University of Saskatchewan Research Archive
Not a member yet
14369 research outputs found
Sort by
The Effect of Germination on the Physicochemical, Functional, and Nutritional Properties of Yellow Pea, Red Lentil and Green Lentil Flours
Get PDFAbstract
Pulses have been a staple protein in many vegetarian and low-cost diets in the Middle East and Asia. In recent years, their popularity has also risen in Western diets, as more consumers are turning to plant-based proteins instead of animal derived products. Germinating pulses have been shown to improve their nutritional values in multiple ways; by increasing protein contents, improving the amino acid scores, and improving digestibility of the raw seed. In this study, yellow peas, green lentils, and red lentils were germinated for up to three days. The germinated seeds were milled into flour, and several properties of the flours were analysed, including their compositional changes, and physicochemical properties, such as water and oil holding capacity, foaming, and emulsifying properties, and protein solubility. The flour was also analysed for α-amylase activity, starch digestibility, and pasting properties. Overall, germination of pulses had significant impacts on the composition and functionality of the pulse flours. The protein content increased in flours from germinated seeds, whereas the starch content decreased. The resulting flours showed improved water holding capacity, emulsifying activity and capacity, and reduced protein solubility. The foaming capacity of each flour varied with length of germination. The lentil flours were much lower in viscosity in flours from the germinated seeds, while in yellow pea, the effects of germination did not have as large of an impact. The pasting temperature of each pulse flour was also lower than untreated flour when derived from the germinated seed. Germination had varied effects on the nutritional properties of pulses. The in-vitro protein digestibility corrected amino acid score (IV-PDCAAS) of yellow peas was highest in the soaked sample. In red and green lentils, the in-vitro protein digestibility (IVPD) decreased after germination, resulting in a decrease in the IV-PDCAAS. The starch digestibility of all three pulses was improved by germination. In all samples, the percentage of rapid digesting starch (RDS) and slow digesting starch (SD) increased after germination, while the percentage of resistant starch was highest in soaked seed samples, then decreased with germination time.
Radio Frequency Power Amplifiers Adapted For Low Field Magnetic Resonance Imaging
Get PDFMagnetic Resonance Imaging (MRI) is a reliable and established minimally invasive imaging technique that can provide diagnostically relevant information about the internal structures of the human body. While the basic design of the new MRI scanners is not much different from when they were first designed a few decades ago, finding new ways to modify these big, power-hungry, expensive and complex systems is becoming more and more essential. One of the ways of removing the restrictions that conventional MRI systems have is making them low field. This leads to lighter, smaller, simpler and less expensive MRI scanners that can potentially become portable. Once they are portable, MRI scanners can have various applications ranging from being used in emergency and operating rooms to being taken to remote areas and even outer space. The Space MRI Lab at the University of Saskatchewan focuses on building prototypes of portable MRIs for monitoring astronaut health by using TRansmit Array Spatial Encoding (TRASE). TRASE is an innovative MRI method that operates without relying on noisy, heavy and complex gradient coils. In TRASE, the spatial encoding happens based on the phase gradients of the transmit radio frequency (RF) magnetic field.
TRASE-based MRI scanners have specific requirements. One of those requirements is RF power amplifiers (RFPAs) with high-power RF output, high duty cycle and fast switching times. These characteristics are important for achieving maximal TRASE MRI resolution. However, since no commercially available RFPA with these specifications exists, it was necessary to build RFPAs customized for TRASE applications. A class A/B Ham radio power amplifier design was modified to be more compatible with TRASE-based MRIs. As part of this thesis, two of these RFPAs were constructed at the University of Saskatchewan Space MRI Lab. The RFPAs were assembled to be used with the Merlin MRI, an ankle-sized portable MRI tested in zero-gravity which uses TRASE. Fortunately, both of the RFPAs showed expected results at the testing stage and have since been integrated with the Merlin MRI. Details of the assembly work are presented in this thesis
Increasing Fusarium Head Blight Resistance Breeding Resources in Bread Wheat
Get PDFFusarium head blight (FHB), caused by Fusarium spp., is a destructive disease of cereal crops globally. It causes decreased yield, loss of quality, and potential mycotoxin contamination of harvested grain. Integrated pest management (IPM) strategies are required to mitigate the effects of FHB; using cultural control methods, appropriate fungicide application, and planting varieties with moderate or higher resistance ratings are used in combination. Planting a variety with elevated resistance is a vital component to IPM; however, there are limited resistant varieties available to producers. Breeding for FHB resistance is complicated, and sources of resistance are few. A continual search is ongoing for novel sources of resistance and other resources to aid in breeding efforts. The objective of this thesis is to aid in this search for novel sources of resistance and additional resources. Within this thesis, 11 minor and one major quantitative trait loci were identified in a RIL population with Agropyron repens L. ancestry; a wild relative to wheat identified as a possible source of FHB resistance. A detached leaf assay was also investigated in the hopes of saving time and resources in FHB resistance breeding. One moderately, inverse correlation was identified between incubation time and deoxynivalenol content in barley. Additionally, a phenotypic evaluation and preliminary Genome Wide Association Study was performed on Plant Gene Resources of Canada accessions. Four accessions were identified to have elevated FHB resistance based on best linear unbiased predictors. Thirteen SNPs were also associated with resistance within the population. The results of this thesis will aid wheat breeders in their efforts to breed for FHB resistance
The effect of grain elevator market concentration on Saskatchewan farmland prices
Get PDFIn western Canada, grain elevators assume a central role in the Grain Handling and Transportation
System (GHTS). Over the decades, the GHTS has undergone important changes. First, the number of grain
elevators has declined rapidly, and older elevators have been replaced by larger and more efficient elevators.
This resulted in increased average market concentration ratios of grain elevators and increased length of
truck haul by farmers. Second, the removal of the single desk seller power of the Canadian Wheat Board in
2012 affected the way GHTS operates. After the removal of the CWB, grain elevator companies were left
to handle both marketing and logistics (C¸ akir and Nolan, 2015). This change resulted in the removal of the
CWB as an established participant in the GHTS and it became legal for Canadian grain farmers to sell their
grain to whomever they choose.
We examine the effect of grain elevator market concentration on Saskatchewan farmland prices. We
present two models of market concentration. Market power is measured by the total number of elevators
within a radius of farmland or by the distance between elevators. In order to measure efficiency, we consider
the total capacity of elevators within a radius around a farmland or the capacities of the closest grain
elevators.
Our specification explains farmland prices based on market power and capacity variables. Overall, consistent with the economic theory, the models suggest that as the local market power measures increase,
the farmland prices decrease after 2012. Furthermore, contrary to the general economic theory, the efficiency measures are negatively related to farmland prices. For the most part, the results of both models are
consistent
A Novel Centrifugal Microfluidic Approach for Magnetic Circulating Tumor Cell Separation of Blood Cells Through Biocompatible Magnetite-Arginine Nanoparticles
No full textThe abstract of this item is unavailable due to an embargo
Ultrasonic and Fungal Pretreatment of Switchgrass for Biofuel and Bioproduct Applications
No full textThe abstract of this item is unavailable due to an embargo
Predicting the Genotype to Phenotype Relationship in Plants using Machine Learning and Deep Learning
Get PDFWith advancements in science and technology, it has become easier and faster to perform complex computations in a matter of a few minutes. Combined with the evolution in the area of artificial intelligence, machine learning has taken the world by storm. The availability of programming libraries with built-in machine learning methods has made it commonplace to use machine learning in order to solve tasks from all fields of science. The economical and computational feasibility to generate dense genome-wide markers has also grown because of advancements in marker and genotyping technology. An amalgamation of these has opened up the potential to improve the process of agricultural development. Indeed, the tasks of genomic prediction and genomic selection can be performed swiftly and offer the potential to reduce the cycle time in plant breeding by making accurate phenotypic predictions for the crops to be grown.
In this study, we compare and evaluate the performance of computational models for the tasks of genomic prediction and genomic selection on four publicly available datasets of different species of agricultural crops. We examine and quantify the capability of various computational models to accurately predict the phenotypic values and determine the top-ranked samples to be used for the next breeding cycle.
We also look at two methodologies to determine the important genomic markers, and compare their performance. We found that convolutional neural network models based on different architectures were able to make the best predictions and were capable of solving the tasks of genomic prediction and genomic selection. We also found that the entropy-based methodology performed well for the task of determining the important genomic markers, and it aided the computational models in achieving higher prediction accuracy.
Finally, we created and presented a web application built to solve the tasks of genomic prediction, genomic selection, and marker assessment in one place. The web application is aimed at solving the discussed problems in an easy and intuitive manner by users
Molecular epidemiology and diagnostics for Echinococcus multilocularis in canid definitive and intermediate hosts
Get PDFEchinococcus multilocularis shed by canid definitive hosts causes alveolar echinococcosis (AE) in rodent intermediate hosts as well as human and dog aberrant hosts. AE is debilitating in humans and dogs, resulting in serious health challenges and expenses for both veterinary and public health. This thesis addresses needs to improve molecular and serological diagnostics for E. multilocularis in wild canids and dogs. I adapted and evaluated an in-house copro-qPCR-MCA which has comparable diagnostic sensitivity and specificity with the ‘gold standard’ adult cestode recovery, and superior diagnostic sensitivity (92% vs 39%) when compared to conventional fecal flotation techniques. I demonstrated E. multilocularis prevalence of 72% in coyotes in Saskatchewan, a highly endemic region, and using the copro-qPCR-MCA, 17% in coyotes from a newly endemic and highly populated area of British Colombia, and 10% in foxes from islands in the western Canadian Arctic. I also demonstrated parasite stage specificity of the Em95 antigen for serological diagnosis of canine AE in coyotes with intestinal infections, suggesting that serology for the Em95 antigen is likely to be an excellent tool for detecting cases of AE in dogs in North America, where this disease is increasingly described. My thesis also described 27 cases of canine AE from western Canada, highlighting important clinical, epidemiological, and economic information for veterinary practitioners and dog owners and indicating that dogs with AE may serve as indicators of parasite range expansion and risk to humans. Finally, molecular epidemiology revealed that the haplotypes present in intestines of wild canids and AE cases in dogs and humans in prairie regions of western Canada are highly pathogenic and zoonotic European strains, compared to the N2 strain previously described in central North America. In the western Canadian Arctic, my thesis reports, for the first time, that the established haplotype of E. multilocularis is N1 North American Arctic strain, and not Asian strains reported from the west coast of Alaska, nor the N2 or European strains established in populated regions of southern Canada. Therefore, the Canadian Arctic remains vulnerable to introduction of Asian and European strains with higher zoonotic potential. This thesis provides useful diagnostic tools for large scale prevalence studies of E. multilocularis in canids, as well as data on the molecular epidemiology and prevalence which can guide the formulation of control and prevention policies
Exploring Structural Variant Identification using Current Software, Whole-Genome Alignment Methods, and a Preliminary Study into Graph-based Alternatives
No full textStructural variants (SVs) are genetic sequence rearrangements that play a significant role in many critical biological traits; however, current SV identification tools often produce substantial disparities in their outputs. Additionally, due to low alignment accuracy, most SV identification methods struggle in complex or repetitive genetic regions, introducing errors in the SV results. This struggle with alignment accuracy is especially concerning when considering the highly repetitive nature of plant genomes. Consequently, this thesis addresses four research objectives, including a comparative study of several state-of-the-art SV tools, the creation of a whole genome alignment-based SV calling model, the construction of a quantitative and automated evaluation process to measure the accuracy of SV results, and a preliminary study into the patterns created by simulated SV sequences when modelled using sequence graphs.
First, this thesis proposes a Snakemake pipeline named Structural Variants - Jaccard Index Measure, or SV-JIM, to identify SVs using multiple SV callers and then reduce the disparity and improve the confidence of SV results. SV-JIM contains several existing SV callers that take raw sequencing reads or genome assemblies as input. It uses these callers as a foundation to generate SV sets supported by multiple types of evidence and results. Further, this work evaluates inter-caller consistency and examines several patterns produced by their results through an aggregation approach. SV-JIM was validated using datasets from several species, including Brassica nigra, Arabidopsis thaliana, and Homo sapiens, which permitted a detailed survey of its results with different-sized genomes. The human genome data allowed SV-JIM to be benchmarked against known SV locations to assess its precision, recall, and F1 scores. Using the benchmark, the SV callers contained in SV-JIM achieved precision and recall rates as high as 67% and 90%. The benchmark served to identify top performers and provided insights into finding the optimal amount of consensus between SV callers. SV-JIM is available under MIT license through GitHub at https://github.com/USask-BINFO/SV-JIM.
Second, this thesis proposes a software pipeline named Structural Variant Pattern Scan, or SVPS, to explore using whole genome alignment for SV detection. SVPS takes whole genome alignments (WGA) as input and detects SV locations based on patterns found in the input WGA. Several quantitative and automated processes to improve the thoroughness of SV result verification are incorporated within SVPS to evaluate the precision of its results when validated using Brassica nigra and Arabidopsis thaliana data. Using these data, SVPS demonstrated high precision rates above 90% for most SV types. In addition, the experiments used multiple whole genome alignment software configurations to study the effect of alignment sensitivity on SV results, suggesting that differences in sensitivity can reduce the granularity of alignment gaps and distort which regions are reported. SVPS is available under MIT license through GitHub at https://github.com/USask-BINFO/SVPS.
Last, this thesis explores using k-mer and string graphs to model biological sequences and examine any patterns created by variations at known SV locations. Several basic k-mer and string graphs were constructed using simulated sequences containing a single SV to identify graph patterns that could be used to detect SV locations algorithmically. These graphs also revealed several complexities in the graphs' construction, including a string graph's tendency to represent identical subsequences using different vertices. This led to a greedy approach to their construction. Further, these experiments also identified several desirable graph features to explore in future research, including providing single base SV breakpoint resolution between vertices and allowing genetic sequences to traverse vertices in both the forward and reverse orientations
