College of Agriculture & Natural Resources

Permanent URI for this communityhttp://hdl.handle.net/1903/1598

The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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    INVESTIGATING COMPOSTING AS A METHOD FOR REDUCING ESTROGENICTY IN POULTRY LITTER AND BIOSOLIDS
    (2015) Hammett, Kirsten; Yonkos, Lance; Environmental Science and Technology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Biosolids and poultry litter contain the natural estrogens 17β-estradiol and estrone, which can be transported to receiving waters via runoff when these materials are used as fertilizers. Estrogens are of concern because of their ability to act as endocrine disruptors and feminize fish. In this study, In-Vessel Aerated and Turned composting was investigated for its efficacy at mitigating estrogen concerns in BS and PL. Pre- and post- composted, BS and PL samples were investigated for total estrogenicity and estrogen species concentrations. In addition, conversion of estrone to 17β-estradiol was investigated by measuring the creation of deuterated 17β-estradiol from a deuterium-labeled estrone stock within aqueous PL mixtures. Data from these studies indicates that there may be efficacy in composting BS and PL prior to land application and suggest that estrone is capable of converting to the more potent 17β-estradiol species as a result of entering microbially active environments.
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    Hyperspectral Reflectance as an Indicator of Foliar Nutrient Levels in Hybrid Poplar Clone OP-367 Grown on Biosolid Amended Soil
    (2009) Griffeth, Tommy; Felton, Gary; Biological Resources Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Trees of the genus Populus are fast growing trees that require considerable amounts of water and nutrients to meet physiological growth demands. The determination of correlations between hybrid poplar leaf spectral reflectance in the 325-1100 nm range, laboratory foliar analysis of leaf macronutrient and micronutrient concentrations, and leaf water potential datasets were analyzed using Full Cross-Validation and Test Set Models via the partial least squares (PLS) method of regression analysis. Based on an evaluation of the slope of the Predicted vs. Measured regression line, the root mean squared error (RMSE), and r-squared, the majority of the models constructed did not adequately model foliar concentrations from spectral data. However, the models for H, N, P, K, Cu and Al had values (slope of the Predicted vs. Measured regression line greater than 0.50 and r-squared values greater than 0.50 in at least one type of model) that warrant future study.