GrowPro: a flexible and high-resolution imaging tool for high-throughput plant phenotyping in the field
Date
2018-07-04
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
ORCID
0000-0002-1460-6068
Type
Thesis
Degree Level
Masters
Abstract
Various remote sensing platforms are being used in agriculture research, but their capability and
exibility
may not be enough for carrying out e cient computer analysis. Low-quality data can a ect the accuracy
of methods and techniques used for high-throughput phenotyping in plant breeding. Despite the fact that
there are many available remote sensing tools, researchers are seeking new platforms with superior features
and performance over already proven systems.
In this thesis, we describe a novel approach for remote sensing for eld-based phenotyping called the
GrowPro. This thesis presents an overview of related work and commonly available approaches to remote
sensing, description of the designed system, data gathering procedure, post-processing pipeline and best
practice for capturing plants.
We show the ease of use of the GrowPro, simplicity of data gathering and qualify the accuracy of the
stitching process. We proved that by using this novel approach, high-resolution RGB stitched images of
regions of interests (e.g., an individual plot or range of plots) can be obtained. This method appeared to be
stable over time, di erent trials and weather conditions. Examples of RGB stitched images of a variety of
crops at various stages of growth have been described.
Description
Keywords
HTP, field phenotyping, remote sensing, GrowPro
Citation
Degree
Master of Science (M.Sc.)
Department
Computer Science
Program
Computer Science