Browsing by Author "Heuberger, Adam, committee member"
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Item Open Access Assessment of methods to screen for carotenoids in yellow-fleshed potato germplasm(Colorado State University. Libraries, 2020) Logrono, Jeremy Brandon, author; Holm, David G., advisor; Jayanty, Sastry, advisor; Heuberger, Adam, committee member; Byrne, Patrick, committee memberRapid Evaporative Ionization Mass Spectrometry (REIMS) has the capability to rapidly perform tissue analysis without sample preparation, extractions or chromatography required. The study was conducted to evaluate REIMS as an efficient platform to identify carotenoids in yellow-fleshed potato germplasm (N = 60) from the Colorado Potato Breeding and Selection Program. The specific aim eventually is to improve selection efficiency and accelerate genetic gain in nutritional quality of potato cultivars. Phenotypic tuber flesh color (FC) rating (0 – 3), chroma values, and individual and total carotenoids data were collected, processed and combined with multivariate analyses to help in REIMS data interpretation. Results showed that orange-fleshed (FC 3) potato genotypes gave significantly higher overall carotenoid content (P <0.0001) compared to the white-fleshed (FC 0), yellow-fleshed (FC 1) and dark yellow-fleshed (FC 2) genotypes. Zeaxanthin was the major carotenoid detected among the 60 selections/cultivars evaluated. The association between tuber flesh chroma and carotenoid content was analyzed. Results from Pearson correlation analysis revealed positive correlations overall. The correlation coefficient values (r) for lutein vs. chroma (r = 0.56, P < 0.01), zeaxanthin vs. chroma (r = 0.60, P < 0.01) and total carotenoid vs. chroma (r = 0.63, P < 0.01) were considered moderate. A metabolite mass fingerprint for each replicated sample was collected via REIMS to build a data matrix and processed to test the fit with prediction models. Multivariate methods of analysis (MVA) of principal component analysis (PCA), partial least square (PLS) and orthogonal-PLS (OPLS) were created to determine any sample differentiation among the yellow germplasm. FC rating data (0 – 3) were integrated to MVA models as a covariate. Rep 3 samples were excluded in all MVA analyses due to high presence of noise in the raw data. PCA of Reps 1 and 2 (n = 95) showed a predictive power of 48.4% (Q2). No apparent trends or separations based on flesh color was observed in the PCA model. PLS and OPLS supervised models illustrated better differentiation among sample components. OPLS model (n = 71) of high carotenoids (FC 3) vs. low carotenoids (FC 1 & 0) with a predictive power of 56.1% (Q2) was considered the best model due to clear separations of high vs. low carotenoid samples. Loadings and variable importance score (VIP) data were also analyzed to rank metabolite masses that contributed to differentiation of samples, detecting mostly lipid class molecules. Precursor molecules of lutein and zeaxanthin were not detected from the REIMS analyses and carotenoid fragmentation products were most likely contributing to differentiation among samples. Further research is needed to verify identification of carotenoid fragmentation in REIMS as well as the use of more portable and cost-efficient devices.Item Open Access Assessment of rapid evaporative ionization mass spectrometry (REIMS) to characterize beef quality and the impact of oven temperature and relative humidity on beef(Colorado State University. Libraries, 2018) Gredell, Devin, author; Woerner, Dale, advisor; Belk, Keith, committee member; Engle, Terry, committee member; Prenni, Jessica, committee member; Heuberger, Adam, committee memberThe objective of experiment 1 was to evaluate the ability of rapid evaporative ionization mass spectrometry (REIMS) to predict beef eating quality characteristics. Striploin sections (5 cm in thickness; N = 292) from 7 beef carcass types (Select, Low Choice, Top Choice, Prime, Dark Cutter, Grass-fed, and Wagyu) were collected to achieve variation in fat content, sensory attributes, tenderness, and production background. Sections were aged for 14 d, fabricated into 2.54 cm thick steaks, and frozen until analysis. Trained descriptive panel rated tenderness, flavor, and juiciness attributes for sensory prediction models. Slice shear force (SSF) and Warner-Bratzler shear force (WBS) values were measured to predict tenderness classifications. A molecular fingerprint of each sample was collected via REIMS to build prediction models. Models were built using 80% of samples that were selected randomly for this purpose and tested for prediction accuracy using the remaining 20%. Partial least squares (PLS) discriminant analysis was used as a dimension reduction technique before building a linear discriminant analysis (LDA) model for classification. When Select and Low Choice samples, as well as Top Choice and Prime samples, were combined, balanced prediction accuracy reached 83.8%. Slice shear force and WBS tenderness classifications (tough vs tender) were predicted with 75.0% and 70.2% accuracy, respectively. Sensory models were built to assign samples into positive and negative classifications based on either all sensory attributes (i.e., tenderness, juiciness, and flavor) or only flavor attributes. Overall sensory class was predicted with 75.4% accuracy and flavor class with 70.3%. With future fine-tuning, these data suggest that REIMS produces a metabolic fingerprint to provide a method to meaningfully predict numerous beef quality attributes in an on-line application. The objective of the second study was to evaluate the roles of cooking rate and relative humidity on sensory development of beef strip steaks. Thirty USDA Choice beef strip loins were collected from a commercial packing facility. Each strip loin was cut into steaks and randomly assigned to 1 of 6 cooking methods utilizing 2 oven temperatures (80°C and 204°C) and 3 levels of relative humidity [zero (ZH), mid (MH), and high (HH)]. Cooked steaks were used to evaluate internal and external color, Warner-Bratzler and slice shear force, total collagen content, protein denaturation, and trained sensory ratings. Relative humidity greatly reduced cooking rate, especially at 80°C. Steaks cooked at 80°C-ZH had the greatest (P < 0.01) cook loss of all treatments, and cook loss was not affected (P > 0.05). Steaks cooked at 80C-ZH appeared the most (P < 0.01) well-done and had the darkest (P > 0.01) surface color. Total collagen was greatest (P < 0.01) in steaks cooked with ZH, regardless of oven temperature. Myosin denaturation was not affected (P > 0.05) by treatment. Increased (P = 0.02) sarcoplasmic protein denaturation was observed with ZH and MH, while increased (P = 0.02) actin denaturation was observed only with ZH. Oven temperature did not influence (P > 0.05) protein denaturation. Trained panelists rated steaks most tender (P < 0.01) when cooked at 80°C and with ZH and MH. Humidity did not affect (P > 0.05) juiciness at 204°C; however, MH and HH produced a juicier (P < 0.01) steak when cooked at 80°C. Humidity hindered (P < 0.01) the development of beefy/brothy and brown/grilled flavors but increased (P = 0.01) metallic/bloody intensity. Lower oven temperatures and moderate levels of humidity could be utilized to maximize tenderness, while minimally affecting flavor development.Item Open Access Capabilities of rapid evaporative ionization mass spectrometry to predict lamb flavor and overview of feeding genetically modified grain to livestock(Colorado State University. Libraries, 2019) Gifford, Cody Lynn, author; Woerner, Dale, advisor; Belk, Keith, committee member; Engle, Terry, committee member; Prenni, Jessica, committee member; Heuberger, Adam, committee memberThe objective of experiment 1 was to evaluate the ability of rapid evaporative ionization mass spectrometry (REIMS) to predict characteristics of cooked sheep meat flavor using metabolomic data from raw samples. Boneless leg samples were obtained from 150 carcasses of sheep representing three age classifications (n=50 per age classification), at three USDA inspected harvest facilities located in Colorado and California, between October 2017 to June 2018. A trained descriptive panel rated seven flavor attributes. Metabolomic data from fat, lean and ground patties from legs of sheep carcasses were captured through the REIMS platform. Principal component analysis factor scores were used in hierarchical cluster analysis to assess two-level and three-level sensory clusters. Partial least squares (PLS) was used to reduce dimensionality of data before the linear discriminant analysis (LDA) model was built. Eighty percent of the samples were randomly selected to train models and the remaining 20% were used to test prediction accuracy. Mutton carcasses were identified with 88.9% sensitivity and 80.0% precision using external fat of the leg and with 100% sensitivity and 90.9% precision using ground patties. Yearling carcasses were identified with 85.7% precision using lean and lambs were predicted with 70% precision using lean and fat tissue. Greater than 80% accuracy (overall and balanced), sensitivity and precision was achieved in models using lean and ground patties to identify production background (whether the live animal that produced the lean or ground patties was grain-finished or grass-finished). Prediction accuracies of age classification, production background and two-level flavor performance categories were 68% or higher with various machine learning algorithms coupled with data dimension reduction approaches. Further work is warranted to validate use of this technology in an on-line production setting and additional datasets could be used to further refine or create additional prediction models with better understanding of data processing characteristics. The review was conducted to assess the scientific literature for evidence of altered health effects in livestock species that have been fed genetically modified grain and any health effects discussed in reference to human consumption of meat products from those animals. Public concern still exists for feeding genetically modified (GM) or genetically engineered (GE) corn to animals that produce animal protein foods. In the U.S., 90% of all corn acres planted in 2013 were from single herbicide or insect resistance GE corn varieties. Regulation of GE crops is mandatory in the U.S. and consists of review and approval by three different Federal agencies. Substantial equivalence is a principle used in evaluating the safety of GE crops to establish that transgenic (GE or GM) varieties are nutritionally similar and as safe as non-transgenic crops. Animal feeding trials can provide further information to establish the safety of GE crops for human and animal consumption. No publications were found that had reported human metabolic effects from consuming beef cattle fed genetically modified grains. No consistent conclusions have been made that feeding GE corn to mice or rats, beef or dairy cattle, swine, or poultry causes any adverse effects to health. Parameters regarding sample size, diet treatments and specified controls exist to guide researchers in designing animal feeding trials with GE crops, but many criticisms of the scientific literature still exist. Additionally, published feeding trials conducted with transgenic corn grain and silage in beef cattle are limited.Item Open Access Cytokinin-mediated processes promote heat-induced disease susceptibility of plants to bacterial pathogens(Colorado State University. Libraries, 2021) Shigenaga, Alexandra Marie, author; Argueso, Cristiana, advisor; Bush, Dan, committee member; Leach, Jan, committee member; Heuberger, Adam, committee member; Nishimura, Marc, committee memberAs global human populations continue to grow and temperatures are expected to rise, the pressure to increase food productivity and develop more stress-resistant crop varieties intensifies. Increased temperatures, a consequence anticipated as a result of global climate change, is expected to have an overall negative impact on crop productivity and agricultural systems. When exposed to non-optimal, high temperature conditions plant defense responses to pathogen attack are attenuated, leading to a process referred to here as heat-induced disease susceptibility. The plant growth hormone cytokinin is known to regulate responses to both biotic and abiotic pressures, making it an ideal target to study heat-induced disease susceptibility. The overarching goal of this dissertation was to understand the role of cytokinin in heat-induced disease susceptibility, to identify novel strategies to combat this process and design new ways to teach future generations about the impact of climate change on agricultural systems and science policy. First, I identified that a plant lacking a functional cytokinin signaling pathway, ahk2,3 mutated on the cytokinin signaling receptors AHK2 and AHK3, was less susceptible at elevated temperatures to the bacterial pathogen, Pseudomonas syringae pv. tomato DC3000 (Pst DC3000). My results show that ahk2,3 plants are less susceptible under high temperature conditions with Pst DC3000 populations proliferating at a lower rate compared to wild-type plants overtime, suggesting that heat-induced susceptibility is partially dependent on cytokininiii signaling. Our results show that differences in susceptibility under elevated temperatures of ahk2,3 and wild-type plants is not attributed to an increase in defense responses, but rather by a possible change in the availability of nutrients for Pst DC3000. Together the data reveals that under high temperature conditions cytokinin promotes late-physiological processes, centered around primary metabolism, that are contributing to increased pathogen proliferation. These results led to the identification of cytokinin-regulated genes that could be utilized for breeding efforts to obtain loss-of-heat induced disease susceptibility that could be translated to crop species. Second, I identified that another member of the Brassicaceae family, Brassica napus, also exhibited heat-induced disease susceptibility to the bacterial pathogen, P. syringae pv. maculicola (Psm ES4326). Gene expression analysis confirms that similar to Arabidopsis, B. napus plants increase cytokinin signaling in response to high temperature stress. To further address if cytokinin was important for heat-induced disease susceptibility of B. napus, I utilized a chemical approach. B. napus plants were sprayed with the cytokinin-signaling antagonist, PI-55, prior to inoculation and results show that a single application of PI-55 led to a loss of susceptibility under heat to Psm ES4326. Additionally, this application of PI-55 did not lead to any adverse vegetative growth parameters, suggesting a potential novel chemical approach to combat heat-induced disease susceptibility in Brassicaceae crops. Lastly, I constructed a new approach to teach future generations about the impact of climate change on plant diseases in agricultural systems. "Plant Diseases and Climate Change" is an active learning activity designed to give college students experience in synthesizing information and developing a solution, in the context of plant pathology. This exercise uses the issue of heat-induced susceptibility of rice in the Philippines to improve student understanding of the interactions between abiotic and biotic factors affecting global food security. By using an international agricultural pathosystem, I aim to inform students how environmental pressures can impact economically important plant systems, the role scientists and experts play in policy making to preserve food security, and the importance of agriculture on a global scale.Item Open Access Day and night for cyanobacteria: systems and synthetic biology approaches to understanding and engineering Synechocystis sp. PCC 6803 under day/night light cycles(Colorado State University. Libraries, 2018) Werner, Allison Jean Zimont, author; Peebles, Christie A. M., advisor; Reardon, Kenneth, committee member; Prasad, Ashok, committee member; Heuberger, Adam, committee memberPhotosynthetic organisms—including plants, algae, and cyanobacteria—harness sunlight as an energy source to grow, utilizing atmospheric carbon dioxide in the process. This ability can be harnessed for the sustainable production of food, fuels, and chemicals, reducing demand for petrol-based products and overall greenhouse gas emissions. Photosynthetic success rests on the efficient and timely capture of sunlight. Natural day/night cycles subject these organisms to changing energy availability, presenting a fundamental question: How do phototrophs regulate metabolism to thrive under daily and dramatic changes in energy supply? This question has significant impact on the productivity of plants, algae, and cyanobacteria. Cyanobacteria have been extensively engineered for the production of biofuels, polymers, and valuable pigments under continuous-light (CL) laboratory conditions. However, industrial production requires outdoor cultivation under diurnal light/dark (LD) cycles, where yield improvements in engineered strains observed in CL are lost in LD cycles. The success of industrially-productive cyanobacteria biotechnology is limited by the lack of appropriate strain engineering tools and gap in knowledge of photosynthetic metabolism under daily day/night light cycles. The aim of this thesis is therefore to improve the feasibility of cyanobacteria biotechnology in industrially-relevant conditions by integrating aspects of diurnal LD cycles into genetic tools and by expanding the current knowledge of dynamic photosynthetic metabolism. The first part of this thesis presents novel genetic engineering tools which enable light-entrained gene expression under diurnal LD cycles. The tools developed here enable engineering of temporally controlled chemical production under diurnal LD cycles, which we hypothesize will improve yield in outdoor cultivation environments. The second part of this thesis presents time-course characterization of growth and metabolite abundance under realistic diurnal LD cycles. Previous work was limited to on/off patterns of low light and restricted to detecting few metabolites. To expand the realism of light profiles and metabolite scope, a photobioreactor was engineered to supply sinusoidal patterns and intensity of light (sinLD cycles), and a multi-platform mass spectrometry workflow was developed to enable semi-comprehensive metabolite detection. Cyanobacteria growth under realistic diurnal sinLD cycles is presented for the first time, to our knowledge. We observe a short lag phase at the onset of day, followed by cell mass increase during the early day, cell division during afternoon and evening, and slight mass loss overnight. Further, comprehensive metabolite abundance every 30-120 minutes across a 24-hour diurnal sinLD cycle is presented. Insoluble C6 carbohydrates displayed sharp oscillations at the day/night transition; insoluble C5 carbohydrates and glucosamine display these in addition to abundance 're-sets' at the night/day transition. Free amino acids and nucleic acids increase immediately upon transition to light during the lag phase, followed by gradual incorporation into protein during the mass accumulation phase. Metabolites involved in central metabolism did not oscillate to the same extent as other pathways. Accumulation of phosphoenolpyruvate but not pyruvate during the light phase suggests a potential bottleneck. Integration of the metabolomics data into genome-scale metabolic models to perform dynamic flux balance analysis could improve the method by which engineering targets are identified for production in outdoor conditions. Together, this thesis demonstrates the need for revision of the current approach to cyanobacteria strain engineering. More broadly, this work highlights the dynamic nature of photosynthetic metabolism and motivates future investigations into metabolic regulation and metabolic flux under realistic day/night cycles.Item Open Access Evaluation of the effectiveness of supplemental lights vs no supplemental lights on hydroponically grown lettuce(Colorado State University. Libraries, 2017) Al-Houti, Fatima, author; Newman, Steven, advisor; Heuberger, Adam, committee member; Bunning, Marisa, committee memberThe purpose of the study was to examine the literature from the past 20 years regarding the evaluation of the Effectiveness of Supplemental lights vs No supplemental lights on Organic and Synthetic lettuce production via hydroponically growing lettuce in a greenhouse. The two types of lettuce are 1) green salad bowl and 2) gourmet blend mix. This research was conducted in the Colorado State University, Ft. Collins (CSUFC). The Researcher used quantitative research design with basic agricultural, horticultural, quantitative, and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) quantitative statistical calculations. This research method addressed agricultural horticulture research findings from agriculturalists, farmers, horticulturalists, policy makers, researchers, scientists, universities, and/or other key stakeholders in the agriculture, farming, greenhouse, and horticulture industry. The student researched the historical and current literature and the effects of altering the Supplemental lights for the maximum growth and development of healthy mineral rich lettuce. Twenty-three minerals were tracked and measured using the ICP-MS after production via Supplemental light vs. No Supplemental light using parts per million (ppm) converted from mg, (ng/g), and other amounts. This Thesis contains five chapters including: (1) Introduction, (2) Literature review, (3) Material and Methods, (4) Results and Discussion and (5) Conclusion. Finally, research recommendations are made for future replications and studies to accentuate and increase the validity and reliability of this study.Item Open Access Genomic and phenomic tools to aid in the utilization of eastern European and central Asian wheat germplasm in U.S. hard winter wheat breeding(Colorado State University. Libraries, 2017) Beil, Craig Thomas, author; Haley, Scott, advisor; Byrne, Patrick, committee member; Jahn, Courtney, committee member; Heuberger, Adam, committee memberTo view the abstract, please see the full text of the document.Item Open Access Impact of unconventional beef carcass rib separation, oven temperature, and degree of doneness on eating quality of beef(Colorado State University. Libraries, 2016) de Paula e Mancilha, Talita, author; Belk, Keith E., advisor; Woerner, Dale R., advisor; Martin, Jennifer, committee member; Heuberger, Adam, committee memberTo view the abstract, please see the full text of the document.Item Open Access Metabolomic profiles associated with physiological resistance to Sclerotinia sclerotiorum (Lib.) de Bary in common bean(Colorado State University. Libraries, 2015) Robison, Faith M., author; Brick, Mark, advisor; Prenni, Jessica, advisor; Schwartz, Howard, committee member; Byrne, Pat, committee member; Heuberger, Adam, committee memberCommon bean (Phaseolus vulgaris L.) is an important global food crop with a recently sequenced and annotated genome. Plant metabolic and hormone processes are being increasingly recognized as central to disease resistance. For common bean, the molecular and metabolic processes that mediate resistance to white mold disease (caused by Sclerotinia sclerotiorum, (Lib.) de Bary) are largely unknown. Identifying metabolites associated with Sclerotinia infection may provide novel targets to breed for enhanced resistance. The metabolic changes that occur during S. sclerotiorum infection of a detached leaf were characterized using a non-targeted metabolomics workflow spanning primary and secondary metabolism, and a targeted panel of 13 hormones. Partial resistant (A195, beige seed coat color) and susceptible (Sacramento, light red kidney market class) Andean bean lines were inoculated with isolate S20 for non-targeted metabolite profiling at 16, 24, and 48 hours post inoculation (hpi) and at 8 and 16 hpi for hormones. Metabolites from healthy tissue adjacent to the necrotic lesion were extracted with the solvent methanol:water (80:20) and detected using non-targeted UPLC-TOF-MS and GC-MS workflows, and hormones were profiled using UPLC-MS/MS. The analysis detected 140 metabolites that varied between A195 and Sacramento, with the greatest metabolite variation occurring at 16 hpi. The metabolites that varied included amines, amino acids, saccharides, organic acids, phytoalexins, hormones, ureides, and molecules involved in cell wall and membrane composition. The diversity in observed metabolic changes points towards a multi-faceted response associated with plant resistance to S. sclerotiorum in common bean. The integration of metabolomics and genomic data discover functional markers of metabolic resistance to white mold.Item Embargo The influence of genotype, environment, and storage time on the ascorbic acid content and retention in potato germplasm from the Colorado Potato Breeding and Selection Program(Colorado State University. Libraries, 2023) Tikhonova, Olga, author; Holm, David G., advisor; Jayanty, Sastry, advisor; Heuberger, Adam, committee member; Weir, Tiffany, committee memberPotato is a globally consumed vegetable crop known to contain vitamin C, with its active form, ascorbic acid (AsA), serving as a potent antioxidant involved in numerous physiological processes within the human body. The oxidized form, dehydroascorbic acid (DHA) was not measured in this study. Thus, the focus of this thesis was to investigate ascorbic acid in potato germplasm in the Colorado Potato Breeding and Selection Program. However, even if a potato genotype contains a sufficiently large amount of AsA, immediately after harvesting, its content may significantly decrease during storage. Therefore, it is so important to focus not only on the initial AsA content but also on its retention in storage. An investigation was conducted to enhance our understanding of the potential to increase AsA content in potato tubers through traditional breeding. This study examined the variations in AsA levels due to genetic factors (assaying multiple genotypes), environmental conditions (different growing locations), and AsA retention (sampling during storage). This study was divided into 2 parts. In Part 1 (Year 1, 2021), AsA initial level and its retention during storage was investigated in 34 genotypes grown in the San Luis Valley, CO, USA. The initial AsA content ranged from 8.5 to 37.7 mg/100 g FW. All genotypes experienced some level of AsA loss during storage, with the mean loss across all 34 genotypes being 34.8%. Notably, there was considerable variation in both initial AsA levels and retention among the genotypes, with some even exhibiting a temporary increase in AsA content during storage. In Part 2 (Year 2, 2022), six cultivars (selected from 34 from last year) were grown in three different locations to investigate the effect of environmental conditions on the initial content of AsA and retention. Among the genotypes examined, three showed evidence of variation between AsA retention and growing location (time:environment, TxE interaction), indicated by varying slopes. Four genotypes demonstrated variation in initial AsA content over three different locations, representing a genotype:environment, (GxE) interaction. In conclusion, this investigation emphasizes the potential for improving potato tuber AsA content through traditional breeding, while also underscoring the significance of considering both the initial content and retention during storage to maximize nutritional benefits. This research highlights the complex interactions between genetics (genotype), environment (growing location), and storage time that influence AsA retention in this widely consumed vegetable.Item Open Access Transformation of soil organic matter in forest fire impacted watersheds elucidated by FT-ICR mass spectrometry(Colorado State University. Libraries, 2022) Bahureksa, William, author; Borch, Thomas, advisor; Farmer, Delphine, committee member; Ackerson, Chris, committee member; Heuberger, Adam, committee memberSoils provide numerous ecosystem services that are essential to life on Earth, including food security, water filtration and purification, and infrastructure for biodiversity. Soil properties (e.g., soil productivity, moisture retention, structure and aggregation, and nutrient supply) that facilitate these services depend on the soil organic matter (SOM), which can be dramatically impacted from ecosystem disturbances such as wildfires. Wildfires can provide benefits to an ecosystem through the cleaning of the forest floor, soil nourishment, and the removal of competitive underbrush. However, wildfires have grown in frequency and severity around the world, and there is great interest in resolving changes to SOM composition under wildfire conditions to secure water resources and recover fire-affected areas. In the following work, Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was critically evaluated for the analysis of SOM. Data processing methods for FT-ICR MS were investigated to improve compositional analysis. Laboratory-simulated and field-based burn samples were collected and used to investigate changes to water-soluble fractions over progressive series of fire intensity, burn severity, and burn extent gradients. FT-ICR MS currently achieves the highest mass resolving power in the world, which makes it suitable for the study of complex mixtures with tens of thousands of compounds that are separated by mass on the order of a few electrons. Recent strategies for SOM characterization by FT-ICR MS are critically reviewed, with emphasis on SOM sample collection, preparation, analysis, and data interpretation. Importantly, the range of structures, functionalities, and mass means no technique achieves "complete" characterization, and methods used for processing and visualizing FT-ICR MS spectra can influence representation and interpretation of data. The complexity of DOM and influence of post-data processing was demonstrated by studying the effect of peak-picking threshold (3σ, 4σ, 5σ, and 6σ) on a Suwannee River Fulvic Acid standard measured by a custom 21 tesla FT-ICR mass spectrometer. Applying a 3σ peak-picking threshold revealed an additional 13,000 peaks that could be assigned compared to a 6σ peak-picking threshold with a difference of only 12 ppb root-mean-square mass error. Furthermore, isobaric overlaps differing by as little as the mass of an electron are identified up to m/z 1000, and 18O and 17O isotopologues were assigned for the first time in DOM at 3σ. Ecosystem recovery after wildfires in forested watersheds depends on revegetation and soil microbial communities and is therefore limited by the availability of nutrients. The remaining nutrients and substrate available for microbes depends on specific wildfire intensities and are poorly understood. To investigate SOM byproducts during heating and mechanisms that contribute to pyrogenic organic matter (pyOM) formation and mobilization, water-extractable organic matter was extracted from soils heated at discrete temperatures using laboratory microcosms. Relative to the unburnt control, dissolved organic carbon and nitrogen increased at ≥150°C and decreased when ≥450°C. Nitrogen-containing species predominated mass spectra at temperatures >150°C, and mass difference-based analysis suggested that products formed during heating could be used to model transformations along the Maillard reaction pathway. To investigate the short-term impacts of burn extent on water chemistry and dissolved organic matter (DOM) in fire-affected watersheds, streams originating from catchments of low, moderate, and high burn extent within the area of the Cameron Peak Fire of 2020 were sampled before, during, and after the first large rainstorm following the fire. Water chemistry parameters (DOC, TDN, turbidity) for moderate and high burn extents streams tended to increase during the storm and decrease following the storm in high burn extent streams. Fluorescence indices indicated that low/moderate burn extent streams exhibited an increase in microbially-derived residues compared to high burn extent. While a substantial portion of DOM species between every stream were common between each event and included labile and aromatic residues during the storm, the low burn extent exhibited the most unique aromatic features after the storm. When chlorinating stream samples to simulate drinking water treatment, the total DBPs were greater in streams of moderate/high burn extents compared to low burn extent. When DBP concentrations were normalized to DOC, the DOM introduced during the storm resulted in fewer DBPs, suggesting the increase in DBP formation is due to increased DOM loading overall rather than increased reactivity of the DOM. In total, the work presented here contributes to the mechanistic understanding of the residues produced during SOM heating that can be mobilized and impact water chemistry in fire-affected watersheds.