It is crucial to improve the efficiency of plant breeding and crop yield in order to fulfill rising food demands. In plant phenotyping study, the capability to correlate morphological traits of plants plays an important role. However, measuring the plant phenotypes manually is prone to human errors, labor intensive and time-consuming. Hence, it is important to develop techniques for measurement of plant phenotypic data accurately and rapidly. The objective of this study was to find out the feasibility of point cloud data of 3D LiDAR including RGB image for plant phenotyping. The obtained results were then verified through the manually acquired data for sorghum and soybean plant samples. The overall results showed remarkable correlation between point cloud data and manually acquired data for plant phenotyping. This correlation indicates that the 3D Lidar imaging system have potential to measure phenotypes of crops in rapid and accurate way.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.