Pruning of indeterminate tomato plants is vital for a profitable yield and it still remains a manual process. There has been research in automated pruning of grapevines, trees, and other plants, but tomato plants have yet to be explored. Wage increases are contributing to the depleting profits of greenhouse tomato farmers. Rises in population are the driving force behind the need for efficient growing techniques. The major contribution of this thesis is a computer vision algorithm for detecting greenhouse tomato pruning points without the use of depth sensors. Given an up-close 2-D image of a tomato stem with the background excluded, the algorithm proposed in this work can detect and mark the tomato suckers.
","abstract_html":"<p>Pruning of indeterminate tomato plants is vital for a profitable yield and it still remains a manual process. There has been research in automated pruning of grapevines, trees, and other plants, but tomato plants have yet to be explored. Wage increases are contributing to the depleting profits of greenhouse tomato farmers. Rises in population are the driving force behind the need for efficient growing techniques. The major contribution of this thesis is a computer vision algorithm for detecting greenhouse tomato pruning points without the use of depth sensors. Given an up-close 2-D image of a tomato stem with the background excluded, the algorithm proposed in this work can detect and mark the tomato suckers.</p>","abstract_has_math":false,"creators":["Angeja, Joey M"],"institution":null,"degree_name":"MS in Computer Science","degree_level":null,"degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Jane Zhang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-06-01T07:00:00Z","date_published":"2018-06-01T07:00:00Z","updated_at":"2026-07-24T01:31:56Z","subjects":["Computer Vision","Automated Pruning","Agriculture","Plant Pruning","Computational Engineering","Robotics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["10.15368/theses.2018.37"],"render_values":[{"text":"10.15368/theses.2018.37","href":"https://doi.org/10.15368/theses.2018.37","code":true}]}]},"links":{"outbound_url":"https://digitalcommons.calpoly.edu/theses/1839","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Jane Zhang"]},{"key":"dc:creator","label":"Author","values":["Angeja, Joey M"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-06-11T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS in Computer Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Computer Vision","Automated Pruning","Agriculture","Plant Pruning","Computational Engineering","Robotics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.calpoly.edu/theses/1839","10.15368/theses.2018.37"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Pruning of indeterminate tomato plants is vital for a profitable yield and it still remains a manual process. There has been research in automated pruning of grapevines, trees, and other plants, but tomato plants have yet to be explored. Wage increases are contributing to the depleting profits of greenhouse tomato farmers. Rises in population are the driving force behind the need for efficient growing techniques. The major contribution of this thesis is a computer vision algorithm for detecting greenhouse tomato pruning points without the use of depth sensors. Given an up-close 2-D image of a tomato stem with the background excluded, the algorithm proposed in this work can detect and mark the tomato suckers.
"]},{"key":"dc:title","label":"Title","values":["Automated Pruning of Greenhouse Indeterminate Tomato Plants"]}]}],"canonical_facts":{"dc:contributor":["Jane Zhang"],"dc:creator":["Angeja, Joey M"],"dc:date.available":["2018-06-11T07:00:00Z"],"dc:description.abstract":["Pruning of indeterminate tomato plants is vital for a profitable yield and it still remains a manual process. There has been research in automated pruning of grapevines, trees, and other plants, but tomato plants have yet to be explored. Wage increases are contributing to the depleting profits of greenhouse tomato farmers. Rises in population are the driving force behind the need for efficient growing techniques. The major contribution of this thesis is a computer vision algorithm for detecting greenhouse tomato pruning points without the use of depth sensors. Given an up-close 2-D image of a tomato stem with the background excluded, the algorithm proposed in this work can detect and mark the tomato suckers.
"],"dc:identifier":["https://digitalcommons.calpoly.edu/theses/1839","10.15368/theses.2018.37"],"dc:subject":["Computer Vision","Automated Pruning","Agriculture","Plant Pruning","Computational Engineering","Robotics"],"dc:title":["Automated Pruning of Greenhouse Indeterminate Tomato Plants"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_name":["MS in Computer Science"]},"updated_at":"2026-07-24T01:31:56Z"}