{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/95517"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/95517","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Soil texture determination by an acoustic cone penetrometer method","abstract":"Soil texture is an important soil property, contributing to many aspects of soil performance, ranging from productivity to ease of tillage. Currently, textural analysis is either estimated in the field with limited accuracy, or analyzed in a laboratory setting through a time consuming and labor intensive process. This study outlines the development of a new system for in-situ soil textural analysis using an automated cone penetrometer outfitted with a microphone, where the resulting sound produced from the cone-soil interface is used to determine soil texture. The system was tested in a laboratory setting using soil samples with well defined textural compositions. Correlations between the textural breakdown of the samples, and the power for certain frequency ranges were made. The prediction model for clay that was developed had an adjusted R2 of 0.950, while the models for silt and sand had lower adjusted R2 values. Future research should look into the effects of soil moisture content, bulk density, and organic matter content on the acoustic signal.","abstract_html":"Soil texture is an important soil property, contributing to many aspects of soil performance, ranging from productivity to ease of tillage. Currently, textural analysis is either estimated in the field with limited accuracy, or analyzed in a laboratory setting through a time consuming and labor intensive process. This study outlines the development of a new system for in-situ soil textural analysis using an automated cone penetrometer outfitted with a microphone, where the resulting sound produced from the cone-soil interface is used to determine soil texture. The system was tested in a laboratory setting using soil samples with well defined textural compositions. Correlations between the textural breakdown of the samples, and the power for certain frequency ranges were made. The prediction model for clay that was developed had an adjusted R2 of 0.950, while the models for silt and sand had lower adjusted R2 values. Future research should look into the effects of soil moisture content, bulk density, and organic matter content on the acoustic signal.","abstract_has_math":false,"creators":["Tate, Brandon Lee"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Agricultural and Biological Engineering","degree_department":null,"school":null,"contributors":["Grift, Tony E."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-03-01T16:37:10Z","date_published":"2017-03-01T16:37:10Z","updated_at":"2026-07-22T22:26:37Z","subjects":["Soil texture"],"languages":["en"],"rights":["Copyright 2016 Brandon L. 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Correlations between the textural breakdown of the samples, and the power for certain frequency ranges were made. The prediction model for clay that was developed had an adjusted R2 of 0.950, while the models for silt and sand had lower adjusted R2 values. Future research should look into the effects of soil moisture content, bulk density, and organic matter content on the acoustic signal.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2018-12-01","The student, Brandon Tate, accepted the attached license on 2016-12-06 at 17:31.","The student, Brandon Tate, submitted this Thesis for approval on 2016-12-06 at 17:40.","This Thesis was approved for publication on 2016-12-08 at 16:11.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10462 on 2017-02-28 at 14:37:30","Made available in DSpace on 2017-03-01T16:37:10Z (GMT). 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Currently, textural analysis is either estimated in the field with limited accuracy, or analyzed in a laboratory setting through a time consuming and labor intensive process. This study outlines the development of a new system for in-situ soil textural analysis using an automated cone penetrometer outfitted with a microphone, where the resulting sound produced from the cone-soil interface is used to determine soil texture. The system was tested in a laboratory setting using soil samples with well defined textural compositions. Correlations between the textural breakdown of the samples, and the power for certain frequency ranges were made. The prediction model for clay that was developed had an adjusted R2 of 0.950, while the models for silt and sand had lower adjusted R2 values. 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