Peach Blossom Monitoring Using Small Unmanned Aerial Systems
Faculty Mentor Information
Duke M Bulanon Esmaeil Fallahi
Presentation Date
7-2016
Abstract
One tool for optimal crop production is the regular monitoring and assessment of crops. During the growing season of fruit trees, the bloom period has increased photosynthetic rates that correlate with the fruiting process. This poster presents the development of an image processing algorithm to detect the blossoms on peach trees. Images of an experimental peach orchard were acquired from the Parma Research and Extension Center of the University of Idaho using an off-the-shelf unmanned aerial system (UAS), equipped with a multispectral camera (Near-infrared, Green, Blue). The orchard has different stone fruit varieties and different plant training systems. Individual tree images (high-resolution) and arrays of trees images (low-resolution) were acquired to evaluate the detection capability. The image processing algorithm was based on different vegetation indices. Initial results showed that the image processing algorithm could detect peach blossoms and demonstrated good potential as a monitoring tool for orchard management.
Peach Blossom Monitoring Using Small Unmanned Aerial Systems
One tool for optimal crop production is the regular monitoring and assessment of crops. During the growing season of fruit trees, the bloom period has increased photosynthetic rates that correlate with the fruiting process. This poster presents the development of an image processing algorithm to detect the blossoms on peach trees. Images of an experimental peach orchard were acquired from the Parma Research and Extension Center of the University of Idaho using an off-the-shelf unmanned aerial system (UAS), equipped with a multispectral camera (Near-infrared, Green, Blue). The orchard has different stone fruit varieties and different plant training systems. Individual tree images (high-resolution) and arrays of trees images (low-resolution) were acquired to evaluate the detection capability. The image processing algorithm was based on different vegetation indices. Initial results showed that the image processing algorithm could detect peach blossoms and demonstrated good potential as a monitoring tool for orchard management.
Comments
Poster #W59