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Sensing and Automation in Pruning of Apple Trees: A Review
- Source :
- Agronomy, Vol 8, Iss 10, p 211 (2018)
- Publication Year :
- 2018
- Publisher :
- MDPI AG, 2018.
-
Abstract
- Pruning is one of the most important tree fruit production activities, which is highly dependent on human labor. Skilled labor is in short supply, and the increasing cost of labor is becoming a big issue for the tree fruit industry. Meanwhile, worker safety is another issue in the manual pruning. Growers are motivated to seek mechanical or robotic solutions for reducing the amount of hand labor required for pruning. Identifying tree branches/canopies with sensors as well as automated operating pruning activity are the important components in the automated pruning system. This paper reviews the research and development of sensing and automated systems for branch pruning in apple production. Tree training systems, pruning strategies, 3D structure reconstruction of tree branches, and practice mechanisms or robotics are some of the developments that need to be addressed for an effective tree branch pruning system. Our study summarizes the potential opportunities for automatic pruning with machine-friendly modern tree architectures, previous studies on sensor development, and efforts to develop and deploy mechanical/robotic systems for automated branch pruning. We also describe two examples of qualified pruning strategies that could potentially simplify the automated pruning decision and pruning end-effector design. Finally, the limitations of current pruning technologies and other challenges for automated branch pruning are described, and possible solutions are discussed.
- Subjects :
- 0106 biological sciences
Computer science
pruning
Machine learning
computer.software_genre
tree fruit
01 natural sciences
lcsh:Agriculture
Pruning (decision trees)
sensing
automation
robotics
business.industry
lcsh:S
Robotics
04 agricultural and veterinary sciences
Automation
Tree (data structure)
Robotic systems
040103 agronomy & agriculture
0401 agriculture, forestry, and fisheries
Artificial intelligence
business
Agronomy and Crop Science
computer
010606 plant biology & botany
Subjects
Details
- ISSN :
- 20734395
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- Agronomy
- Accession number :
- edsair.doi.dedup.....154708de8009fa5e5bfcbb2dc67c2066