ANALYSIS OF SWITCHGRASS CHARACTERISTICS USING NEAR INFRARED SPECTROSCOPY

Switchgrass varieties grown under various environments were investi-gated by dispersive and Fourier Transform Near-Infrared (NIR) spectro-meters. The collected NIR spectra were analyzed using multivariate approaches. More specifically, principal component analysis (PCA) and projection to latent structures (PLS) regression techniques were employed to classify and predict characteristics of the switchgrass samples. The multivariate results were compared to reflectance indices that are commonly used to study the physiological performance of plants. From near infrared spectra, discrimination between the two growth locations was successfully achieved by PCA. Separation based on the ecotype and the rate of fertilizer applied to the field was also possible by the multivariable analysis of the spectral data. For the classification/ discrimination of the switchgrass samples, the near infrared spectra collected by the dispersive and the Fourier Transform spectrometers provided similar results. From the two near infrared data sets robust models were developed to predict non-structural carbohydrates content and the rate of nitrogen applied to the field. However, the spectra collected by the dispersive spectrometer resulted in more accurate models for these samples

An Historical Analysis of the Fay B. Kaigler Children’s Book Festival

This study focuses on investigating the origins of the Fay B. Kaigler Children’s Book Festival, an internationally renowned annual conference hosted at The University of Southern Mississippi. This research is based on archival collections available at the McCain Archives and Special Collections

By the Pricking of My Thumbs, State Restriction This Way Comes: Immunizing Vaccination Laws from Constitutional Review

The article argues how states should not allow philosophical exemptions and should either retain or create religious exemptions that meet certain requirements under the Free Exercise Clause, the Due Process Clause, and the Establishment Clause. It reports the U.S. Supreme Court\u27s jurisprudence regarding parental rights in cases \u27Jacobson v. Massachusetts\u27 and \u27Zucht v. King.\u2

Characterizing Wood Components as Network Polymers by Dynamic Mechanical Analysis

The characterization of structure-property relationships in wood components, such as lignin, is a critical aspect of utilization. This point has been emphasized recently with concerns directed toward the application of natural products as wood bonding agents. Dynamic mechanical analysis is a valuable technique for the study of these relations because of its sensitivity to variations in polymer structure

The Properties of The Wood-Polystyrene Interphase Determined by Inverse Gas Chromatography

The properties of the interphase in wood-polymer composites are important determinants of the properties of the final composite. This study used inverse gas chromatography (IGC) to measure interphasal properties of composites of polystyrene and two types of wood fiber fillers and an inorganic substrate (CW) with varying amounts of surface coverage of polystyrene. Glass transition temperatures, thermodynamic parameters, and the London component of the surface free energy (YsL) were deter mined. Values for YsL became constant at higher coverages, allowing the thickness of the interphase to be estimated

Ecological analysis of marine microfossil communities: insight into the timing, magnitude, and drivers of change

The Plio-Pleistocene Caribbean basin underwent dynamic changes as the uplift of the Isthmus of Panama separated the Atlantic from the Pacific and global cooling manifested in strengthening glacial-interglacial oscillations. In this thesis I quantify community variability across known paleoenvironmental transitions to identify the dominant scales of ecological change, resolve the hierarchy of environmental controls on community assembly, and assess how tectonic and climatic thresholds shaped marine ecosystems during this critical interval in Earth's history. Utilizing a high-resolution (~3 ky) record of planktonic foraminifera abundances from 5.03-1.38 Ma, I identify compositionally and temporally distinct intervals of relatively persistent community configurations. I resolve the timing and magnitude of these distinct compositional shifts, demonstrating that faunal turnovers associated with the closure of the Central American Seaway (CAS) and the amplification of Northern Hemisphere Glaciation (NHG) occurred in rapid, discrete transitions lasting 100 ky to 330 ky. This tempo contrasts previous interpretations of gradual change derived from coarser-resolution records which I address through down-sampling experiments, demonstrating that coarse resolution sampling may obscure the true tempo of biotic change. Integrating faunal data with published geochemical proxies shows that community structure most strongly correlates with sea level and nutrient-related proxies. These results suggest that nutrient dynamics, mediated by changing ocean circulation and ventilation states, act as the primary driver of changes in Caribbean planktonic foraminifera community composition. Finally, I leverage the 171 glacial and interglacial oscillations archived in our record as natural experiments to assess the predictability of community assembly and the effects of climate cyclicity on community composition. While early Pliocene assemblages showed minimal differentiation between ice states, the onset of Northern Hemisphere Glaciation (~2.71 Ma) and the final closure of the Central American Seaway (~3 Ma) amplified glacial-interglacial contrasts, driving deterministic shifts in community composition. Pleistocene communities stabilized into predictable, low-diversity configurations, revealing a tradeoff between richness and stability.&nbsp

The Application of Near Infrared (Nir) Spectroscopy to Inorganic Preservative-Treated Wood

There is a growing need to find a rapid, inexpensive, and reliable method to distinguish between treated and untreated waste wood. This paper evaluates the ability of near infrared (NIR) spectroscopy with multivariate analysis (MVA) to distinguish preservative types and retentions. It is demonstrated that principal component analysis (PCA) can differentiate lumber treated with CCA, ACZA, or ACQ preservatives. Furthermore, separation according to wood species and assay zone was also observed. Within the range of preservative concentrations available, partial least squares (PLS) regression was also performed on the NIR data, from which retention levels were predicted. The results highlight the potential for this technique to predict the concentration, as well as identify the type, of inorganic preservatives present

U.S. Billion-ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry

The Report, Biomass as Feedstock for a Bioenergy and Bioproducts Industry: The Technical Feasibility of a Billion-Ton Annual Supply (generally referred to as the Billion-Ton Study or 2005 BTS), was an estimate of “potential” biomass within the contiguous United States based on numerous assumptions about current and future inventory and production capacity, availability, and technology. In the 2005 BTS, a strategic analysis was undertaken to determine if U.S. agriculture and forest resources have the capability to potentially produce at least one billion dry tons of biomass annually, in a sustainable manner—enough to displace approximately 30% of the country’s present petroleum consumption. To ensure reasonable confidence in the study results, an effort was made to use relatively conservative assumptions. However, for both agriculture and forestry, the resource potential was not restricted by price. That is, all identified biomass was potentially available, even though some potential feedstock would more than likely be too expensive to actually be economically available. In addition to updating the 2005 study, this report attempts to address a number of its shortcoming

Detecting Special-Cause Variation \u27Events\u27 From Process Data Signatures

The ability to detect the special-cause variation of incoming feedstocks from advanced sensor technology is invaluable to manufacturers. Many on-line sensors produce data signatures that require further off-line statistical processing for interpretation by operational personnel. However, early detection of changes in variation in incoming feedstocks may be imperative to promote early-stage preventive measures. A method is proposed in this applied study for developing control bands to quantify the variation of data signatures in the context of statistical process control (SPC). Control bands based on pointwise prediction intervals constructed from the Bonferroni Inequality and Bayesian smoothing splines are developed. Applications using the control band method for data signatures from near-infrared (NIR) spectroscopy scans of industrial fibers of Switchgrass (Panicum virgatum) used for biofuels production, Loblolly Pine (Pinus taeda) fibers for medium density fiberboard production, and formaldehyde (HCHO) emissions from particleboard were used. Simulations curves (k) of k = 100, k = 1000, and k = 10,000 indicate that the Bonferroni method for detecting special-cause variation is closely aligned with the Shewhart definition of control limits when the pdfs are Gaussian or lognormal