Automated Pruning of Greenhouse Indeterminate Tomato Plants

<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>

Name thesis:degree_name

MS in Computer Science

Discipline thesis:degree_discipline

Computer Science

Year dc:date.available

2018

Author dc:creator

• Angeja, Joey M

Contributors dc:contributor

• Jane Zhang

• Computer Vision
• Automated Pruning
• Agriculture
• Plant Pruning
• Computational Engineering
• Robotics

Identifier

10.15368/theses.2018.37

OAI identifier oai:identifier

oai:digitalcommons.calpoly.edu:theses-3167