K-State Electronic Theses, Dissertations, and Reports: 2004 -
Permanent URI for this collectionhttps://hdl.handle.net/2097/4
This is the collection for doctoral dissertations and masters theses and reports submitted electronically by K-State students. Electronic submission of doctoral dissertations was required beginning Fall semester 2006. Electronic submission for masters theses and reports was required beginning Fall 2007. The collection also contains some dissertations, theses, and reports from the years 2004 and 2005 that were submitted during a pilot test project. Some items before 2004 have been digitized and are available in K-State Electronic Theses, Dissertations, and Reports: pre-2004. Check the Library catalog for dissertations, theses, and reports not found in these collections.
All items included in this collection have been approved by the K-State Graduate School. More information can be found on the ETDR Information Page. Items within this collection are protected by U.S. Copyright. Copyright on each item is held by the individual author.
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Item Open Access Effects of grain source and feed additive inclusion on processing characteristics and feeding value of swine diets(2025) Friesen, WalterA total of 7 experiments were conducted and structured in 3 chapters to evaluate the effects of grain sources and feed additive supplementation on feed processing characteristics, digestibility of energy and AA, and growth performance of growing pigs. For Chapter 1, two experiments were conducted to determine the effects of Kernza® grain on geometric mean diameter (dgw), Standard deviation (Sgw), angle of repose (AoR), and pellet durability index (PDI). Grinding characteristics were determined by changing hammermill screen hole diameters (2.0 mm, 2.8mm, 3.6mm), while pelleting characteristics were observed by increasing inclusion levels of Kernza® into treatments (0, 2.5, 5, 10, 30%). Increasing screen hole diameter increased dgw and decreased Sgw. Increasing Kernza grain from 0 to 30% of the diet improved PDI from 58.6% to 88.4%. For Chapter 2, two experiments were conducted to determine the effect of 3 sorghum varieties (red non-waxy, red waxy, white waxy) on dgw, Sgw, AoR, and PDI when ground with consistent hammermill settings (Exp.1), or to a consistent dgw of 550µm (Exp. 2). Waxy sorghum had greater dgw and PDI with a lower sgw , and AOR than that of the non-waxy sorghum and corn within Exp. 1. When comparing grain sources at a consistent particle size, waxy sorghum had a lower sgw leading to a more uniform product. Waxy red sorghum diets improved PDI compared to other grain sources. Chapter 3 encompassed three experiments to determine the impact of feed additive premix (FAP; proprietary blend of enzymes, prebiotics, plant extracts, and acidifiers) on energy metabolism, standardized ileal digestibility of AA, and growth performance when fed to pigs with varying diet compositions. Treatments were arranged with 2 levels of FAP (0.0, or 0.13%), and 3 diet types (corn-, sorghum-, sorghum & DDGS-based). Pigs fed corn and sorghum-based diets had similar growth performance and pigs fed sorghum and DDGS-based diets had reduced growth performance. The FAP used in this experiment did not improve growth performance of pigs and even reduced ADG of finishing pigs fed sorghum-based.Item Open Access Susceptibility of ruminant livestock to experimental infection with SARS-CoV-2 and HPAIV H5N1(2025) Cool, KonnerEmerging RNA viruses represent a constant and expanding threat to global public health, agriculture, and biosecurity. The recent panzootics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and highly pathogenic avian influenza virus (HPAIV) H5N1 clade 2.3.4.4b illustrate how host-generalist viruses can infect a broad range of wildlife, companion, and food production animal species, sometimes sustaining transmission and spillover to humans. These events underscore the critical need to understand host susceptibility and potential transmission pathways early in an outbreak. The experiments described here were designed to investigate the susceptibility and transmission potential of ruminant hosts to SARS-CoV-2 and HPAIV H5N1 through controlled experimental infection studies. The objectives were to assess infection outcomes, viral shedding, within host virus competition, host adaptation, and potential animal-to-animal transmission following experimental exposure to each of these pathogens. The resulting data clarified the role of ruminant species in the respective pathogen ecology, reduced the uncertainty about undetected virus maintenance, and informed targeted surveillance and outbreak response. Collectively, these findings advanced our understanding of host range, intraspecies transmission, and the potential for these emerging zoonotic RNA viruses to establish new animal reservoirs.Item Open Access TABLE TALK Impact of Intergenerational food transmission on the nutritional environment and strategies for the prevention of eating disorders(2025) Meek, KathleenThis report examines the role of intergenerational food transmission in the prevention of eating disorders, emphasizing the influence of early feeding practices and family food environments on long-term relationships with food and body image. As rates of disordered eating continue to rise, this research highlights protective strategies rooted in nutrition science and developmental psychology, including shared family meals, responsive feeding using Satter’s Division of Responsibility, and parental modeling of intuitive eating. Through a comprehensive review of current literature, this report explores how food behaviors, attitudes, and language are passed down within families, often shaping a child’s internal regulation and self-perception. Particular attention is given to the impacts of weight-focused talk, food moralization, and restrictive feeding on emotional and physical health outcomes. Findings suggest that fostering autonomy at the table, eliminating shame-based messaging, and creating emotionally supportive food environments can reduce the risk of disordered eating and promote a lifelong, positive relationship with food. The research calls for more inclusive, longitudinal studies across diverse family structures, cultures, and socioeconomic contexts to better understand and apply these findings. This work positions food not just as sustenance, but as a vehicle for connection, identity, and emotional well-being. The research offers a framework for prevention that begins in the home and has the potential to shift generational narratives around eating and body trust.Item Open Access Families of students with exceptionalities: A phenomenological study of the lived experiences of families and public school discipline(2025) George, EmilyIn this study, I explored the lived experiences of eleven Kansas families navigating special education systems and disciplinary practices in public schools. I used a hermeneutic framework to interpret the meanings families ascribe to their advocacy, challenges, and resilience. Participants were limited to families of students with documented disabilities or exceptionalities who were enrolled in and received discipline from a Kansas public middle or high school. I collected data through semi-structured interviews in person and over Zoom and kept a researcher’s journal of my thoughts and responses during the entire research process. I cleaned the transcripts of the interviews and analyzed them using grounded theory approaches informed by Charmaz’s (2025) methodological guidance. I combed the transcripts twice to find recurring ideas, which I grouped into seven themes. Then, I read through the transcripts two more times to search for quotes that highlighted those themes and to check for outliers or discrepancies in my findings. Those findings revealed seven central themes: accessing services or supports, discipline and its effects on student wellbeing, family and school staff relationships, parental advocacy and agency, inequity and bias, familial strain, and informal growth and supports. All participant families described accessing services as a prolonged and continuous process that could be emotionally and financially exhausting. Inequity and systemic bias appeared in surprising ways, such as school staff using overt racial or ableist remarks or with academic performance used to deny formal services or accommodations and to perpetuate misinformation about child development. School staff used informal and formal discipline to promote safety and to discourage undesired behaviors. However, when discipline was exclusionary, it was stigmatizing and reinforced negative student self-perception, often increasing the behaviors the school attempted to decrease. Families reported behaviors being interpreted negatively, rather than being seen as communication or evidence of a skill deficit or underlying need. Teacher relationships emerged as pivotal: supportive educators were transformative influences that anchored the students in schooling, while punitive, traumatizing, or dismissive educators increased student disengagement, distrust of school staff, social isolation, and stress. Parental advocacy was a lifeline for student success, but also a burden, which left parents feeling misunderstood or marginalized. For some families, inequity and bias shaped daily school interactions, with race, disability, previous interactions with the district, academic standing, and narrow eligibility criteria influencing access to services and disciplinary outcomes. These systemic challenges encroached on the home and impacted family stress and dynamics, yet families also highlighted resilience and growth for their students through informal supports and affirming spaces, especially those within extracurricular activities. This study contributes to scholarship on family experiences in special education and public-school discipline through parent and student voices. The findings underscore the impact of school staff responses to and perceptions of students and the deleterious effects on student wellbeing when these are negative or punitive. While the participants mostly communicated neutral or negative experiences, the study findings also emphasize the transformative potential of supportive relationships. Implications for changes in practice include the need for consistent, individualized supports, trauma-informed and restorative disciplinary approaches, supported family-school partnerships, and an overall deeper understanding of students’, and their families’, experiences. In the conclusion, I recommend changes in school policy that highlight the importance of upholding the mandates of IDEA (Individuals with Disabilities Education Act, 2004), addressing the effects of exclusionary discipline, increasing access to information and supports, and strengthening the school-family-student relationship, especially for those students in need of support, such as those for whom the school issues a disciplinary action and those with disabilities or exceptionalities. Ultimately, this study calls for educational systems to move beyond deficit-based perceptions and toward practices that affirm the strengths and individuality of all students and their families.Item Open Access Evaluating U.S. Purity Culture’s Impact on Female Sexual Health and Development(2025) Pugh, Mary-JoyThe purpose of this research was to investigate the impact of Christian purity culture on the sexual health and development of emerging adult women in the United States. Using self-determination theory and social script theory, the research explores how exposure to purity culture and the internalization of Christian messages via identification and introjection impact sexual health outcomes, including functioning, guilt, pleasure, and first coital affect. The study also examines mediating and moderating variables including age and relationship status at the time of first intercourse. Using a mixed sample (N = 300) of college-attending and national panel participants, women aged 18-29 were asked to complete a retrospective online Qualtrics survey assessing exposure to purity culture, sexual health indicators, and religious internalization. Path analyses were conducted to test three hypotheses referencing the relationships among purity culture, religious internalization, and sexual health outcomes. Results indicated that exposure to purity culture beliefs in childhood is associated with poorer sexual health outcomes in emerging adult women, particularly when religious values are internalized through introjection rather than identification. Identification, while also associated with guilt, was positively associated with sexual pleasure, functioning, and older age at first intercourse, suggesting a buffering effect against the negative impacts of purity culture. Guilt was identified as a mediating factor in sexual health outcomes, and relationship status was found to moderate associations between purity culture and introjection, purity culture and guilt, and introjection and guilt. Findings contribute to a deeper understanding of how religious socialization and sexual scripts influence female sexual development and may inform future sexual education and mental health interventions. Ultimately, purity culture has a net negative influence on women’s sexual health outcomes, although the way its messages are internalized can mitigate the impact.Item Open Access The impact of effort on the search for information(2025) Payne, KarissaIn everyday environments, people encounter vast amounts of information but are limited in what they can realistically use in making decisions. Because acquiring information often requires effort, individuals may favor less demanding sources even at the expense of their accuracy. However, it remains unclear how effort costs and the predictive validity of information jointly shape information search in decision-making. This study investigates how these factors interact in probabilistic environments. Across two experiments, participants explored a two-dimensional digital environment, using their mouse cursor to uncover cue information used to predict answers in a two-alternative forced choice task. Cue predictive validities ranged from 50% to 100%, and effort was manipulated through cursor speed and cue distance. Experiment 1 tested how effort costs and predictive validity influenced sampling when validities were explicitly presented on screen, whereas Experiment 2 required participants to learn predictive validities through trial and error. In both experiments, higher effort reduced sampling of less valid cues, while perfectly predictive (100%) cues were consistently prioritized even under greater effort, demonstrating a certainty effect in information search. When predictive validities were hidden in Experiment 2, effort exerted a stronger deterrent effect than it did when predictive validities were known (Experiment 1), and individual variability in exploration strategies increased. Analyses further indicated that participants treated perfectly predictive cues as categorically distinct, and the functional form of effort’s influence was similar to that of a delay discounting curve. Together, these findings support a cost-benefit view of information search, in which people weigh expected information gain against the cost of effort. Effort constrains information sampling, but perfectly predictive information resists the cost of effort much more than less predictive information.Item Open Access Habitat and adaptive foraging impacts on the topology and conservation of plant-pollinator interaction networks(2025) Poyner, HeatherPlant-pollinator mutualistic interactions are crucial for maintaining global biodiversity. Therefore, it is important to identify the behaviors that confer stability to these communities by evaluating emergent patterns of community organization using network analysis for effective biodiversity conservation. In the U.S. Great Plains, habitat loss resulting from agricultural intensification has contributed to steep declines in pollinator populations. Private land conservation programs such as the Conservation Reserve Program (CRP) offer a potential solution to declining pollinator populations. However, most work has focused on bees with less effort to assess overall pollinator community structure in these conservation plantings. In addition to studying simple metrics of diversity, plant-pollinator network topology can provide insight into the behavior and ecological dynamics that structure these communities, such as adaptive foraging. Although theory has often implicitly assumed that plant-pollinator interactions are static, there is mounting evidence that pollinator species continually switch the plant species with which they interact to maximize energy gain per cost and enhance the efficiency of resource utilization. Pollinators may adapt their foraging choices to maximize mutualistic benefits or minimize competitive costs, but it is difficult to separate these influences on community structure and stability empirically. To address these issues, I performed empirical observations of plant-pollinator interactions on different CRP planting types as well as non-CRP grasslands and simulated plant-pollinator community dynamics with different adaptive foraging strategies. The objectives of this work were to: a) evaluate how local- and landscape-scale habitat characteristics influence the effectiveness of CRP planting types in supporting pollinator communities and b) examine how different adaptive foraging strategies and pollinator dependence on plants impact community stability and the resulting network topology in comparison to empirical networks. Pollinator community composition differed across CRP planting types, whereas pollinator abundance and diversity were more influenced by site-specific habitat characteristics, such as forb species richness and grassland habitat availability. Habitat characteristics had an interactive effect on pollinators such that landscape-scale habitat availability modulated the availability and diversity of pollinators that could use floral resources within CRP plantings. Plant-pollinator networks were specialized and modular, indicating that pollinator foraging decisions are guided more by niche partitioning in response to the abundance of competitors and the diversity of floral resources. In the simulation model, adaptive foraging resulted in less stable pollinator communities but larger pollinator populations, which suggests that without interaction switching interspecific competition kept pollinator populations at lower densities, but not so low as to result in competitive exclusion. Additionally, empirical network topology was most similar to that of simulated networks when pollinators were highly dependent on plants for survival. These findings offer insights into how the habitat characteristics of conservation plantings impact pollinator communities while highlighting the ecological dynamics that confer stability to plant-pollinator networks.Item Open Access Uncovering Hidden Patterns in Flight Safety Data Through Statistical Analysis(2025) Vandervort, MaxThis research aims to identify trends in data that indicate a potential increase in the risk of aviation accidents. By analyzing aviation incident historical data, we look at the relationship between incidents on the ground and those in flight, as well as minor incidents and major incidents within an Army aviation unit. Machine learning algorithms applied to data sets involving crew experience and mishap reports may determine whether indications exist that forecast a higher risk of an aviation incident for an aviation organization within the U.S. Army. Achieving zero preventable mishaps regarding aviation operations requires a proactive approach to hazard identification and risk management, which is explored in the methods of this project. The results from the analyzed data determine if any consistencies exist in the conditions within an aviation unit leading up to recordable mishaps.Item Open Access Diagnostic approaches to transboundary and zoonotic diseases(2025) Bold, DashzevegTransboundary animal diseases (TADs), including those caused by African swine fever virus (ASFV), Classical swine fever virus (CSFV), and Foot-and-mouth disease virus (FMDV), as well as highly contagious zoonotic agents such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), pose significant threats to agriculture and public health globally. Early detection and follow-up measures are critical for the management of these infectious diseases. In the laboratory, polymerase chain reaction (PCR) is the most commonly used method for diagnosing these pathogens; however, in order to rapidly identify and prevent the spread of these highly infectious viruses, point-of-care (POC) diagnostic assays for the detection of the pathogen’s genetic materials, antigens (Ag), and antibodies (Ab) in the field are necessary. In this dissertation, lateral flow assays (LFAs) for ASFV Ag and Ab detection, multi-antigen print immunoassays (MAPIAs) for ASFV and FMDV Ab detection, and indirect ELISAs for SARS-CoV-2 Ab detection were established. It was also demonstrated that POC approaches used in a low-income country were able to identify ASFV, CSFV, and FMDV genetic sequences in suspect materials, proving the feasibility of POC diagnostics for these pathogens in low resource environments. As a result of this thesis, valuable tools were generated for improving the detection and diagnosis of ASFV, CSFV, FMDV, and SARS-CoV-2.Item Embargo Evaluating the Efficacy of Nutrient Solution Reuse in Hydroponics(2025) Tetteh, MillicentNutrient solution reuse in hydroponics is a sustainable strategy to improve resource efficiency. However, increased microbial risks, nutrient toxicity, and accumulation of allelochemicals can compromise system safety and crop yield. The first objective of this study they are not specifically tailored to hydroponic nutrient solutions. This review synthesizes current knowledge on the risks and opportunities of nutrient reuse in hydroponic systems, highlighting emerging treatment technologies and the urgent need for hydroponics-specific, science-based standards to ensure both sustainability and food safety to support production by small scale farmers. In the second objective, we evaluated the combined performance of slow sand filtration (SSF), biochar filtration, and UV-C disinfection for multi-cycle reuse of hydroponic nutrient solution in romaine lettuce production and assessed the impact of treated nutrient solutions use of plant growth and nutritional quality. Results showed that SU (SSF + UV-C) and SBU (SSF + Biochar + UV-C) consistently achieved ≥5 log₁₀ reductions of E. coli, meeting World Health Organization (WHO) microbial safety criteria. Physically, turbidity remained <2 NTU, and SBU showed the highest light transmittance. Chemically, both treatments reduced ammonium-N, total N, and total P, with SBU showing the highest removals. However, nitrate levels remained relatively stable, calcium steadily accumulated across cycles, and pH in SU and C fell below Food and Agriculture Organization (FAO)/World Health Organization (WHO) guidelines. Micronutrient analysis revealed substantial declines in Fe, Zn, Cu, and Mn—up to 90–97% in SBU resulting in progressive micronutrient imbalance despite EC-based nutrient supplementation. Romaine lettuce grown in SU initially produced the highest biomass but declined by ~30% across cycles, while SBU showed even larger reductions (~45%). Chlorophyll, SPAD, and vitamin C decreased in all treatments, reflecting micronutrient depletion, salinity stress, and oxidative damage. The freshwater treatment also experienced reduced quality due to ammonium accumulation. Overall, combining SSF, biochar, and UV-C provides effective microbial inactivation and maintains physical water quality but progressively depletes essential micronutrients, limiting long-term crop performance. These findings highlight the potential of low-cost treatment systems for small-scale hydroponic growers while emphasizing the need for cycle-specific micronutrient supplementation to sustain yield and nutritional quality during extended nutrient-solution reuse.Item Open Access Fed Cattle Basis Risk under Grid Pricing(2025) Alderson, CaitlynHedging risk in fed cattle markets has become increasingly important as producers face elevated price volatility and market uncertainty. This challenge is particularly pronounced for producers marketing cattle using grid pricing systems, which reward or penalize producers based on carcass attributes such as yield grade, quality grade, and carcass weight. Grid pricing has expanded rapidly over the last decade to represent about 70% of fed cattle marketings. Despite its prominence, little is known about how basis risk changes when cattle are priced using grids instead of traditional live or dressed pricing. With more variable factors impacting realized net price, we expect basis risk increases when cattle are sold on a grid. While grid pricing offers opportunities to capture premiums for higher-quality cattle, it also exposes producers to downside risk due to discounts applied to cattle that do not meet desired specifications. Managing this dual exposure to both price and quality-related premium/discount risks requires quantifying the price risk managed through traditional live or dressed price hedging. It also involves understanding the risk that remains due to varying cattle quality and associated grid component value variation. Results will inform producers using grid pricing of unhedgeable risk using traditional price risk management tools of futures and Livestock Risk Protection. Depending on the magnitude of elevated price risk, additional price risk management instruments might be warranted to manage price risk more effectively. For example, developing a Choice-Select spread or other price risk management market may be valuable. The objectives of this thesis are to quantify how fed cattle hedging risk has changed and to identify the main determinants of hedging risk for grid-priced fed cattle. A key measure is basis risk, the difference between the realized and predicted basis under various fed cattle valuation systems, and the uncertainty of cattle quality. Unique to this study is the adjustment of the predicted basis based on how cattle are priced and the expected quality distributions of cattle of varying quality and premiums/discounts, providing an essential contribution to better understanding contemporary fed cattle basis risk. Hedging risk changes as uncertainty on cattle quality and premiums and discounts are introduced: 1. We start by quantifying traditional weekly basis risk for cash-negotiated cattle over 20 years (2005-2024). This provides a baseline to illustrate historical trends and the evolution of basis risk. 2. Next, risk is quantified on a weekly basis for constant cattle quality (used broadly here to include quality grades, yield grades, carcass weights, etc.), letting premiums and discounts vary over time. Constant carcass quality distributions are averages based on more than 10,000 pens of packing plant grid carcass data obtained from commercial feedyards. This step enables us to determine how introducing varying premiums and discounts affects traditional hedging risk. 3. The analysis then incorporates quality and premium variability over time assuming producers have perfect foresight of quality of each pen hedged. To accomplish this analysis, a random pen of cattle is selected each week from the commercial feedyard data noted above. In this way, quality variation is introduced, but since it is assumed that the producer perfectly anticipates the quality of each pen, there is no quality uncertainty. This segment enables incremental measurement relative to the previous scenario of how introducing quality variation impacts hedging risk and premium/discount variation over time. 4. Finally, imperfect quality guesses are introduced by adding random errors to predicted quality distributions based on the above-referenced feedyard data. This segment enables incremental variation from above scenarios adding quality uncertainty. My approach highlights increasing complexity and variability in basis risk as grid pricing systems dominate the market. Understanding this complexity is critical for producers because it directly impacts the effectiveness of traditional risk management tools. Producers, policymakers, and market participants must recognize these dynamics to develop innovative tools and strategies that better address the unique risks posed by grid pricing. Price risk management in fed cattle markets is of greater importance than ever, with high price levels and elevated price risk. However, traditional hedging instruments are designed for hedging commodity cattle sold using negotiated cash prices. However, with grid pricing, valuing cattle based on carcass merit has become the dominant fed cattle valuation method, and the basis risk for cattle hedging is poorly understood. Traditional hedging instruments enable only base price protection but do nothing to manage varying premiums and discounts on uncertain cattle carcass quality. This study will demonstrate how basis risk changes as cattle are grid-priced and quantify the amount of price risk unhedged for grid-valued cattle. The study will also explain how much of this variation is due to premium/discount variation and uncertainty about varying cattle quality. The findings will provide critical insights for evolving price risk management tools for cattle producers and inform policymakers in designing LRP risk management programs. Depending on the extent of unhedgeable risk identified, new price risk management tools or institutions may be needed to mitigate the increasing price risk associated with grid pricing.Item Embargo Modifying Functional and Nutritional Properties of Pulse Flours and Starches by Roller Milling and Thermal Processes(2025) Qi, JingFunctional and nutritional properties of pulse flours and starches were enhanced by controlled roller milling and thermal processes, with an emphasis on increasing resistant starch (RS) content and understanding factors that influence starch digestibility. In Chapter 1, a comprehensive review highlighted the nutritional significance of pulses, particularly dry peas, lentils, and chickpeas, which are rich in dietary fiber, slowly digestible starch (SDS), and RS. This chapter discussed how pulse-based ingredients, especially flours, can be strategically used in food applications to reduce glycemic response and enhance satiety. In Chapter 2, the molecular structure of pea starch was analyzed, and its amylose content was measured by four methods and compared with starches from maize, potato, and high amylose maize. Pea starch had ~38–40% amylose content as measured by iodine colorimetric, differential scanning calorimetry (DSC), and gel-permeation method (GPC) methods. The Concanavalin A method yielded a lower value (30.4%), suggesting the presence of clustered short branches in pea amylose. The findings highlight the importance of method selection in characterizing starch structure. Given their high amylose content, pea and high amylose maize starches were selected for the production of starch spherulites. In Chapter 3, DSC and a Parr reactor were used to investigate spherulite formation. Spherical crystalline aggregates, known as starch spherulites, were successfully formed from both starches through a controlled thermal process involving heating followed by controlled cooling. Under optimized conditions, both pea and high amylose maize starches formed B-type crystalline spherulites, highlighting the potential for scalable production and future applications in targeted nutrient delivery. In Chapter 4, dry roller milling was used to generate pulse flours from yellow peas, chickpeas, and lentils with varying cell wall integrity. Coarse-sized flours retained more intact cotyledon cell walls, leading to significantly reduced starch digestibility and higher RS levels, particularly after cooking. Chapter 5 focused on the thermal properties of dehulled pulse flours at different moisture levels using DSC. Distinct thermal behavior was observed among the flours and their components (isolated starch, protein fractions), providing fundamental knowledge for the hydration-dependent functional performance of pulse ingredients. In Chapter 6, a novel heat moisture treatment (HMT) protocol was developed and applied to pulse flours to enhance their structural and nutritional qualities. HMT led to increased RS and total dietary fiber content, altered thermal transitions, and reinforced starch crystallinity, demonstrating its potential to improve starch-protein interactions and enzymatic resistance. Chapter 7 summarized the overall conclusions and future research directions. Overall, this dissertation integrates molecular analysis, starch crystallization, flour processing, and thermal/digestibility profiling across seven chapters, advancing the understanding of how pulse starch and flour properties can be optimized for nutritional and functional applications.Item Open Access Community economic development in two rural Kansas communities: a thematic analysis(2025) Colle, KevinRural communities across Kansas face growing challenges of population decline, limited financial resources, and shifting economic structures. This study examines the factors that shape community economic development (CED) in two rural Kansas towns, Sterling and Nickerson, using the Community Capitals Framework (CCF) as an analytical lens. The CCF identifies seven interrelated forms of capital that collectively influence a community’s development trajectory. Through a qualitative comparative case study approach, nine semi-structured interviews were conducted with local leaders and stakeholders from both communities. Data were coded deductively using the seven capitals and analyzed inductively through thematic analysis. Findings reveal four interrelated themes shaping CED in these communities: (1) the power and limits of social capital, (2) political capital as a gatekeeper to development, (3) identity and attachment to place, and (4) built strengths and constraints. The study concludes that communities with well-coordinated political, social, built, and cultural capitals are more likely to “spiral up” toward sustainable growth, while those with fragmented or exclusionary networks risk “spiraling down.” By applying the CCF to rural Kansas, this study contributes to the understanding of how small towns mobilize their assets amid structural and demographic challenges. The findings offer insights for policymakers, local leaders, and development practitioners seeking to strengthen community resilience and guide equitable economic growth in rural America.Item Open Access Free choice feeding and its impact on feed efficiency and oxidative stress in growing sheep(2025) Frey, JonnThe traditional total mixed ration (TMR) is a staple in the animal feeding industry as it allows, on aggregate, for animals to perform at a high level of efficiency when feeding large numbers of animals together. However, free choice feeding could have performance benefits and help improve the well-being of animals compared to TMR feeding that is used today. With free choice feeding, animals can develop and exercise individual preference of feedstuffs which has been theorized as one potential reason for the improvement in efficiency with free choice feeding. We conducted a study using growing sheep to assess differences in performance and oxidative stress between the two feeding methods. For this study, Polypay lambs (n=23, BW = 29.7 ± 6.6 kg) were utilized with lambs being blocked by body weight and randomly assigned to either a TMR diet (CON) or a free choice diet (FCD). The diets for both TMR and the FCD were of the same primary ingredients, with the free choice group having the macro nutrients (energy and protein) being supplied by the two main components of the TMR, corn and alfalfa, offered separately in pelleted form. For determination of the oxidative health impact of the two feeding systems, blood was collected at the beginning and end of the experiment, and was analyzed for the oxidative stress metabolite malonaldehyde (MDA) and the overall antioxidant capacity (AO). The experiment lasted a total of 42 days. Lambs were fed daily with the refusals targeting 5% to allow for ad libitum consumption. Lambs were weighed weekly for the duration of the experiment and rate of gain was determined using linear regression, with the slope of the regression line being average daily gain (ADG). The heavy block of FCD had a greater (P <0.05) ADG compared to the heavy block of CON (0.23 kg/d vs 0.17 kg/d), but was similar to light blocks of the FCD and CON treatments. For DMI, TDN intake, and the variability of daily intake, there was no significant difference between treatments for any of these variables. For F:G, although no difference was observed between treatments, a significant treatment by block interaction was observed (P = 0.04). Intake of CP was a greater (P = 0.03) for CON than for FCD (0.31 kg/d vs. 0.26 kg/d). Sheep in the FCD group showed an initial preference for the alfalfa pellets, but they began to prefer corn relative to alfalfa as the experiment progressed. Measures of oxidative stress showed no differences between treatment groups at the start as well as the end of the experiment. The results of this study showed that, although some benefits to animal performance might occur with FCD, the positive impact on oxidative stress may not be true in all situations, in contrast with previously published literature.Item Embargo Development of a field water/cement ratio test using time domain reflectometry(2025) Yu, BinxiangA reliable and nondestructive method is needed to determine the water-to-cement or water-to-cementitious material ratio (w/cm) of fresh concrete for performance-based quality assurance. This study developed and validated a Time Domain Reflectometry (TDR) based method to quantify the real-time w/cm ratio of fresh concrete. Forty-eight concrete mixtures with varying w/cm ratios, air contents, and cementitious binder types (cement-only, fly ash, and slag) were tested, and TDR measurements were synchronized with conventional tests to establish a calibrated model between the apparent dielectric constant (K_a) and volumetric water content (θ_v). Data were analyzed using the statistical software R, employing group standardization, ordinary least-squares regression, and the Simulation–Extrapolation (SIMEX) method to correct for measurement-error bias. Four models developed for different cementitious binder systems showed strong consistency between measured and predicted results, confirming the reliability of the proposed calibration framework. However, as an empirical model, its applicability may be limited to the specific material range for which it was tested. Future studies should incorporate additional laboratory and field experiments, as well as explore physics-based dielectric modeling, to enhance prediction accuracy and generalization.Item Embargo Insights into the seasonal ecology and thermal biology of the lesser grain borer, Rhyzopertha dominica (Coleoptera: Bostrichidae)(2025) Christensen, DawsonOf the more than 20,000 edible plant species, maize, rice, and wheat provide half of the world’s diet. After harvest, these crops are stored for extended periods, but roughly 10 percent of global grain is lost to insect damage, costing the U.S. alone over 2.5 billion dollars annually. Among the estimated 1,500 insect species that can infest stored grain, the lesser grain borer, Rhyzopertha dominica, is a major pest capable of infesting intact kernels and causing damage directly or indirectly through contamination and promoting fungal growth. Its resilience to chemical controls and behavior of developing within grain kernels make traditional management challenging, prompting interest in alternative strategies such as cold-based interventions, including ambient and chilled aeration. Yet, the effectiveness of these methods depends on a variety of factors, including grain type, insect density, environmental conditions, and exposure duration. Here, our study addresses these knowledge gaps on how R. dominica responds to cold temperatures. A literature review first identified gaps in understanding how stored product insects tolerate cold conditions, with emphasis on R. dominica, and how this knowledge can reduce infestation risks under variable climates. Rhyzopertha dominica employs behavioral (e.g., burrowing, dispersal) and physiological (e.g., antifreeze proteins, cryoprotectants) strategies to survive harsh conditions. Commodity type and natural refugia further influence survival, and responses vary by insect species, sex, life stage, prior cold exposure, and population, highlighting the need for continued research on thermal biology to guide postharvest pest management. In line with understanding how cold treatments can be used to manage R. dominica, the first objective examined R. dominica habitats beyond stored grain, to see whether this species uses specific landscape features as alternative habitats. Field sampling in Manhattan, Kansas, indicated a strong association between beetle abundance and rodent dens. These data, combined with historical trap records, were used to develop predictive models of population trends across Kansas prairies. Incorporating climatic variables, forecasts suggest relatively stable populations through 2040, with slightly earlier seasonal emergence under warming scenarios, informing regionally adaptive monitoring and integrated pest management strategies. The second objective examined R. dominica movement under cold conditions, simulating navigation in grain bins or natural habitats. Beetles were tested across temperatures (10, 20, 30 C), acclimation (18 vs. 30 C), strains (lab colonies vs. recently collected, or wild), and sexes. Cold acclimation reduced movement at warmer temperatures but enhanced mobility in colder conditions. Females moved more than males, and lab strain beetles were more active than wild strain ones. These results indicate that acclimation, sex, and population origin strongly influence beetle movement and cold tolerance. The third objective examined how commodity type affects R. dominica survival and reproduction under warm and cold storage. Beetles were held in corn, sorghum, rice, or wheat at different temperatures (30, 18, or 5 C) for distinct exposure periods (2, 4, 8, or 12 weeks), then returned to 30 C for 6 weeks to simulate a recovery period from cold conditions. At 18 and 30 C, wheat, sorghum, and rice supported the highest adult counts, while corn was least favorable. At 5 C, counts across all grain types were relatively similar. Populations were highest at 30 C, intermediate at 18 C, and lowest at 5 °C. At 30 C, populations increased over time, stabilizing in sorghum, rice, and wheat, but continuing to rise in corn. Extended exposure at 18 C gradually reduced populations, while at 5 C, effects varied by commodity: corn and wheat remained stable at low levels, whereas rice and sorghum declined. These results indicate that even brief cold exposure (e.g., 4 weeks) can suppress reproduction, offering practical options for postharvest pest management. Overall, the work presented here emphasizes the complex interplay between thermal biology, behavioral ecology, commodity characteristics, and climate variability in shaping R. dominica population dynamics and responses to environmental stressors. Rhyzopertha dominica can withstand cold temperatures by seeking alternative habitats, acclimating gradually to cooler conditions, or persisting within the protective environment of grain. Integrating these factors into predictive models and pest management strategies will prove to be essential for optimizing cold-based interventions, enhancing sustainable grain storage, and mitigating economic losses under current and projected climate scenarios.Item Embargo Real-time monitoring of soil moisture and nutrients using an integrated dielectric sensor and an underground wireless network(2025) Han, MingqiangContinuous, accurate measurements of soil moisture and nutrients enable data-driven decisions that reduce water and fertilizer waste, improve yields, and minimize environmental impact. However, no practical sensor system currently provides these measurements simultaneously with the required accuracy. Dielectric spectra sensors offer a promising solution, but significant challenges, including system reliability, field validation, and identifying frequency responses specific to individual soil properties, remain. This dissertation addresses these challenges by developing and validating an integrated system for accurate measurement of volumetric water content (VWC), nitrate-nitrogen (NO3-N), and ammonium-nitrogen (NH4-N), with data transmitted through wireless underground networks, to advance sustainable agricultural management. A multi-layer soil propagation model was introduced to predict signal attenuation in complex soil profiles. Extensive field tests across different soil types were conducted to validate this model and demonstrate the feasibility of wireless underground communication using various transceivers. The proposed model significantly improved attenuation estimation, and field results confirmed reliable underground data transmission at depths of up to 50 cm. LoRa-based technology was selected as the preferred wireless communication method due to its robust performance across soil conditions. A dielectric sensor system capable of measuring both magnitude and phase responses from near DC to 1 GHz was designed and implemented. These measurements provide information on soil permittivity, which can be used to estimate key soil properties. The system integrates circuits for signal generation, conditioning, processing, data acquisition, storage, and wireless transmission, all controlled by an STM32F407 microcontroller with efficient power management. System performance was thoroughly tested and validated. An integrated software platform with a user-friendly graphical interface was developed for real-time data visualization and interpretation. Robust communication protocols were established for seamless connectivity among wireless sensor nodes and user devices. The interface supports data collection setup, real-time monitoring, sensor geolocation, and integration with weather data. Laboratory and field experiments were performed to evaluate sensor performance for soil property measurement. Multiple experimental datasets were analyzed to identify the most responsive frequencies for detections of VWC, NO3-N, and NH4-N using variable selection methods, including competitive adaptive reweighted sampling (CARS), minimum redundancy maximum relevance (MRMR), and successive projections algorithm (SPA), in conjunction with artificial neural network (ANN) models. The system achieved good predictive performance, with selected frequencies enabling the development of final models yielding test set R2 values of 0.80, 0.66, and 0.76 for VWC, NO3-N, and NH4-N, respectively. In summary, this dissertation introduces a comprehensive soil monitoring system that delivers accurate, real-time data to advance sustainable agricultural practices.Item Open Access What’s the buzz?: a dual-scale assessment of Kansas bumble bee species to inform future conservation efforts(2025) Holthaus, DanielleThe decline of bumble bee (genus Bombus) populations across North America, attributed to factors such as habitat loss/ fragmentation, increasing use of pesticides, and climate change, poses significant concerns for both natural ecosystems and agricultural productivity. Two bumble bee species found in the Great Plains are imperiled, which necessitates further research exploring where they are located, how their habitats differ from species that are stable, and what land management techniques can be implemented to benefit the bumble bee community as a whole. In this thesis, I used experimental and modeling methodologies to assess how Kansas bumble bee species are affected by environmental factors on two different scales. On a local scale (Chapter 1), I take an experimental approach by conducting a two-year field study to investigate the direct and indirect effects of bison (Bison bison) grazing and fire frequency (common grassland management strategies) on bumble bee abundance, community composition, and plant interactions. I found that the presence of bison indirectly increases total bumble bee abundance by means of increasing floral resource availability; there were interactive effects with fire frequency. Community composition did not differ significantly between grazing treatments; however, there were differences in host-plant interactions among bumble bee species. On a state-wide scale (Chapter 2), I use species distribution models to understand differences in habitat selection and spatial distributions between common and threatened species in Kansas. While most findings were species-specific and not characteristic of “common” or “threatened” groups as a whole, one species of least-concern deviated the most in terms of habitat associations. In general, all species were negatively associated with monoculture crop coverage. Climate factors appeared to be less important drivers of distribution than landscape factors. Model-predicted maps created from each species’ most significant set of predictor variables display hotspots where individuals are most likely to be detected across Kansas. Such maps are crucial for designating priority areas for threatened species protection. Overall, this research provides valuable insights into the ways in which grassland management, land cover, and climate factors affect bumble bee species for the purposes of assisting with targeted conservation efforts across Kansas and the entire Great Plains.Item Embargo Understanding Listeria biofilms: formation, ecology, and control in the produce industry(2025) Deniz, AysuListeria monocytogenes, a major foodborne pathogen, has been a growing concern in the fresh produce industry and is increasingly recognized as a vehicle for transmission of foodborne illnesses. Its persistence and contamination potential are strongly associated with its ability to form biofilms. Hard-to-clean sites in food processing environments can provide favorable conditions for biofilm establishment and survival. Exposure of these biofilms to sublethal concentrations of sanitizers can trigger stress response mechanisms, leading to alterations in gene expression that promote adaptive response. Beyond single-species systems, a further challenge is the frequent occurrence of L. monocytogenes in multispecies biofilms, particularly with Pseudomonas spp., a common spoilage microorganism. These mixed communities exhibit enhanced resistance and tolerance to sanitizing practices, creating greater challenges for effective control. Therefore, the main objectives of this study were to: 1) Assess the growth of L. monocytogenes biofilms on common food processing surfaces used in the fresh produce industry and evaluate the efficacy of commercially available sanitizers alone or simultaneously with UV-C light; 2) Characterize the transcriptional response of L. monocytogenes biofilms exposed to sublethal concentrations of commercial sanitizers and identify mechanisms involved in biofilm adaptation; and 3) Investigate the interactions between Pseudomonas fluorescens and L. monocytogenes in dual-species biofilms and evaluate the efficacy of commercially available sanitizers against these biofilms across different food-contact surfaces. Multi-strain L. monocytogenes biofilms were grown in a Centers for Disease Control and Prevention (CDC) biofilm reactor on stainless steel, nylon, polyvinyl chloride (PVC), high density polyethylene (HDPE), and Teflon for up to 96 h. Mature biofilms were exposed to 120 ppm peracetic acid (PAA), silver dihydrogen citrate (SDC; 4.85% citric acid and 0.003% silver ions), 4% lactic acid, and UV-C light (254 nm) for 1 or 5 min by spraying. Biofilm architecture was evaluated using Laser Scanning Confocal Microscopy (LSCM) before and after treatments. Uninoculated surface materials showed different topographical characteristics and when mature biofilms were treated for 1 min with different sanitizers, biomass was visibly affected. Antimicrobial treatment and the interaction of treatment and material showed significant effects (P < 0.05). All tested liquid sanitizers significantly reduced biofilm cell populations as compared to controls (P < 0.05), with PAA and lactic acid demonstrating the highest efficacy across surfaces. However, simultaneous application of UV-C light with sanitizers did not statistically improve treatment efficacy. Given the observed variation in sanitizer efficacy against L. monocytogenes biofilms populations observed, transcriptomic analysis was conducted to further explore the relationship between sanitizer-induced stress and gene expression. Biofilms were exposed to sublethal concentrations of PAA (10 ppm), chlorine (10 ppm), SDC (4.85% citric acid and 0.003% silver ions), and lactic acid (0.4%), with untreated biofilms serving as controls. L. monocytogenes biofilms responded differently to sublethal stresses of these sanitizers. Among them, chlorine and peracetic acid induced the most rapid and significant transcriptional changes. Comparative analysis of differentially expressed genes (DEGs) revealed both unique and shared transcriptional responses across treatments. Chlorine induced the highest number of unique upregulated genes, while chlorine and PAA shared a subset of commonly regulated genes. This suggested both distinct and overlapping stress response mechanisms depending on the sanitizer used. Chlorine exposure triggered regulatory and transport systems, while PAA induced ion transport and ABC transporters. These sanitizer-specific responses suggested distinct adaptive strategies that may contribute to persistence. Since complex interspecies interactions can enhance resistance and tolerance to sanitation efforts, this study also evaluated the efficacy of commercial sanitizers against dual-species biofilms of L. monocytogenes and P. fluorescens. Biofilm production capacities of these species were first assessed by crystal violet staining. Dual-species biofilms were then grown in a CDC biofilm reactor on stainless steel, PVC, Teflon, and HDPE surfaces at 22 2C for 96 h. Mature biofilms were treated by immersion with the previously tested sanitizers, along with chlorine (500 ppm) for 5 min. Surviving cells were recovered on selective and general media. In addition, growth dynamics of both species were monitored over time, and LSCM was used to visualize colonization patterns and spatial organization within the biofilms. Results revealed that both P. fluorescens and L. monocytogenes were found to be biofilm formers with different production capacities and P. fluorescens showed significantly higher biomass production than L. monocytogenes (P < 0.05). Material, treatment, and their interaction had significant effects on microbial recovery (P < 0.05). Among sanitizers tested, chlorine was the most effective showing enhanced effectiveness on stainless steel where the total counts were reduced from 8.43 ± 0.32 log CFU/coupon to 5.26 ± 0.09 log CFU/coupon. A similar trend was observed when L. monocytogenes and P. fluorescens populations were enumerated individually. PAA was also effective against dual-species biofilms. On HDPE, PAA treatment resulted in the combined counts of 6.27 ± 0.15 log CFU/coupon where untreated control was 8.63 ± 0.34 log CFU/coupon. Overall, this study demonstrates that L. monocytogenes biofilms exhibit sanitizer and surface dependent responses and provides insight into how interspecies interactions and sanitizer adaptations affect their persistence on food processing surfaces. These findings provide insightful information on the use of a combined sanitizing approaches and support the development of more effective strategies for controlling biofilms on food processing surfaces in the fresh produce industry.Item Embargo Machine learning integration of UAS-based thermal and multispectral imaging for precision irrigation in corn(2025) Abon, John Eric; Sharda, Ajay; Sharda, Vaishali; Aguilar, Jonathan; Ciampitti, IgnacioWater scarcity and climate variability are intensifying the challenge of sustaining corn (Zea mays L.) yield while minimizing irrigation inputs. The study employed Unmanned Aerial System (UAS)-based thermal and multispectral remote sensing with advanced machine and deep learning methods to create a comprehensive, field-scale framework for precision irrigation and crop productivity forecasting. UAS-based thermal imaging was deployed to quantify the spatial variability of crop water stress under three irrigation treatments—33% (P33), 67% (P67), and 100% (P100) of full crop water requirement across six reproductive stages (R1—R6). High resolution canopy temperature maps were converted to the Crop Water Stress Index (CWSI), a standardized indicator of water stress revealing severe stress in the P33 treatment (CWSI > 0.80, canopy temperature > 45°C), moderate stress in the P67 treatment (CWSI 0.40-0.75), and optimal conditions in the P100 treatment (CWSI < 0.40). Temporal analysis confirmed peak stress during early reproductive stages, and non-parametric statistics (Friedman χ² = 6.33, p = 0.042) verified significant treatment effects, indicating the value of UAS-derived thermal data for site-specific irrigation scheduling. Temporal-Spatial Fusion Network (TSFN) was developed to predict corn yield by integrating thermal and multispectral imagery collected by unmanned aerial systems (UAS) across six maize reproductive stages (R1 to R6) with deep learning modules: convolutional neural networks (CNNs) to learn intra-plot spatial features, Graph Neural Networks (GNNs) to model inter-plot spatial dependencies, and gated Recurrent Units (GRUs) with attention mechanisms to capture sequential temporal dynamics. High resolution imagery was acquired weekly and used to derive vegetation indices (NDVI, NDRE, GCI, MTCI, EVI) and crop water stress Index (CWSI), enabling spatially explicit tracking of crop health and water stress responses. TSFN combines the model significantly outperformed traditional machine learning methods and standalone deep learning models. It achieved an R² of 0.79 and RMSE of 13.10 bu/acre, surpassing CNN-GNN and ensemble baselines. Later reproductive stages (R4-R6) contributed most to predictive accuracy, while early-stage data (R1-R3) supported timely in-season diagnostics. The model performed best under moderate and deficit irrigation (P67 and P33) due to increased spectral variability caused by crop stress. Unmanned aerial system (UAS) multispectral imagery was combined with machine-learning and deep learning models to generate high-resolution evapotranspiration (ET) estimates. NDVI-derived crop coefficient (Kc) and on-site ET-gage reference evapotranspiration (ETo) informed model training. Random Forest delivered near perfect accuracy across irrigation levels (R² = 1.00 at R1 to R3, RMSE = 0.00 mm day -1) and only small reduction at R4 (R² = 0.97). ResNet18 consistently outperformed the CNN and achieved strong agreement with field measurements (R² ≈ 0.95–1.00, RMSE ≈ 0.00-0.17 mm day -1). Stage-wise evaluation revealed ResNet18 remained highly accurate during most reproductive phase, but showed moderate dip at R4 (R² = 0.95). Ablation analysis confirmed that late season imagery was essential for model performance. Removing R5, which contains the highest ETc values (≈ 6-8 mm day-1), produced largest decline in predictive accuracy, reducing R² to 0.93 and raising RMSE to 0.28 mm day-1), whereas omitting R4 had minimal impact and in some cases slightly improved accuracy. These studies effectively delivered information that integrating UAS thermal and multispectral sensing with advanced analytics enables zone-level mapping of crop water stress, accurate yield prediction, and operational ET estimation. The resulting framework provides actionable, data-driven irrigation strategies that reduce water use while sustaining corn productivity under variable irrigation regimes.
