{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/124415"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/124415","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"The use of high-resolution imaging tools for estimation of hydraulic soil properties and quantification of particulate organic matter","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms","abstract_has_math":false,"creators":["Pope, Daniela Diaz"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Natural Res & Env Sciences","degree_department":null,"school":null,"contributors":["Wander, Michelle","Ugarte, Carmen","Grift, Tony"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-05","date_published":"2024-05","updated_at":"2026-07-22T22:25:00Z","subjects":["Particulate Organic Matter","Soil Imaging","Computed Tomography","Fluorescence Imaging","Porosity","Water Retention"],"languages":["en","eng"],"rights":["Copyright 2024 Daniela Pope"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/124415","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Wander, Michelle","Ugarte, Carmen","Grift, Tony"]},{"key":"dc:creator","label":"Author","values":["Pope, Daniela Diaz"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-05","2024-04-30"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Natural Res & Env Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Particulate Organic Matter","Soil Imaging","Computed Tomography","Fluorescence Imaging","Porosity","Water Retention"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2024 Daniela Pope"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/124415"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms","The student, Daniela Pope, accepted the attached license on 2024-04-26 at 11:18.","The student, Daniela Pope, submitted this Thesis for approval on 2024-04-26 at 11:28.","This Thesis was approved for publication on 2024-04-30 at 16:11.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20655 on 2024-09-16 at 00:37:07","Soil water holding capacity and particulate organic matter (POM) are important soil health indicators that are typically quantified in the lab using laborious methods. This work, divided into two projects, addresses methods for quantification of these important metrics using high resolution imaging techniques. In the first project, micro-computed tomography (µ-CT) was used to quantify plant available water using object-oriented image analysis of intact soil cores to reveal microscale features of 3D void space. Soil cores from the Morrow Plots, established in 1876 on a Flanagan silty clay loam, were used to assess the capability of µ-CT image-derived soil-water descriptors through comparison with estimates derived from soil moisture release curves. The use of µ-CT imaging to directly image soil structure allowed for direct quantification of pore connectivity, a variable that is not provided by soil moisture release curves. Estimates of plant available water were positively correlated with mesopore connectivity density and average mesopore diameter. The agreement between mean porosity values estimated using destructive and non-destructive methods confirms the efficacy of image-based analysis. The agreement between estimated water content using indirect versus direct measures of porosity for use in the double exponential water model also indicate the ability of directly quantified pore fractions to predict water content. A second project attempted to determine if volumetric quantification of POM using µ-CT estimates and fluorescence imaging methods was viable and could be optimized. Using deep learning methods, we identified significant fluorescent wavelength pairs using PARAFAC analysis that were associated with naturally occurring POM and soil organic matter. Despite this, and previous work suggesting CT was a viable method at the aggregate level, neither method produced area-based estimates of POM contents that were correlated with values determined in the lab. Notable variability in estimates obtained from different soil types and from soils that were sieved or left intact suggests that neither imaging technique can produce reliable estimates of POM. Chapter one identified strategies to formalize reproducible and effective imaging protocols for soil structural analysis. Application of these strategies in chapter two allowed us to determine that while fluorescence imaging is useful for OM quality assessment, neither it nor µ-CT methods are promising for volumetric POM quantification."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["The use of high-resolution imaging tools for estimation of hydraulic soil properties and quantification of particulate organic matter"]}]}],"canonical_facts":{"dc:contributor":["Wander, Michelle","Ugarte, Carmen","Grift, Tony"],"dc:creator":["Pope, Daniela Diaz"],"dc:date":["2024-05","2024-04-30"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms","The student, Daniela Pope, accepted the attached license on 2024-04-26 at 11:18.","The student, Daniela Pope, submitted this Thesis for approval on 2024-04-26 at 11:28.","This Thesis was approved for publication on 2024-04-30 at 16:11.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20655 on 2024-09-16 at 00:37:07","Soil water holding capacity and particulate organic matter (POM) are important soil health indicators that are typically quantified in the lab using laborious methods. This work, divided into two projects, addresses methods for quantification of these important metrics using high resolution imaging techniques. In the first project, micro-computed tomography (µ-CT) was used to quantify plant available water using object-oriented image analysis of intact soil cores to reveal microscale features of 3D void space. Soil cores from the Morrow Plots, established in 1876 on a Flanagan silty clay loam, were used to assess the capability of µ-CT image-derived soil-water descriptors through comparison with estimates derived from soil moisture release curves. The use of µ-CT imaging to directly image soil structure allowed for direct quantification of pore connectivity, a variable that is not provided by soil moisture release curves. Estimates of plant available water were positively correlated with mesopore connectivity density and average mesopore diameter. The agreement between mean porosity values estimated using destructive and non-destructive methods confirms the efficacy of image-based analysis. The agreement between estimated water content using indirect versus direct measures of porosity for use in the double exponential water model also indicate the ability of directly quantified pore fractions to predict water content. A second project attempted to determine if volumetric quantification of POM using µ-CT estimates and fluorescence imaging methods was viable and could be optimized. Using deep learning methods, we identified significant fluorescent wavelength pairs using PARAFAC analysis that were associated with naturally occurring POM and soil organic matter. Despite this, and previous work suggesting CT was a viable method at the aggregate level, neither method produced area-based estimates of POM contents that were correlated with values determined in the lab. Notable variability in estimates obtained from different soil types and from soils that were sieved or left intact suggests that neither imaging technique can produce reliable estimates of POM. Chapter one identified strategies to formalize reproducible and effective imaging protocols for soil structural analysis. Application of these strategies in chapter two allowed us to determine that while fluorescence imaging is useful for OM quality assessment, neither it nor µ-CT methods are promising for volumetric POM quantification."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/124415"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Daniela Pope"],"dc:subject":["Particulate Organic Matter","Soil Imaging","Computed Tomography","Fluorescence Imaging","Porosity","Water Retention"],"dc:title":["The use of high-resolution imaging tools for estimation of hydraulic soil properties and quantification of particulate organic matter"],"dc:type":["text"],"thesis:degree_discipline":["Natural Res & Env Sciences"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:00Z"}