Avocado is an economically important crop with ~70% oil in its fruit tissue, which is an essential component of human diet. The steady increase in global demand for avocado production (9%/year) has drawn attention to the importance of understanding the genetic regulation of triacylglycerol (TAG) accumulation. Using RNA-seq approach, mesocarp-specific regulation and biosynthesis of TAG in developing avocado fruit was analyzed. During the period of TAG accumulation in the mesocarp, an increased expression was noted for genes mostly associated with hexose metabolism in plastids, including pyruvate kinase, relative to cytosol, which is likely associated with the need for higher pyruvate flux directed toward plastid fatty acid synthesis. A corresponding increase in expression for plastidial fatty acid synthesis genes was also noted but not for TAG assembly genes. Additionally, WRINKLED1 (WRI1), a regulatory element typically associated with seed oil biosynthesis, was also highly expressed in oil-rich mesocarp of avocado, along with two other isoforms of WRI. Transcriptomics also revealed that multiple acyltransferases that participate in rate-limiting step in TAG synthesis might be active concomitantly in mesocarp to achieve higher levels of TAG accumulation. Similar observations were previously made with transcriptome analysis of oil-rich seed and non-seed tissues. Together these data suggest a ubiquitous role for WRI1 and that a major point of regulation of oil biosynthesis in oilrich mesocarp tissue most likely occurs at the level of source and not sink. Overall, this study provides a foundation for functional genomics required to direct metabolic engineering efforts to enhance avocado oil yield.

In this thesis we survey several interpolation methods that are used to construct the yield curves. We also review the bootstrapping and show that the bootstrap is closely connected to the interpolation in the case of bootstrapping yield curve. The most effort is dedicated, in this thesis, on the monotone convex method and on investigation of the difficulties to get accurate yield curves.

Switchgrass (Panicum virgatum L.) is a promising bioenergy crop for biofuel production. However, the effects of biosolids application on biomass yield, nitrogen (N) concentration, feedstock quality and theoretical ethanol yield (TEY) are rarely reported in the literature. The objectives of this research were: 1) to compare the effects of biosolids application on biomass yield, N concentration, feedstock quality and TEY, and 2) to compare the effects of harvest frequency on biomass yield, N concentration, feedstock quality and TEY. This experiment began in 2010 and tested four plant available N (PAN) rates of biosolids (0, 153, 306, 459 kg ha-1), one urea rate (180 kg ha-1), and two harvest frequencies (cut once in November or cut in July and November) on a Davidson soil at Orange, VA. Biosolids and urea applications increased biomass yield and TEY across years relative to control, but had no effects on measures of feedstock quality. Inconsistent biomass yield responses to harvest frequency were observed during three years. Cutting once per year consistently increased biomass lignin, cellulose, and hemicellulose concentrations, theoretical ethanol potential (TEP), and reduced N and ash concentrations compared to two cuts. Across years one cut increased TEY by 11% over the two cuts. The results demonstrate that biosolids can be applied as an N source to increase biomass yield and TEY. Two cuts increased biomass yield but reduced TEP, and had inconsistent effects on TEY. / Master of Science

New materials, optimized for increased strength, ductility, and other desirable properties, have the potential to improve every aspect of modern living. To achieve these optimums, the necessary technological advancements are impeded mainly by the limits of available material models. Innovations in this field rely on research into the nature of material behavior. While a typical model of material behavior in the region near yield involves the initial linear elastic response, followed by yield and isotropic hardening, this fails to explain various important phenomena that manifest in a range of materials, such as pre-yield nonlinearity, anelasticity, yield point phenomena, hardening stagnation, and the Bauschinger effect. These effects have been explained over the past century with the theories of Cottrell atmospheres, the Orowan by-pass mechanism, and back stress. This manuscript compares data from experimental observation in tantalum to these theories to better understand the micromechanisms occurring near yield. Understanding deformation in this region has significant implications in structural and mechanical engineering, as well has having direct applications in the forming of metals. Forty-four dogbone-shaped samples were cut from 99.99% pure tantalum and pulled in load-unload-load and multi-cycle loop tensile tests at room temperature. The specimens were either single crystal, whose orientations were chosen based on desired active slip mode determined by Schmid factors, or bicrystal, based on the orientation of the single grain boundary. Sample behavior was simulated in both crystal plasticity and General Mesoscale finite element models to assist in interpreting results and in suggesting plausible micromechanisms. The experimental results and crystal plasticity simulations suggest alternate explanations to some of the discussed mechanical theories of near-yield deformation. The combined experimental / modeling approach indicates that other slip systems, besides the conventionally assumed {110}, are activated upon yield; particularly the {112} system. The breakaway model traditionally associated with the yield point phenomenon may also be better explained through a different mechanism; back stress development during deformation is shown to result in the observed behavior. Lastly, as is well-known, the Taylor formulation, upon which most crystal plasticity models are based, does not adequately predict yield stress behavior in the presence of grain boundaries; once again, an internal stress mechanism matches much better with the experimental results on single and bicrystals. While not all observations could be fully explained by simply adding internal stress generation to a standard crystal plasticity model, this work anticipates further studies to enable more accurate predictive modeling capabilities and increase understanding of the mechanisms driving the fundamental material properties necessary for future progress.

Accurately modeling key aspects of coal combustion allows for the virtual testing and application of new technologies and processes without the need for investments in lab- and pilot-scale facilities, since such facilities may only be used for a few small tests. However, modeling of subprocesses must not only be accurate but computationally efficient. Modeling of coal devolatilization reactions and processes are one of the important parts of large-scale simulations of coal combustion systems. The work presented here details efforts to improve the modeling of coal devolatilization processes in massively-parallel simulations of coal combustors, including: (1) devolatilization rate/yield models, (2) modeling various chemical, physical, and thermodynamic properties of coal, char, and tar (including structural NMR parameters like carbon aromaticity, the elemental composition of coal char and tar, and the heating value of coal-based and other fuels), and (3) the application of various simplifying assumptions to equilibrium calculations of coal devolatilization products using multiple levels of fuel mixture fractions. Using several different advanced statistical methods, the models discussed here were developed and improved by careful comparison with large sets of experimental data. The advanced statistical methods and procedures show large improvements in these models over previous work.

Purpose The high yield debt market has evolved into a $1 trillion market over the last 25 years. The purpose of this paper is to analyze the riskadjusted performance of individual mutual funds that investors use to invest in this asset class. Design/methodology/approach Conditional excess returns are calculated for individual high yield bond mutual funds. Performance persistence over time is measured and size, asset growth, asset duration, the expense ratio, turnover, and manager tenure are used to determine if differences across funds can be explained. Findings Overall, high yield bond funds significantly underperform the CSFB high yield index by 1.6 percent on an annualized basis which is 0.5 percent more than the average expense ratio. Individually, funds do exhibit performance persistence and top ranked funds in one period outperform bottom ranked funds over the proceeding period by an average of 2.7 percent annually. However, except for the expense ratio, commonly used explanatory variables do not appear useful for explaining riskadjusted excess return differences across funds leaving 86 percent of the variation unexplained. Research limitations/implications This paper examines only noload mutual funds that have at least ten years of return data. Historical data for the explanatory variables used to explain alpha differences are limited which constrains any longterm definitive conclusions. Practical implications For investors wishing to invest in this asset class, it appears that past performance does indicate future success, and investors should concentrate on the top performing funds with the lowest expense ratios. Originality/value This paper usefully reaffirms previous evidence on the persistence of high yield bond mutual funds, but casts doubt on the viability of using standard variables other than the expense ratio to explain riskadjusted returns across funds.

By 2050, food consumption and agricultural water use will increase as a result of a global population that is projected to reach 9 billion people. To address this food and water security challenge, there has been increased attention towards the concept of sustainable agriculture, which has a broad aim of securing food and water resources while preserving the environment for future generations. An element of this is the use of precision agriculture, which is designed to provide the right inputs, at the right time and in the right place. In order to optimize nutrient application, water intakes, and the profitability of agricultural areas, it is necessary to improve our understating and predictability of agricultural systems at high spatio-temporal scales. The underlying goal of the research presented herein is to advance the monitoring of croplands and crop yield through high-resolution satellite data. In addressing this, we explore the utility of daily CubeSat imagery to produce the highest spatial resolution (3 m) estimates of leaf area index and crop water use ever retrieved from space, providing an enhanced capacity to provide new insights into precision agriculture. The novel insights on crop health and conditions derived from CubeSat data are combined with the predictive ability of crop models, with the aim of improving crop yield predictions. To explore the latter, a sensitivity analysis-linked Bayesian inference framework was developed, offering a tool for calibrating crop models while simultaneously quantifying the uncertainty in input parameters. The effect of integrating higher spatio-temporal resolution data in crop models was tested by developing an approach that assimilates CubeSat imagery into a crop model for early season yield prediction at the within-field scale. In addition to satellite data, the utility of even higher spatial resolution products from unmanned aerial vehicles was also examined in the last section of the thesis, where future research avenues are outlined. Here, an assessment of crop height is presented, which is linked to field biomass through the use of structure from motion techniques. These results offer further insights into small-scale field variabilities from an on-demand basis, and represent the cutting-edge of precision agricultural advances.

Silicon nanocrystals (SiNCs) are nanometer-sized semiconducting materials. Their small size endows them with unique photophysical properties. Efficient photoluminescence (PL) from silicon nanocrystal (SiNC) composites has important implications for emerging solar-energy collection technologies, yet a detailed understanding of PL relaxation in non-colloidal SiNCs is still materializing. In this dissertation, we examine the photophysical properties of silicon nanocrystal/off-stoichiometry thiol-ene composites (SiNCs/OSTE hybrids). The dissertation begins with an introduction to the photophysical properties of SiNCs, their photophysical properties, how SiNC/polymer composites are made, the various SiNC preparation techniques, and the most likely application areas for these nanocrystals. A description of experimental methods such as PL spectroscopy and transmission electron microscopy (TEM) follows, and SiNC/OSTE polymer preparation methods are then explained in detail. In the first study, TEM and photophysical characterization were performed on selected polydisperse SiNCs samples. These samples were synthesized in a nonthermal plasma reactor, using Si6H12 as precursor, and functionalized with R (where R is 1-dodecene). These SiNCs were dispersed in mesitylene:1-dodecene (5:1) as a colloid. Optical absorption, quantum efficiency, and PL lifetime of SiNCs were then investigated, as well as the relationship between quantum yield, lifetime, and PL peak. In the second study, we selected samples for size separation via the density gradient ultracentrifugation method (DGU). We successfully applied this technique to separate silicon nanocrystals with sizes from 2 nm to 4 nm from the ensemble samples using an engineered density medium layer stack, and photophysical characterization was performed on the DGU size–separated SiNCs. Lastly, we explored details of PL relaxation in photo-polymerized off-stoichiometric polymer/nanocrystal hybrids. We found time- and air-stable emission from dilute composites with up to 70% QY, and we investigated PL relaxation in the parameter space of nanocrystal size and temperature. In light of previous work, our results reveal similarities between the impacts of crosslinking and cooling to cryogenic temperature, but of which are characterized by a relative reduction in the available of phonons.

Demands for sustainable crop production are increasing to cope with threats of climate change and diversity loss. Tillage is one of the main farming practices that could impact crop production, soil, and air quality. We utilized a long-term (>48-yr old) tillage trial to evaluate four tillage systems including: (i) moldboard plow (MP), (ii) chisel-disk (grower’s current practice) (CD), (iii) alternate tillage [2-yr no-till (NT) and 1-yr MP; AT], and (iv) NT on corn (Zea mays L.) and soybean (Glycine max L.) grain production, nutrient removal and balances, soil physical, chemical, and biological properties, and nitrous oxide (N2O) emissions. We found that a switch from intensive tillage practices (CD and MP) to NT resulted in (i) similar corn and soybean grain yield, nutrient removal, and balances; (ii) increased soil aggregation and aggregate stability; (iii) increased soil organic carbon (C), active C, and aggregate associated C and nitrogen at 0-15 cm soil depth (iv) had consistence penetration resistance at the plow depth (30 cm depth), lower bulk density, higher soil porosity and available water capacity; (v) had lower soil NO3-N and TN, two-yr cumulative N2O-N emissions, and yield-scaled N2O-N (vi) greater soil ecosystem stability based on nematode community populations; (vii) increased earthworm abundance and biomass, diversity and species evenness, and percentage of epigeic ecotypes. Interestingly, NT did not influence soil C beyond topsoil indicating a limitation for NT to sequester C at deeper soil layers. These findings indicate improved soil in NT vs. other tillage practices provides C sequestration and reduced environmental footprints, without impacting grain yield while improving functional soil biology. Because the cost of NT operations are lower than other tillage practices, we concluded continuous NT could be a step towards sustainable crop production. To further improve the sustainability of crop production, other practices (e.g. cover cropping, crop diversification, soil amendments etc.) should be integrated into continuous NT practices.

Fusarium graminearum (Schwabe), causal organism of fusarium head blight (FHB), has become a major pathogen of wheat (Triticum aestivum L.) throughout North America. Since its discovery in the United States, the disease has spread south and east until at present it is an annual threat for growers of winter wheat in the Mid-Atlantic region. Yield losses for soft red winter (SRW) wheat averaged 908 kg ha-1 in the FHB outbreak of 1998 (Griffey et al., 1999). The economic loss from this single FHB epidemic was an estimated 8.5 million dollars. Environmental conditions favorable for FHB development, including above average rainfall and temperatures during anthesis, have become more common in the Upper-Midwestern wheat-growing region over the past decade, leading to substantial losses in wheat and barley crops. This, coupled with low prices being paid for wheat, has prompted research toward solving the problem of FHB across the nation. The majority of labor and financial resources devoted to FHB research are dedicated to incorporating FHB resistance into adapted wheat lines. While this is a prudent method of combating this disease, this process will take many years to complete. We have examined all FHB assessment parameters, which include FHB incidence, FHB severity, FHB index, percentage fusarium damaged kernels (percentage FDK), and 15-acetyl deoxynivalenol toxin (DON toxin) accumulation, to ascertain which assessment parameters best quantify FHB resistance levels in addition to grain yield and grain volume weight (GVW) losses. FHB index provides the most reliable in-field assessment of a genotype's resistance level, whereas percentage FDK provides a reliable measure of a genotype's resistance level post-harvest. FHB index and percentage FDK are also the most predictive assessment parameters with regard to grain yield and GVW loss. A wide range in both level and type of resistance was observed among genotypes examined in this study. The cultivars Agripro Patton, Ernie, INW9824, Roane, and the experimental line NY87048W-7388 consistently had lower scores for FHB assessment parameters and lower losses of grain yield and GVW. / Master of Science