Raspberry Pi-powered imaging for plant phenotyping
| Autor: | James C. Carrington, Noah Fahlgren, Malia A. Gehan, Andy Lin, Monica Tessman, John Steen Hoyer, Dmitri A. Nusinow, Jose Carlos Tovar, Steven T. Callen, Allison Tielking, S. Elizabeth Castillo, Michael Miller |
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| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
0301 basic medicine Raspberry Pi ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image processing Plant Science Image processing software Biology Protocol Notes 01 natural sciences Raspberry pi 03 medical and health sciences Phenomics Protocol Note morphology Image acquisition Protocol (object-oriented programming) Ecology Evolution Behavior and Systematics Plant diversity For the Special Issue: Methods for Exploring the Plant Tree of Life Invited Special Article business.industry imaging Plant phenotyping low‐cost phenotyping 030104 developmental biology business Computer hardware 010606 plant biology & botany |
| Zdroj: | Applications in Plant Sciences |
| ISSN: | 2168-0450 |
| Popis: | Premise of the study Image-based phenomics is a powerful approach to capture and quantify plant diversity. However, commercial platforms that make consistent image acquisition easy are often cost-prohibitive. To make high-throughput phenotyping methods more accessible, low-cost microcomputers and cameras can be used to acquire plant image data. Methods and results We used low-cost Raspberry Pi computers and cameras to manage and capture plant image data. Detailed here are three different applications of Raspberry Pi-controlled imaging platforms for seed and shoot imaging. Images obtained from each platform were suitable for extracting quantifiable plant traits (e.g., shape, area, height, color) en masse using open-source image processing software such as PlantCV. Conclusions This protocol describes three low-cost platforms for image acquisition that are useful for quantifying plant diversity. When coupled with open-source image processing tools, these imaging platforms provide viable low-cost solutions for incorporating high-throughput phenomics into a wide range of research programs. |
| Databáze: | OpenAIRE |
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