Automated vision system studies, analyzes plant growth for crop improvement purposes
Plant physiology researchers at the University of Wisconsin-Madison have designed an automated vision system which utilizes CCD cameras and a robotic gantry positioning system to acquire and analyze images of plants for the purpose of determining how a genetic manipulation affects plant growth and development.
Plant physiology researchers at the University of Wisconsin-Madison have designed an automated vision system that acquires and analyzes images of plants for the purpose of determining how a genetic manipulation affects plant growth and development.
Researchers placed the genetically-manipulated plant samples in an LED-illuminated 6 x 6 grid of Petri plates mounted on a vertical tubular aluminum frame to conduct 36 simultaneous experiments, according to a press release. The image capture system uses an XYZ vertical robotic gantry positioning system from IntelLiDrives to control the positioning of two Allied Vision Technologies (AVT) Marlin F146B CCD cameras, which monitor and capture images of the plants.
AVT’s Marlin cameras feature a 2/3” global shutter Sony CMOS image sensor with a 1280 x 1024 pixel format and 6.7 µm x 6.7 µm pixel size. The cameras also feature a frame rate of up to 25 fps.
The XYZ robots moves the CCD cameras over a 1m x 1m area with a position resolution of 10 µm and an additional linear axis allows the camera’s field of view to change to acquire images of the seedlings in the Petri plates. Once the images are captured, they are analyzed to determine cellular growth rates in the root as well as the angle and curvature of the root tip. Computer vision algorithms developed by the University of Wisconsin-Madison research team measure the sizes of seeds, plants’ cellular growth rates, and the angle and curvature of the roots.
With this system, the researchers were able to automate the plant growth time-lapsed image acquisition and processing and increase the throughput of experiments to track the plants growth and development. It also enabled the research them to find the genes that control plant’s root growth and have fundamental importance to crop improvement.
Former VSD Editor James Carroll joined the team 2013. Carroll covered machine vision and imaging from numerous angles, including application stories, industry news, market updates, and new products. In addition to writing and editing articles, Carroll managed the Innovators Awards program and webcasts.
