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dc.contributor.advisorMorgan, Cristine L. S.
dc.creatorBalke, Sarah Nicole
dc.date.accessioned2020-12-15T19:46:25Z
dc.date.available2020-12-15T19:46:25Z
dc.date.created2020-05
dc.date.issued2020-01-08
dc.date.submittedMay 2020
dc.identifier.urihttps://hdl.handle.net/1969.1/191539
dc.description.abstractQuantitative soil structure metrics would be beneficial not only for assessing soil health, but also optimizing biophysical models. A rapid and reliable field method of soil structure measurement that can obtain quantitative metrics, is needed so that the effects of land management on soil structure can be measured in situ. Successful methods and analyses quantifying soil structure of intact soil profiles transported to the lab have been established. The research objective of this thesis is to develop a method for quick and accurate field quantification of soil structure using 3D scanning technology. Once the field methodologies were established, scans of soil surface horizons were collected from three areas across the Blackland Prairie Major Land Resource Area of Texas, USA. In each of these three areas, scans were collected in triplicate from fields under three land management categories: conventional till, no till, and perennial. Measurements of bulk density and other physical properties of the scanned soil were made also. Two scanner resolutions for field data collection were evaluated; Wide (0.4 mm) and Macro (0.1 mm). Wide scan collection and processing was quicker by approximately 70 minutes and produced similar results to Macro. Tessellation analysis of the soil face topography data from the scans yielded useful quantitative soil structure data that were assessed in linking changes in soil condition to changes in management practices. Average tessellation polygon areas showed statistical structural differences between soil horizons (p = 0.002) and a statistical difference between managements in one of the studied areas (p = 0.03). Other measured soil properties did not show strong correlations with tessellation results or significant differences by management. The tessellation analysis was proven to be a successful analytic data method but needs further refinement for more widespread use in agricultural applications.en
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectSoil Structureen
dc.subjectSoil Healthen
dc.subjectMLT scanningen
dc.subject3D scanneren
dc.subjectQuantitativeen
dc.titleEstablishing Quantitative Metrics for Soil Health: An In-Situ Method for Quantifying Soil Structureen
dc.typeThesisen
thesis.degree.departmentSoil and Crop Sciencesen
thesis.degree.disciplineSoil Scienceen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelMastersen
dc.contributor.committeeMemberGentry, Terry J.
dc.contributor.committeeMemberMoore, Georgianne W.
dc.contributor.committeeMemberMcBratney, Alex B.
dc.type.materialtexten
dc.date.updated2020-12-15T19:46:26Z
local.etdauthor.orcid0000-0002-1573-677X


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