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Development of an accurate low cost NDVI imaging system for assessing plant health
BACKGROUND: Spectral imaging is a key method for high throughput phenotyping that can be related to a large variety of biological parameters. The Normalised Difference Vegetation Index (NDVI), uses specific wavelengths to compare crop health and performance. Increasing the accessibility of spectral...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887843/ https://www.ncbi.nlm.nih.gov/pubmed/36717879 http://dx.doi.org/10.1186/s13007-023-00981-8 |
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author | Stamford, John D. Vialet-Chabrand, Silvere Cameron, Iain Lawson, Tracy |
author_facet | Stamford, John D. Vialet-Chabrand, Silvere Cameron, Iain Lawson, Tracy |
author_sort | Stamford, John D. |
collection | PubMed |
description | BACKGROUND: Spectral imaging is a key method for high throughput phenotyping that can be related to a large variety of biological parameters. The Normalised Difference Vegetation Index (NDVI), uses specific wavelengths to compare crop health and performance. Increasing the accessibility of spectral imaging systems through the development of small, low cost, and easy to use platforms will generalise its use for precision agriculture. We describe a method for using a dual camera system connected to a Raspberry Pi to produce NDVI imagery, referred to as NDVIpi. Spectral reference targets were used to calibrate images into values of reflectance, that are then used to calculated NDVI with improved accuracy compared with systems that use single references/standards. RESULTS: NDVIpi imagery showed strong performance against standard spectrometry, as an accurate measurement of leaf NDVI. The NDVIpi was also compared to a relatively more expensive commercial camera (Micasense RedEdge), with both cameras having a comparable performance in measuring NDVI. There were differences between the NDVI values of the NDVIpi and the RedEdge, which could be attributed to the measurement of different wavelengths for use in the NDVI calculation by each camera. Subsequently, the wavelengths used by the NDVIpi show greater sensitivity to changes in chlorophyll content than the RedEdge. CONCLUSION: We present a methodology for a Raspberry Pi based NDVI imaging system that utilizes low cost, off-the-shelf components, and a robust multi-reference calibration protocols that provides accurate NDVI measurements. When compared with a commercial system, comparable NDVI values were obtained, despite the fact that our system was a fraction of the cost. Our results also highlight the importance of the choice of red wavelengths in the calculation of NDVI, which resulted in differences in sensitivity between camera systems. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13007-023-00981-8. |
format | Online Article Text |
id | pubmed-9887843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98878432023-02-01 Development of an accurate low cost NDVI imaging system for assessing plant health Stamford, John D. Vialet-Chabrand, Silvere Cameron, Iain Lawson, Tracy Plant Methods Methodology BACKGROUND: Spectral imaging is a key method for high throughput phenotyping that can be related to a large variety of biological parameters. The Normalised Difference Vegetation Index (NDVI), uses specific wavelengths to compare crop health and performance. Increasing the accessibility of spectral imaging systems through the development of small, low cost, and easy to use platforms will generalise its use for precision agriculture. We describe a method for using a dual camera system connected to a Raspberry Pi to produce NDVI imagery, referred to as NDVIpi. Spectral reference targets were used to calibrate images into values of reflectance, that are then used to calculated NDVI with improved accuracy compared with systems that use single references/standards. RESULTS: NDVIpi imagery showed strong performance against standard spectrometry, as an accurate measurement of leaf NDVI. The NDVIpi was also compared to a relatively more expensive commercial camera (Micasense RedEdge), with both cameras having a comparable performance in measuring NDVI. There were differences between the NDVI values of the NDVIpi and the RedEdge, which could be attributed to the measurement of different wavelengths for use in the NDVI calculation by each camera. Subsequently, the wavelengths used by the NDVIpi show greater sensitivity to changes in chlorophyll content than the RedEdge. CONCLUSION: We present a methodology for a Raspberry Pi based NDVI imaging system that utilizes low cost, off-the-shelf components, and a robust multi-reference calibration protocols that provides accurate NDVI measurements. When compared with a commercial system, comparable NDVI values were obtained, despite the fact that our system was a fraction of the cost. Our results also highlight the importance of the choice of red wavelengths in the calculation of NDVI, which resulted in differences in sensitivity between camera systems. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13007-023-00981-8. BioMed Central 2023-01-30 /pmc/articles/PMC9887843/ /pubmed/36717879 http://dx.doi.org/10.1186/s13007-023-00981-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Stamford, John D. Vialet-Chabrand, Silvere Cameron, Iain Lawson, Tracy Development of an accurate low cost NDVI imaging system for assessing plant health |
title | Development of an accurate low cost NDVI imaging system for assessing plant health |
title_full | Development of an accurate low cost NDVI imaging system for assessing plant health |
title_fullStr | Development of an accurate low cost NDVI imaging system for assessing plant health |
title_full_unstemmed | Development of an accurate low cost NDVI imaging system for assessing plant health |
title_short | Development of an accurate low cost NDVI imaging system for assessing plant health |
title_sort | development of an accurate low cost ndvi imaging system for assessing plant health |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887843/ https://www.ncbi.nlm.nih.gov/pubmed/36717879 http://dx.doi.org/10.1186/s13007-023-00981-8 |
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