<p>Nowadays, soybean is one the most consumed crops in the
world. As the human population continuously increases, new phenotyping
technology is needed to help plant scientists breed soybean that has
high-yield, stress-tolerant, and disease-tolerant traits. Hyperspectral imaging
(HSI) is one of the most commonly used technologies for phenotyping. The
current HSI techniques include HSI tower and remote sensing on an unmanned
aerial vehicle (UAV) or satellite. There are several noise sources the current
HSI technologies suffer from such as changes in lighting conditions, leaf
angle, and other environmental factors. To reduce the noise on HS images, a new
portable, leaf-level, high-resolution HSI device was developed for corn leaves
in 2018 called LeafSpec. Due to the previous design requiring a sliding action
along the leaf which could damage the leaf if used on a soybean leaf, a new
design of the LeafSpec was built to meet the requirements of scanning soybean
leaves. The new LeafSpec device protects the leaf between two sheets of glass,
and the scanning action is automated by using motors and servos. After the HS
images have been collected, the current modeling method for HS images starts by
averaging all the plant pixels to one spectrum which causes a loss of information
because of the non-uniformity of the leaf. When comparing the two modeling
methods, one uses the mean normalized difference vegetation index (NDVI) and
the other uses the NDVI heatmap of the entire leaf to predict the nitrogen
content of soybean plants. The model that uses NDVI heatmap shows a significant
increase in prediction accuracy with an R2 increase from 0.805 to 0.871.
Therefore, it can be concluded that the changes occurring within the leaf can
be used to train a better prediction model. </p>
<p>Although the LeafSpec device can provide high-resolution
leaf-level HS images to the researcher for the first time, it suffers from two
major drawbacks: intensive labor needed to gather the image data and slow
throughput. A new idea is proposed to use a UAV that carries a 6 degree of
freedom (DOF) robotic arm with a LeafSpec device as an end-effect to
automatically gather soybean leaf HS images. A new UAV is designed and built to
carry the large payload weight of the robotic arm and LeafSpec.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/14997936 |
| Date | 19 July 2021 |
| Creators | Jialei Wang (11147142) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/Automated_Leaf-Level_Hyperspectral_Imaging_of_Soybean_Plants_using_an_UAV_with_a_6_DOF_Robotic_Arm/14997936 |
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