_80245 and 5B_3483 in 2014. This created a larger cM region and a 6 cM shift in the peak of the QTL for 2014. This QTL explains 17-20 % of the phenotypic variation seen in this population. For CF the QTL covers a 1.6 cM region with its peak around 106 cM between the markers 5B_80245 and 5B_51408 explaining 17 % of the phenotypic variation seen in this population.

These populations share the 5B_80245 marker providing validation of the QTL. Additional validation comes from Zanke et al. who located a gene on chromosome 5B related to the Hd6 gene family of rice with a major impact on heading time in wheat. They found that the marker Kukri_c10016_369 was the closest linked marker to the locus,growing tomatoes hydroponically and it maps to the same genetic position as 5B_3483 identified in our mapping experiments. This suggests that the QTL identified in two of our populations across multiple years is indeed this same Hd6 related locus. It is possible that the other QTL identified on 5A and 5D are homoeologous to the 5B QTL. This of course is only speculative and would require further inquiry. The fourth QTL was identified on the long arm of chromosome 5D in the SC and SF populations. For SC the QTL covers a 2.0 and 24.5 cM region with its peak between 78 and 75 cM respectively. A shift from 5D_17130 and 5D_502 in 2013 to 5D_4695 and 5D_17130 in 2014 cause the differences seen in QTL area and peak position, however, in both years the QTLs share marker 5D_17130. The QTL explains 45-49 % of the phenotypic variation seen in this population. In SF the QTL covers a region of 21.7 cM with a peak at 10 cM between the markers 5D_17310 and 5D_42321 and shares the 5D_17310 in common with the SC QTL. This QTL explains 29-41 % of the phenotypic variation seen in this population. Finally, the fifth QTL was located on the long arm of chromosome 5D and identified in the SC and CF populations. In the SC population it covers a 19.0 and 10.7 cM region with a peak around 150 and 156 cM, respectively. This QTL explains 40-52 % of the phenotypic variation found in the population. In 2013 the left and right markers were 5D_1682 and 5D_63558 while in 2014 the markers were 5D_63588 and 5D_5776 with marker 5D_63558 appearing in both years. The large region of this QTL is likely due to poor coverage of SNP markers on most of the D genome chromosomes. This QTL was also observed in the CF population where it covered a 7.6 cM region with a peak at 139 cM between markers 5D_63558 and 5D_5776 and explaining 22-25 % of the phenotypic variation in this population.

Both populations share markers 5D_63588 and 5D_5776 providing good validation for this QTL. When comparing days to heading in the greenhouse and the field it is apparent that the 18 hours of supplemental light given in the greenhouse greatly reduced the flowering time of the populations. This difference in treatment also enabled us to detect different flowering time loci. In the field only the day length sensitivity and insensitivity loci on 2D were detected, yet when grown under 18 hours of light all other QTLs were able to be identified. These other QTLs could potentially be Eps loci given that the photoperiod response was removed via the 18 hours of supplemental lighting provided. However, this speculation would require greater inquiry and further experiments to draw any solid conclusions.These include hybrid necrosis, hybrid chlorosis, and hybrid dwarfness with hybrid necrosis being encountered more frequently . Hermsen described hybrid necrosis as a premature and gradual death of foliage in certain hybrids. The trait is controlled by two dominant complementary genes Ne1 and Ne2 located on chromosome arms 5BL and 2BS respectively . In the three populations tested, hybrid necrosis was rated in the 2013 evaluations only and at which point all lines with unacceptable levels of necrosis were removed. Thus, QTL for hybrid necrosis were identified using the 2013 data for lines with acceptable levels of hybrid necrosis that were genotyped. Two QTLs were identified as being associated with hybrid necrosis in the CF population. The first is on chromosome arm 2BS where it covers a region of 0.8 cM with its peak at 82 cM between markers 2B_31805 and 2B_4614. It explains 22.51 % of the variation seen in the population.

The second QTL is on 5BL, covering a 1.6 cM region with a peak at 53 cM between the markers 5B_29636 and 5B_67642. It explains 31.16 % of the variation seen in the population. These two QTL may be the Ne1 and Ne2 genes but scoring would perhaps have to be repeated to verify the QTLs across years. It is likely that these QTLs were only seen in the CF population since both SF and SC had few lines expressing the trait included in genotyping, whereas CF had more lines expressing the trait that were included in genotyping.With persistent predictions of climate change and increased incidence of drought, crop root systems have gained serious attention. One of the challenges in this line of research is which root traits to focus on and in what environments these traits would be important; another one is to understand how root system traits are associated with one another and what trade-offs at the whole plant level are involved. Most root morphological traits appear to be regulated by a number of small-effect loci that interact with the environment. This becomes very apparent even at the earliest stages of experiments looking at root biomass and length. Natural plasticity induced by the environment creates large deviations that often obscure the genetic component of the observable phenotype. For these reasons de Dorlodot et al. suggested that processbased traits such as growth rate, branching frequency and tropism should be studied as opposed to “static traits” such as length, mass, and volume. Some studies have focused on incorporating traits from wild relatives or via new synthetic wheat . Others have looked at associations of root system traits and plant height and many have now begun to focus on seminal root traits. It has been suggested that, in the context of drought,ebb and flow bench roots targeting water acquisition deep in the soil profile may be especially important for smaller statured plants such as rice, wheat, and common bean . By measuring the amount of total water extracted from soil-filled root observation chambers and root growth pattern data Manschadi et al. estimated that each additional millimeter of water extracted during grain filling generated an additional 55kg ha-1 of grain yield.

Lynch proposed an ideotype for maize roots that included narrow seminal root angles with abundant lateral branching which would optimize water and nitrogen acquisition; this ideotype may also be relevant to other cereal root systems. Narrow seminal root angle generates a root system growing more downward into the soil profile, and presumably, reaching lower soil levels. In contrast, a wide angle of seminal roots appears to promote lateral root growth, a habit that may be beneficial in wetter conditions and under artificial irrigation. With frequent irrigation or rainfall, a root system distributed mainly in the upper soil layers would presumably provide quicker access to water and nutrient, without any cost to the plant for building deep-reaching roots. Oyanagi first began to investigate the inheritance of the geotropic response of seminal roots in wheat and concluded that the trait was simple, being controlled by a single locus, and his continued work contributed to the basis for our understanding of seminal root angle physiology in wheat . Those studies made observations on root distribution patterns and seminal root growth characteristics dependent upon the target environment for which specific cultivars were selected. Typically, cultivars adapted to regions with limited rainfall had narrower seminal root angle and deeper root systems; wheats adapted to environments with higher rainfall and/or irrigation tend to have wide seminal root angles which, presumably, facilitate water and nutrient acquisition from a wider sub-surface area. Following these ideas, Manschadi et al. investigated seminal root angle and discovered a large amount of genetic diversity within the panel of screened cultivars. Their cluster analysis has shown that groups of wheat with similar seminal root characteristics reflected the genetic background and environmental adaptation. Those observations are supported by other research linking root distribution to improved agronomic performance and canopy temperature depression under heat and drought stress . Seminal root traits are relatively simple to score and do not require complex experimental systems. This makes them an aspect of choice in root system studies. Drawing ideas from maize studies, Oyanagi suggested that gravitropic responses of roots would be predictive of wheat root distribution in the soil. That idea was supported by Manschadi et al. who found that root system architecture is closely linked to the angle of seminal root growth at the seedling stage. Those findings led to a suggestion that selection for the growth angle and the number of seminal roots may identify genotypes better suited for drought conditions. Measuring root traits of mature plants in the field is a daunting task; for entire mapping populations it is practically impossible. Perhaps for this reason, seminal root traits of seedlings are the favorite research target as they can be measured in several simple experimental set-ups. For all these reasons, studies of seminal root traits appear justified, by providing observations of simple parameters of root architecture, especially when dealing with hundreds of genotypes at a time. At some point all observations of such proxy indicators would have to be verified by screening in the field with a limited number of genotypes. The results presented here add to earlier foundational work, and begin to unravel the genetics behind some aspects of root system architecture. The emerging picture is far more complicated than originally suggested by Oyanagi . While seminal root angle shows high heritability, it clearly is a quantitative trait with a complicated pattern of inheritance. Seminal root angles and numbers were phenotyped in three doubled haploid populations of bread wheat. These populations were created by pair-wise crossing of three landrace cultivars with contrasting root phenotypes. Cv. Sonora has shallow seminal roots growing at wide angles, and cvs. Foisy and Chiddam Blanc de Mars have deep seminal roots with narrow angles. Crosses were made in a triangular fashion so that each of the three parents is present in two of the populations. This arrangement provides a built in system for verification of QTL identified across populations and genetic backgrounds. Detailed information about genotyping, linkage mapping and general descriptions of each population can be found in the previous chapter of this dissertation.