Development of an Automated Low-Cost Multispectral Imaging System to Quantify Canopy Size and Pigmentation
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| Publicado en: | Sensors vol. 24, no. 17 (2024), p. 5515 |
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| Autor principal: | |
| Otros Autores: | , , , , , , |
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MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 045 | 2 | |b d20240101 |b d20241231 | |
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| 100 | 1 | |a Wacker, Kahlin |u Department of Horticulture, University of Georgia, Athens, GA 30602, USA; <email>kahlin.wacker@uga.edu</email> (K.W.); <email>mvanier@uga.edu</email> (M.W.v.I.); <email>benjaminsidore@gmail.com</email> (B.S.) | |
| 245 | 1 | |a Development of an Automated Low-Cost Multispectral Imaging System to Quantify Canopy Size and Pigmentation | |
| 260 | |b MDPI AG |c 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Canopy imaging offers a non-destructive, efficient way to objectively measure canopy size, detect stress symptoms, and assess pigment concentrations. While it is faster and easier than traditional destructive methods, manual image analysis, including segmentation and evaluation, can be time-consuming. To make imaging more widely accessible, it’s essential to reduce the cost of imaging systems and automate the analysis process. We developed a low-cost imaging system with automated analysis using an embedded microcomputer equipped with a monochrome camera and a filter for a total hardware cost of ~USD 500. Our imaging system takes images under blue, green, red, and infrared light, as well as chlorophyll fluorescence. The system uses a Python-based program to collect and analyze images automatically. The multi-spectral imaging system separates plants from the background using a chlorophyll fluorescence image, which is also used to quantify canopy size. The system then generates normalized difference vegetation index (NDVI, “greenness”) images and histograms, providing quantitative, spatially resolved information. We verified that these indices correlate with leaf chlorophyll content and can easily add other indices by installing light sources with the desired spectrums. The low cost of the system can make this imaging technology widely available. | |
| 651 | 4 | |a United States--US | |
| 653 | |a Physiology | ||
| 653 | |a Machine learning | ||
| 653 | |a Software | ||
| 653 | |a Algorithms | ||
| 653 | |a Automation | ||
| 653 | |a Plant growth | ||
| 653 | |a Light | ||
| 653 | |a Chlorophyll | ||
| 653 | |a Compatible hardware | ||
| 653 | |a Sensors | ||
| 700 | 1 | |a Kim, Changhyeon |u Department of Plant Science and Landscape Architecture, University of Connecticut, Storrs, CT 06269, USA; <email>changhyeon.kim@uconn.edu</email> | |
| 700 | 1 | |a van Iersel, Marc W |u Department of Horticulture, University of Georgia, Athens, GA 30602, USA; <email>kahlin.wacker@uga.edu</email> (K.W.); <email>mvanier@uga.edu</email> (M.W.v.I.); <email>benjaminsidore@gmail.com</email> (B.S.) | |
| 700 | 1 | |a Sidore, Benjamin |u Department of Horticulture, University of Georgia, Athens, GA 30602, USA; <email>kahlin.wacker@uga.edu</email> (K.W.); <email>mvanier@uga.edu</email> (M.W.v.I.); <email>benjaminsidore@gmail.com</email> (B.S.) | |
| 700 | 1 | |a Pham, Tony |u College of Engineering, University of Georgia, Athens, GA 30602, USA; <email>tmp52468@uga.edu</email> (T.P.); <email>mhaidekk@uga.edu</email> (M.H.) | |
| 700 | 1 | |a Haidekker, Mark |u College of Engineering, University of Georgia, Athens, GA 30602, USA; <email>tmp52468@uga.edu</email> (T.P.); <email>mhaidekk@uga.edu</email> (M.H.) | |
| 700 | 1 | |a Seymour, Lynne |u Department of Statistics, University of Georgia, Athens, GA 30602, USA; <email>seymour@uga.edu</email> | |
| 700 | 1 | |a Ferrarezi, Rhuanito Soranz |u Department of Horticulture, University of Georgia, Athens, GA 30602, USA; <email>kahlin.wacker@uga.edu</email> (K.W.); <email>mvanier@uga.edu</email> (M.W.v.I.); <email>benjaminsidore@gmail.com</email> (B.S.) | |
| 773 | 0 | |t Sensors |g vol. 24, no. 17 (2024), p. 5515 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3104073989/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3104073989/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
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