Growing winter cereal cover crops (WCCCs) has been identified as an effective in-field practice to reduce nitrate-nitrogen (N) and total phosphorus (P) losses to Upper Mississippi River Basin, USA. In this region, however, growers are reluctant to plant WCCCs prior to corn (Zea mays L.) due to soil N immobilization and corn establishment issues. Two strategies to minimize these issues are (i) incorporating legumes and brassicas into WCCCs as mixtures and (ii) precision planting of cover crops. The objective of chapter 1 was to (i) evaluate the effect of cover crop mixtures vs a no-cover crop control on soil health indicators and (ii) assess the impact of precision planting of cover crops on soil nutrient availability, soil nutrient stratification, soil permanganate oxidizable carbon (POXC) and soil organic carbon (SOC) stocks “on” and “off” the corn row over three depths (0-5, 5-20, and 20-90 cm). Treatments were (i) a no-cover crop control (NCC); (ii) no cover on corn row, hairy vetch (V) on middle row, and winter cereal rye (WCR) on the outside row of corn (NOVR); and (iii) oats (Avena sativa) and radishes (Raphanus sativus) on the corn row, V on the middle row, and WCR on the outside row (ORVR). Our results indicated NCC had lower SOC stocks than the NOVR and ORVR only at 0-5 cm depth. Soil POXC was more sensitive to cover crop management than SOC, and POXC concentrations were higher in ORVR at 5-20 cm than the NCC control. At 0-5 cm depth, cover cropping increased Bray-1 soil test P (STP). Soil test P declined over depth reflecting its immobility in the soil. Mehlich-3 soil test K (STK) was higher in cover crop treatments than the no-cover crop control at 0-5 cm depth. Soil test K was higher on corn row indicating that the oats and radish mix and corn residue decomposition releases K detectable in soil as Mehlich-3 K. Soil test sulfur was similar among treatments but higher at 20-90 cm depth reflecting S leaching and/or potential anion exchange capacity at depth that can lead to subsoil sulfate-S accumulation. These results indicate cover cropping in the fragipan belt / Alfisols of the Upper Mississippi River Basin can benefit soil after six years, but soil C benefits are limited to surface soil depths.In Chapter 2 the objectives were to (i) evaluate the biomass, nutrient concentration, and uptake of precision planted cover crop mixtures; (ii) assess whether precision planted cover crops influence corn stand density, grain yield, yield components, and nutrient balances; identify the best economically viable precision planted mixture prior to corn. Treatments were (i) a no-cover crop control (NCC); (ii) no cover on corn row, hairy vetch (V) on middle row, and winter cereal rye (WCR) + annual rye (AR) on the outside row of corn (RVSKIP); and (iii) no cover on corn row, clover (C) on the middle row, and WCR + AR on the outside row (RCSKIP). Results indicated that RVSKIP was always high yielding, with high N uptake, and low C:N ratio (25) suggesting it could release N throughout the corn growing season without immobilizing N. Cover crops influenced corn population only in one site-yr but that did not result in lower corn grain yield reflecting corn potential for filling the plant gap by creating larger ears with heavier grain (TKW). Similar corn grain in all cover crop treatments was mainly due to adding optimum N as fertilizer. We concluded that overall, cover cropping could benefit soil over a six-year period but to optimize their benefit to corn, adjustments to N should be made. Therefore, future research should focus on revisiting corn N requirement especially in cover crop mixtures with high percentage (>50%) of legumes in the mixture to determine the fertilizer value of the cover crops.

Two studies were conducted from 2017 – 2019 at Stoneville, MS the first was to determine optimum seeding rates on single and twin row configuration during both late and early planting dates. The second study was to compare two row configurations with two planting populations (whole plot) but add management strategies (subplots) within each whole plot. From this data, yield optimization could be reached within each system that likely encompasses everything a producer in the Mississippi Delta could encounter during a growing season. Soybean seed from this data was analyzed for protein, oil, and fatty acid composition to determine which systems produce greater seed quality in terms of seed composition. Normal (non-symptomatic) and seed visually infected with purple seed stain (PSS) were compared to determine how infected soybean seed compared to normal soybean seed. Both seed (infected and non-symptomatic) were compared by measuring seed composition, germination, and vigor. During 2018 and 2019 at Verona, MS the same whole plot with subplot test was used but at this location under rained conditions. Soybean grown under rained conditions is a common practice in that particular region of the state (Northeast) so treatments were designed to be useful to producers in that area.

Narrow row corn production has gained interest in the Mid-South region over the last several years. This narrow row spacing interest has been inspired by increase of soybean grain yield from narrow rows. Therefore, production practices were evaluated for proper management of narrow row corn production. Additionally, the management of glyphosate- and potentially auxin-resistant weeds place pressure on other POST chemistries. Therefore, optimizing glufosinate applications are essential for control of Palmer amaranth. The objectives of this research were four-fold: 1) evaluate the phenotypic and grain yield responses of narrow row corn production under irrigated conditions, 2) test corn hybrids for their response to increased plant population in a narrow row configuration in rainfed environments, 3) assess sidedress nitrogen fertilizer practices in narrow row corn production systems, and 4) further investigate glufosinate management for POST control of Palmer amaranth. The results of this research suggest few phenotypic changes by utilizing narrow rows in corn, but most importantly, a 0.7 Mg ha-1 increase in grain yield across all plant populations. Agronomic optimum plant populations for both irrigated and non-irrigated environments ranged from 101-120 thousand plants ha-1 with hybrids varying in their response to increased plant population. Additionally, sidedress nitrogen application methods of knife-in UAN vs. broadcasting treated urea responded similarly with respect to grain yield. Agronomic and economic optimum nitrogen rate would vary significantly by site. Regarding glufosinate management, smaller droplet sizes provided the greatest control of Palmer amaranth. In conclusion, these data suggest that narrow row corn production is a viable strategy to increase corn grain yield and seeding rates should be adjusted dependent on the corn hybrid of choice. Also, controlling Palmer amaranth in Dundee, MS with glufosinate was best utilizing smaller droplet sizes.

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Design optimality plays a central role in the area of statistical experimental design. In general, problems in design optimality are composed of two vital, but separable, components. One of these is determining conditions under which a design is optimal (such as criterion bounds, values of design parameters, or special structure in the information matrix). The other is construction of designs satisfying those conditions. Most papers deal with either optimality conditions, or design construction in accordance with desired combinatorial properties, but not both. This dissertation determines optimal designs for three treatments in the one-way and multi-way heterogeneity settings, first proving optimality through a series of bounding arguments, then applying combinatorial techniques for their construction. Among the results established are optimality with respect to the well known E and A criteria. A- and E-optimal block designs and row-column designs with three treatments are found, for any parameter set. E-optimal hyperrectangles with three treatments are also found, for any parameter set. Systems of distinct representatives theory is used for the construction of optimal designs. Efficiencies relative to optimal criterion values are used to determine robustness of block designs against loss of a small number of blocks. Nonisomorphic bal anced incomplete block designs are ranked based on their robustness. A complete list of most robust BIBDs for v ≤ 10, r ≤ 15 is compiled. / Ph. D.

The western honey bee, Apis mellifera, provide invaluable economic and ecological services while simultaneously facing stressors that may compromise their health. For example, agricultural landscapes, such as a row crop system, are necessary for our food production, but they may cause poor nutrition in bees from a lack of available nectar and pollen. Row crops are largely wind or self-pollinated, and while previous studies have focused on the impact of bees to row crops, fewer studies have examined the reciprocal relationship of the row crops on honey bees. Here we investigated the foraging dynamics of honey bees in a row crop environment. We decoded, mapped, and analyzed 3460 waggle dances, which communicate the location of where bees collected food, for two full foraging seasons (April – October, 2018-2019), and concurrently collected pollen from returning foragers. We found that bees foraged mostly locally (< 2 km) throughout the season. The shortest communicated median distances (0.48 and 0.32 km), indicating abundant food availability, occurred in July in both years, which was when our row crops were in full bloom. We determined, by plotting and analyzing the communicated locations, that most mid-summer foraging was in row crops, with at least 40% of honey bee recruitment dances indicating either cotton or soybean fields. Bees also largely foraged for nectar when visiting row crop fields, only returning to the hive with Glycine spp. pollen, and foraging on nearby trees and weeds for pollen. Foragers were exposed to thirty-five different pesticides throughout the foraging season, based on pesticide residues in collected pollen. Overall, row crop fields are contributing a surprising majority of mid-summer forage to honey bee hives and suggests that similar agricultural landscapes may also provide abundant, mid-summer forage opportunities for honey bees, however, at the risk of pesticide exposure. / Master of Science in Life Sciences / Declines in the number of honey bee hives have been observed in the United States and western Europe throughout the last century, driven by environmental stressors such as poor nutrition caused by anthropogenic landscape change and pesticide exposure. Agricultural landscapes, for example, contain monocultures and often necessitate pesticide use, which may be detrimental to bee health. Because of these effects, it is necessary to understand how honey bees forage in these systems and what potential health risks they face. We investigated honey bees foraging dynamics in a row crop environment, observing honey bee waggle dance recruitment behavior and gathering forager-collected pollen to better understand when, where, and what honey bees forage on throughout the season (April – October). We found that bees largely foraged near the hive throughout the season, indicating that sufficient resources were available, particularly in July when crops were in full bloom. During full bloom bees considerably foraged in cotton and soybean fields. We found that bees collected minimal row crop pollen, apart from soybean pollen, largely foraging on trees and flowering weeds for pollen. Through pollen foraging bees were exposed to thirty-five pesticides, ranging in toxicity and mode of action. Overall, honey bees foraging in a row crop system foraged substantially in row crop fields during the mid-summer. Row crops systems may be able to provide abundant forage during the mid-summer, but could come at the risk of exposure to pesticides.

A place is said to be meaningful when man feels "at home." Looking at industrial cities, one finds an immense density to them. This results from the communities surrounding the industry. These communities developed from the housing supplied by the factories for the workers, primarily immigrants. They generally formed communities based on their ethnic origins and/or religious beliefs. The craftsmanship, quality and conditions were not the best. Within this context some of the strongest communities developed. Industry supplied these families with minimal housing. These families created something greater - a place to live - a shelter they could return to and a community to grow. The workers and their families succeeded in making a place of their own. / Master of Architecture

Numerous scientific applications have seen the rise of massive inverse problems, where there are too much data to implement an all-at-once strategy to compute a solution. Additionally, tools for regularizing ill-posed inverse problems are infeasible when the problem is too large. This thesis focuses on the development of row-action methods, which can be used to iteratively solve inverse problems when it is not possible to access the entire data-set or forward model simultaneously. We investigate these techniques for linear inverse problems and for separable, nonlinear inverse problems where the objective function is nonlinear in one set of parameters and linear in another set of parameters. For the linear problem, we perform a convergence analysis of these methods, which shows favorable asymptotic and initial convergence properties, as well as a trade-off between convergence rate and precision of iterates that is based on the step-size. These row-action methods can be interpreted as stochastic Newton and stochastic quasi-Newton approaches on a reformulation of the least squares problem, and they can be analyzed as limited memory variants of the recursive least squares algorithm. For ill-posed problems, we introduce sampled regularization parameter selection techniques, which include sampled variants of the discrepancy principle, the unbiased predictive risk estimator, and the generalized cross-validation. We demonstrate the effectiveness of these methods using examples from super-resolution imaging, tomography reconstruction, and image classification. / Doctor of Philosophy / Numerous scientific problems have seen the rise of massive data sets. An example of this is super-resolution, where many low-resolution images are used to construct a high-resolution image, or 3-D medical imaging where a 3-D image of an object of interest with hundreds of millions voxels is reconstructed from x-rays moving through that object. This work focuses on row-action methods that numerically solve these problems by repeatedly using smaller samples of the data to avoid the computational burden of using the entire data set at once. When data sets contain measurement errors, this can cause the solution to get contaminated with noise. While there are methods to handle this issue, when the data set becomes massive, these methods are no longer feasible. This dissertation develops techniques to avoid getting the solution contaminated with noise, even when the data set is immense. The methods developed in this work are applied to numerous scientific applications including super-resolution imaging, tomography, and image classification.

My interest in the study and practice of architecture is as a creative tool or solution to many of the challenges in our daily lives and communities.To not just create beautiful space that brings joy to be and exist in, but also space that, through design, addresses problems and helps make life easier and more livable. When exploring an idea for a thesis, I wanted to find design solutions for many of the problems associated with housing and the changing space needs or requirements throughout one's family life-cycle. For over a century the single family home with the nuclear family has been the quintessential American cultural housing ideal. (Think of all the suburban developments and houses with perfectly manicured lawns and identical rows of winding streets stretching for miles and miles out into the countryside). However, in my opinion, this form of housing is quite wasteful in terms of space, material, family, and community resources. It segregates and separates us from our extended family reserves, costing us money, time and most importantly the daily support we might otherwise have from those closest to us: family. I recognize that I am proposing rethinking longstanding cultural understandings about our most basic everyday functions: where and how we live. Part of my architectural exploration includes a question that I know I can never fully answer in these pages: can design lead culture? More specifically, can I or "we" as architects create a desire for something new in our culture through design? Not a new toy or gadget, but a new way of thinking about our future and how we want to live? / Master of Architecture

The plan and design of a large housing development project by itself was a difficult task in the past, the energy issue made the options very limited, and the planner and/or engineer deal with the solution more often technically intended with or without considering the energy problem. This study is centered on the energy issue as part of the design decision making process. This study tries to integrate the energy use effects as part of the basic planning process, such as land use and building style dependent on the land contour as well as solar exposure; and the passive solar energy utilization as part of the design process where the solar use is not an add on solar system but an integrated part of the basic design scheme. A development summary of the analysis and process guideline is introduced for medium-low density housing project in an urban setting with an actual site as a case study to illustrate the process. / Master of Architecture