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Raspberry plant stress detection using hyperspectral imaging

Monitoring plant responses to stress is an ongoing challenge for crop breeders, growers, and agronomists. The measurement of below‐ground stress is particularly challenging as plants do not always show visible signs of stress in the above‐ground organs, particularly at early stages. Hyperspectral im...

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Autores principales: Williams, Dominic, Karley, Alison, Britten, Avril, McCallum, Susan, Graham, Julie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020142/
https://www.ncbi.nlm.nih.gov/pubmed/36937793
http://dx.doi.org/10.1002/pld3.490
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author Williams, Dominic
Karley, Alison
Britten, Avril
McCallum, Susan
Graham, Julie
author_facet Williams, Dominic
Karley, Alison
Britten, Avril
McCallum, Susan
Graham, Julie
author_sort Williams, Dominic
collection PubMed
description Monitoring plant responses to stress is an ongoing challenge for crop breeders, growers, and agronomists. The measurement of below‐ground stress is particularly challenging as plants do not always show visible signs of stress in the above‐ground organs, particularly at early stages. Hyperspectral imaging is a technique that could be used to overcome this challenge if associations between plant spectral data and specific stresses can be determined. In this study, three genotypes of red raspberry plants grown under controlled conditions in a glasshouse were subjected to below‐ground biotic stresses (root pathogen Phytophthora rubi and root herbivore Otiorhynchus sulcatus ) or abiotic stress (soil water availability) and regularly imaged using hyperspectral cameras over this period. Significant differences were observed in plant biophysical traits (canopy height and leaf dry mass) and canopy reflectance spectrum between the three genotypes and the imposed stress treatments. The ratio of reflectance at 469 and 523 nm showed a significant genotype‐by‐treatment interaction driven by differential genotypic responses to the P. rubi treatment. This indicates that spectral imaging can be used to identify variable plant stress responses in raspberry plants.
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spelling pubmed-100201422023-03-18 Raspberry plant stress detection using hyperspectral imaging Williams, Dominic Karley, Alison Britten, Avril McCallum, Susan Graham, Julie Plant Direct Original Research Monitoring plant responses to stress is an ongoing challenge for crop breeders, growers, and agronomists. The measurement of below‐ground stress is particularly challenging as plants do not always show visible signs of stress in the above‐ground organs, particularly at early stages. Hyperspectral imaging is a technique that could be used to overcome this challenge if associations between plant spectral data and specific stresses can be determined. In this study, three genotypes of red raspberry plants grown under controlled conditions in a glasshouse were subjected to below‐ground biotic stresses (root pathogen Phytophthora rubi and root herbivore Otiorhynchus sulcatus ) or abiotic stress (soil water availability) and regularly imaged using hyperspectral cameras over this period. Significant differences were observed in plant biophysical traits (canopy height and leaf dry mass) and canopy reflectance spectrum between the three genotypes and the imposed stress treatments. The ratio of reflectance at 469 and 523 nm showed a significant genotype‐by‐treatment interaction driven by differential genotypic responses to the P. rubi treatment. This indicates that spectral imaging can be used to identify variable plant stress responses in raspberry plants. John Wiley and Sons Inc. 2023-03-16 /pmc/articles/PMC10020142/ /pubmed/36937793 http://dx.doi.org/10.1002/pld3.490 Text en © 2023 The Authors. Plant Direct published by American Society of Plant Biologists and the Society for Experimental Biology and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Williams, Dominic
Karley, Alison
Britten, Avril
McCallum, Susan
Graham, Julie
Raspberry plant stress detection using hyperspectral imaging
title Raspberry plant stress detection using hyperspectral imaging
title_full Raspberry plant stress detection using hyperspectral imaging
title_fullStr Raspberry plant stress detection using hyperspectral imaging
title_full_unstemmed Raspberry plant stress detection using hyperspectral imaging
title_short Raspberry plant stress detection using hyperspectral imaging
title_sort raspberry plant stress detection using hyperspectral imaging
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020142/
https://www.ncbi.nlm.nih.gov/pubmed/36937793
http://dx.doi.org/10.1002/pld3.490
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