{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/86047"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/86047","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Machine Vision Systems for Real-Time Plant Variability Sensing and in-Field Application","abstract":"In-field variations associated with corn plant spacing, growth stage, and population can lead to a significant yield differences. Since the ability to reduce these variations is directly related to the planter performance, a machine vision-based emerged corn plant sensing system (ECS) was developed for the performance evaluation for prototype planters. With the real-time image sequencing capability, the system also achieved an average spacing measurement error of less than 10 mm.","abstract_html":"In-field variations associated with corn plant spacing, growth stage, and population can lead to a significant yield differences. Since the ability to reduce these variations is directly related to the planter performance, a machine vision-based emerged corn plant sensing system (ECS) was developed for the performance evaluation for prototype planters. With the real-time image sequencing capability, the system also achieved an average spacing measurement error of less than 10 mm.","abstract_has_math":false,"creators":["Tang, Lie"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Agricultural Engineering","degree_department":null,"school":null,"contributors":["Lei Tian"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-28T14:53:45Z","date_published":"2015-09-28T14:53:45Z","updated_at":"2026-07-22T22:26:26Z","subjects":["Agriculture, Agronomy"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3044237"],"render_values":[{"text":"(MiAaPQ)AAI3044237","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/86047","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Lei Tian"]},{"key":"dc:creator","label":"Author","values":["Tang, Lie"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-28T14:53:45Z","10000-01-01","2002"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Agricultural Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"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":["Agriculture, Agronomy"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/86047","(MiAaPQ)AAI3044237"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["In-field variations associated with corn plant spacing, growth stage, and population can lead to a significant yield differences. Since the ability to reduce these variations is directly related to the planter performance, a machine vision-based emerged corn plant sensing system (ECS) was developed for the performance evaluation for prototype planters. With the real-time image sequencing capability, the system also achieved an average spacing measurement error of less than 10 mm.","Made available in DSpace on 2015-09-28T14:53:45Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3044237.pdf: 8311122 bytes, checksum: 93b9ba437b1fd76de4a8f0bc243f2502 (MD5) Previous issue date: 2002","Embargo set by: Seth Robbins for item 87328 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","150 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002."]},{"key":"dc:title","label":"Title","values":["Machine Vision Systems for Real-Time Plant Variability Sensing and in-Field Application"]}]}],"canonical_facts":{"dc:contributor":["Lei Tian"],"dc:creator":["Tang, Lie"],"dc:date":["2015-09-28T14:53:45Z","10000-01-01","2002"],"dc:description":["In-field variations associated with corn plant spacing, growth stage, and population can lead to a significant yield differences. Since the ability to reduce these variations is directly related to the planter performance, a machine vision-based emerged corn plant sensing system (ECS) was developed for the performance evaluation for prototype planters. With the real-time image sequencing capability, the system also achieved an average spacing measurement error of less than 10 mm.","Made available in DSpace on 2015-09-28T14:53:45Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3044237.pdf: 8311122 bytes, checksum: 93b9ba437b1fd76de4a8f0bc243f2502 (MD5) Previous issue date: 2002","Embargo set by: Seth Robbins for item 87328 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","150 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002."],"dc:identifier":["http://hdl.handle.net/2142/86047","(MiAaPQ)AAI3044237"],"dc:language":["eng"],"dc:subject":["Agriculture, Agronomy"],"dc:title":["Machine Vision Systems for Real-Time Plant Variability Sensing and in-Field Application"],"dc:type":["text"],"thesis:degree_discipline":["Agricultural Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:26Z"}