This work demonstrates how a high throughput\nrobotic machine vision systems can quantify seedling\ndevelopment with high spatial and temporal resolution.The\nthroughput that the system provides is high enough to match\nthe needs of functional genomics research. Analyzing images\nof plant seedlings growing and responding to stimuli is a\nproven approach to finding the effects of an affected gene.\nHowever, with 104 genes in a typical plant genome, comprehensive\nstudies will require high throughput methodologies.\nTo increase throughput without sacrificing spatial or\ntemporal resolution, a 3 axis robotic gantry system utilizing\nvisual servoing was developed. The gantry consists of\ndirect drive linear servo motors that can move the cameras\nat a speed of 1 m/s with an accuracy of 1 ?m, and a repeatability\nof 0.1 ?m. Perpendicular to the optical axis of the\ncameras was a 1 m2 sample fixture holds 36 Petri plates in\nwhich 144 Arabidopsis thaliana seedlings (4 per Petri plate)\ngrew vertically along the surface of an agar gel. A probabilistic\nimage analysis algorithm was used to locate the root\nof seedlings and a normalized gray scale variance measure\nwas used to achieve focus by servoing along the optical axis.\nRotation of the sample holder induced a gravitropic bending\nresponse in the roots, which are approximately 45 ?m wide\nand several millimeter in length. The custom hardware and\nsoftware described here accurately quantified the gravitropic\nresponses of the seedlings in parallel at approximately 3 min\nintervals over an 8-h period. Here we present an overview of\nour system and describe some of the necessary capabilities\nand challenges to automating plant phenotype studies.
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