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dc.contributor.advisorJessup, Russell W
dc.creatorShen, Xiaoqing
dc.date.accessioned2019-11-25T21:47:31Z
dc.date.available2021-08-01T07:35:45Z
dc.date.created2019-08
dc.date.issued2019-07-19
dc.date.submittedAugust 2019
dc.identifier.urihttps://hdl.handle.net/1969.1/186508
dc.description.abstractThe application of biochar soil amendments has been proposed as a strategy of mitigating global carbon emissions and soil organic carbon loss. Biochar can provide additional agronomic benefits to cropping systems, including improved crop yield, soil water holding capacity, seed germination, cation exchange capacity (CEC), and soil pH. Commercial development of biochar amendments has been limited; however, their significant potential impacts emphasize the need for further research. In order to maximize beneficial effects of biochar amendments towards the inventory, increase, and management of soil organic carbon (SOC) pools, non-destructive methods to identify and quantify belowground carbon are necessary. Ground penetrating radar (GPR) is potentially one such tool. GPR has been well characterized across geology, archeology, engineering, and military applications. While it has been predominantly utilized to detect relatively large objects such as rocks, tree roots, groundwater, ice, and peat soils, the purpose of this study is to quantify comparatively smaller, particulate sources of soil organic carbon. This research uses three different materials as different carbon source, biochar, graphite, and activated carbon. Mixing with sand, there are twelve treatments in total. GPR attribute analyses, including Pearson correlation, Spearman rank correlation, and naïve Bayes predictive models, were utilized in lieu of visualization methods due to the minute sized carbon particles of interest. Significant correlation coefficients between attributes and carbon content were found, and the correlation between attributes and moisture level was also significant. The predictive model was able to identify differences in both carbon content and carbon structure.en
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectBiocharen
dc.subjectGPRen
dc.subjectAttribute analysisen
dc.subjectMachine Learningen
dc.titleQUANTIFICATION OF ORGANIC CARBON IN BIOCHAR AMENDED SOIL USING GROUND PENETRATING RADAR (GPR)en
dc.typeThesisen
thesis.degree.departmentSoil and Crop Sciencesen
thesis.degree.disciplinePlant Breedingen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelMastersen
dc.contributor.committeeMemberHays, Dirk B
dc.contributor.committeeMemberTabien, Rotante
dc.contributor.committeeMemberBurson, Byron L
dc.type.materialtexten
dc.date.updated2019-11-25T21:47:31Z
local.embargo.terms2021-08-01
local.etdauthor.orcid0000-0002-7610-5496


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