Abstract
An indoor wireless fixed camera network was developed for an efficient, cost-effective method of extracting informative plant phenotypes in a controlled greenhouse environment. Deployed at the Donald Danforth Plant Science Center (DDPSC), this fixed camera platform implements rapid and automated plant phenotyping. The platform uses low-cost Raspberry Pi computers and digital cameras to monitor aboveground morphological and developmental plant phenotypes. The Raspberry Pi is a readily programmable, credit card-sized computer board with remote accessibility. A standard camera module connects to the Raspberry Pi computer board and generates eight-megapixel resolution images. With a fixed array, or “bramble,” of Raspberry Pi computer boards and camera modules placed strategically in a greenhouse, we can capture automated, high-resolution images for 3D reconstructions of individual plants on timescales ranging from minutes to hours, capturing temporal changes in plant phenotypes.
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Acknowledgments
This protocol reflects the input of a larger project team including César Lizárraga, Brandon Patrick, Phil Ozersky, Stuart Marshall, Bradley Flynn, Avisek Datta, and Darren O’Brien. The information presented here is based upon work partially supported by the National Science Foundation under Award Number IIA-1355406 and the US Department of Energy Advanced Research Projects Agency-Energy (ARPA-E) under Cooperative Agreement Number DE-AR0000594. The views and opinions of authors expressed herein do not necessarily state or reflect those of the US government or any agency thereof.
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Shakoor, N., Mockler, T.C. (2022). Wireless Fixed Camera Network for Greenhouse-Based Plant Phenotyping. In: Lorence, A., Medina Jimenez, K. (eds) High-Throughput Plant Phenotyping. Methods in Molecular Biology, vol 2539. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2537-8_6
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DOI: https://doi.org/10.1007/978-1-0716-2537-8_6
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