Preprint Article Version 1 NOT YET PEER-REVIEWED

Peach Flower Monitoring Using Aerial Multispectral Imaging

Version 1 : Received: 4 November 2016 / Approved: 7 November 2016 / Online: 7 November 2016 (05:18:19 CET)

A peer-reviewed article of this Preprint also exists.

Horton, R.; Cano, E.; Bulanon, D.; Fallahi, E. Peach Flower Monitoring Using Aerial Multispectral Imaging. J. Imaging 2017, 3, 2. Horton, R.; Cano, E.; Bulanon, D.; Fallahi, E. Peach Flower Monitoring Using Aerial Multispectral Imaging. J. Imaging 2017, 3, 2.

Journal reference: J. Imaging 2017, 3, 2
DOI: 10.3390/jimaging3010002

Abstract

One of the tools for optimal crop production is 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 paper presents the development of an image processing algorithm to detect peach blossoms on 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 system. 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 demonstrate good potential as a monitoring tool for orchard management.

Subject Areas

blossoms; digital image processing; machine vision; peaches; unmanned aerial system

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