Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory

Background In studies of plant stress signaling, a major challenge is the lack of non-invasive methods to detect physiological plant responses and to characterize plant–plant communication over time and space. Results We acquired time series of phytocompound and hyperspectral imaging data from maize...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	do Prado Ribeiro, Leandro [verfasserIn] Klock, Adriana Lídia Santana Filho, João Américo Wordell Tramontin, Marco Aurélio Trapp, Marília Almeida Mithöfer, Axel Nansen, Christian

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Reflectance profiling Phytocompounds Plant stress signalling Plant defences Insect–plant interaction Plant phenomics

Anmerkung:	© The Author(s) 2018

Übergeordnetes Werk:	Enthalten in: Plant methods - London : BioMed Central, 2005, 14(2018), 1 vom: 06. Juli
Übergeordnetes Werk:	volume:14 ; year:2018 ; number:1 ; day:06 ; month:07

Links:	Volltext

DOI / URN:	10.1186/s13007-018-0322-7

Katalog-ID:	SPR029410037

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520			\|a Background In studies of plant stress signaling, a major challenge is the lack of non-invasive methods to detect physiological plant responses and to characterize plant–plant communication over time and space. Results We acquired time series of phytocompound and hyperspectral imaging data from maize plants from the following treatments: (1) individual non-infested plants, (2) individual plants experimentally subjected to herbivory by green belly stink bug (no visible symptoms of insect herbivory), (3) one plant subjected to insect herbivory and one control plant in a separate pot but inside the same cage, and (4) one plant subjected to insect herbivory and one control plant together in the same pot. Individual phytocompounds (except indole-3acetic acid) or spectral bands were not reliable indicators of neither insect herbivory nor plant–plant communication. However, using a linear discrimination classification method based on combinations of either phytocompounds or spectral bands, we found clear evidence of maize plant responses. Conclusions We have provided initial evidence of how hyperspectral imaging may be considered a powerful non-invasive method to increase our current understanding of both direct plant responses to biotic stressors but also to the multiple ways plant communities are able to communicate. We are unaware of any published studies, in which comprehensive phytocompound data have been shown to correlate with leaf reflectance. In addition, we are unaware of published studies, in which plant–plant communication was studied based on leaf reflectance.
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allfields	10.1186/s13007-018-0322-7 doi (DE-627)SPR029410037 (SPR)s13007-018-0322-7-e DE-627 ger DE-627 rakwb eng do Prado Ribeiro, Leandro verfasserin aut Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2018 Background In studies of plant stress signaling, a major challenge is the lack of non-invasive methods to detect physiological plant responses and to characterize plant–plant communication over time and space. Results We acquired time series of phytocompound and hyperspectral imaging data from maize plants from the following treatments: (1) individual non-infested plants, (2) individual plants experimentally subjected to herbivory by green belly stink bug (no visible symptoms of insect herbivory), (3) one plant subjected to insect herbivory and one control plant in a separate pot but inside the same cage, and (4) one plant subjected to insect herbivory and one control plant together in the same pot. Individual phytocompounds (except indole-3acetic acid) or spectral bands were not reliable indicators of neither insect herbivory nor plant–plant communication. However, using a linear discrimination classification method based on combinations of either phytocompounds or spectral bands, we found clear evidence of maize plant responses. Conclusions We have provided initial evidence of how hyperspectral imaging may be considered a powerful non-invasive method to increase our current understanding of both direct plant responses to biotic stressors but also to the multiple ways plant communities are able to communicate. We are unaware of any published studies, in which comprehensive phytocompound data have been shown to correlate with leaf reflectance. In addition, we are unaware of published studies, in which plant–plant communication was studied based on leaf reflectance. Reflectance profiling (dpeaa)DE-He213 Phytocompounds (dpeaa)DE-He213 Plant stress signalling (dpeaa)DE-He213 Plant defences (dpeaa)DE-He213 Insect–plant interaction (dpeaa)DE-He213 Plant phenomics (dpeaa)DE-He213 Klock, Adriana Lídia Santana aut Filho, João Américo Wordell aut Tramontin, Marco Aurélio aut Trapp, Marília Almeida aut Mithöfer, Axel aut Nansen, Christian (orcid)0000-0003-1324-1949 aut Enthalten in Plant methods London : BioMed Central, 2005 14(2018), 1 vom: 06. Juli (DE-627)500321191 (DE-600)2203723-8 1746-4811 nnns volume:14 year:2018 number:1 day:06 month:07 https://dx.doi.org/10.1186/s13007-018-0322-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2018 1 06 07
spelling	10.1186/s13007-018-0322-7 doi (DE-627)SPR029410037 (SPR)s13007-018-0322-7-e DE-627 ger DE-627 rakwb eng do Prado Ribeiro, Leandro verfasserin aut Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2018 Background In studies of plant stress signaling, a major challenge is the lack of non-invasive methods to detect physiological plant responses and to characterize plant–plant communication over time and space. Results We acquired time series of phytocompound and hyperspectral imaging data from maize plants from the following treatments: (1) individual non-infested plants, (2) individual plants experimentally subjected to herbivory by green belly stink bug (no visible symptoms of insect herbivory), (3) one plant subjected to insect herbivory and one control plant in a separate pot but inside the same cage, and (4) one plant subjected to insect herbivory and one control plant together in the same pot. Individual phytocompounds (except indole-3acetic acid) or spectral bands were not reliable indicators of neither insect herbivory nor plant–plant communication. However, using a linear discrimination classification method based on combinations of either phytocompounds or spectral bands, we found clear evidence of maize plant responses. Conclusions We have provided initial evidence of how hyperspectral imaging may be considered a powerful non-invasive method to increase our current understanding of both direct plant responses to biotic stressors but also to the multiple ways plant communities are able to communicate. We are unaware of any published studies, in which comprehensive phytocompound data have been shown to correlate with leaf reflectance. In addition, we are unaware of published studies, in which plant–plant communication was studied based on leaf reflectance. Reflectance profiling (dpeaa)DE-He213 Phytocompounds (dpeaa)DE-He213 Plant stress signalling (dpeaa)DE-He213 Plant defences (dpeaa)DE-He213 Insect–plant interaction (dpeaa)DE-He213 Plant phenomics (dpeaa)DE-He213 Klock, Adriana Lídia Santana aut Filho, João Américo Wordell aut Tramontin, Marco Aurélio aut Trapp, Marília Almeida aut Mithöfer, Axel aut Nansen, Christian (orcid)0000-0003-1324-1949 aut Enthalten in Plant methods London : BioMed Central, 2005 14(2018), 1 vom: 06. Juli (DE-627)500321191 (DE-600)2203723-8 1746-4811 nnns volume:14 year:2018 number:1 day:06 month:07 https://dx.doi.org/10.1186/s13007-018-0322-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2018 1 06 07
allfields_unstemmed	10.1186/s13007-018-0322-7 doi (DE-627)SPR029410037 (SPR)s13007-018-0322-7-e DE-627 ger DE-627 rakwb eng do Prado Ribeiro, Leandro verfasserin aut Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2018 Background In studies of plant stress signaling, a major challenge is the lack of non-invasive methods to detect physiological plant responses and to characterize plant–plant communication over time and space. Results We acquired time series of phytocompound and hyperspectral imaging data from maize plants from the following treatments: (1) individual non-infested plants, (2) individual plants experimentally subjected to herbivory by green belly stink bug (no visible symptoms of insect herbivory), (3) one plant subjected to insect herbivory and one control plant in a separate pot but inside the same cage, and (4) one plant subjected to insect herbivory and one control plant together in the same pot. Individual phytocompounds (except indole-3acetic acid) or spectral bands were not reliable indicators of neither insect herbivory nor plant–plant communication. However, using a linear discrimination classification method based on combinations of either phytocompounds or spectral bands, we found clear evidence of maize plant responses. Conclusions We have provided initial evidence of how hyperspectral imaging may be considered a powerful non-invasive method to increase our current understanding of both direct plant responses to biotic stressors but also to the multiple ways plant communities are able to communicate. We are unaware of any published studies, in which comprehensive phytocompound data have been shown to correlate with leaf reflectance. In addition, we are unaware of published studies, in which plant–plant communication was studied based on leaf reflectance. Reflectance profiling (dpeaa)DE-He213 Phytocompounds (dpeaa)DE-He213 Plant stress signalling (dpeaa)DE-He213 Plant defences (dpeaa)DE-He213 Insect–plant interaction (dpeaa)DE-He213 Plant phenomics (dpeaa)DE-He213 Klock, Adriana Lídia Santana aut Filho, João Américo Wordell aut Tramontin, Marco Aurélio aut Trapp, Marília Almeida aut Mithöfer, Axel aut Nansen, Christian (orcid)0000-0003-1324-1949 aut Enthalten in Plant methods London : BioMed Central, 2005 14(2018), 1 vom: 06. Juli (DE-627)500321191 (DE-600)2203723-8 1746-4811 nnns volume:14 year:2018 number:1 day:06 month:07 https://dx.doi.org/10.1186/s13007-018-0322-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2018 1 06 07
allfieldsGer	10.1186/s13007-018-0322-7 doi (DE-627)SPR029410037 (SPR)s13007-018-0322-7-e DE-627 ger DE-627 rakwb eng do Prado Ribeiro, Leandro verfasserin aut Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2018 Background In studies of plant stress signaling, a major challenge is the lack of non-invasive methods to detect physiological plant responses and to characterize plant–plant communication over time and space. Results We acquired time series of phytocompound and hyperspectral imaging data from maize plants from the following treatments: (1) individual non-infested plants, (2) individual plants experimentally subjected to herbivory by green belly stink bug (no visible symptoms of insect herbivory), (3) one plant subjected to insect herbivory and one control plant in a separate pot but inside the same cage, and (4) one plant subjected to insect herbivory and one control plant together in the same pot. Individual phytocompounds (except indole-3acetic acid) or spectral bands were not reliable indicators of neither insect herbivory nor plant–plant communication. However, using a linear discrimination classification method based on combinations of either phytocompounds or spectral bands, we found clear evidence of maize plant responses. Conclusions We have provided initial evidence of how hyperspectral imaging may be considered a powerful non-invasive method to increase our current understanding of both direct plant responses to biotic stressors but also to the multiple ways plant communities are able to communicate. We are unaware of any published studies, in which comprehensive phytocompound data have been shown to correlate with leaf reflectance. In addition, we are unaware of published studies, in which plant–plant communication was studied based on leaf reflectance. Reflectance profiling (dpeaa)DE-He213 Phytocompounds (dpeaa)DE-He213 Plant stress signalling (dpeaa)DE-He213 Plant defences (dpeaa)DE-He213 Insect–plant interaction (dpeaa)DE-He213 Plant phenomics (dpeaa)DE-He213 Klock, Adriana Lídia Santana aut Filho, João Américo Wordell aut Tramontin, Marco Aurélio aut Trapp, Marília Almeida aut Mithöfer, Axel aut Nansen, Christian (orcid)0000-0003-1324-1949 aut Enthalten in Plant methods London : BioMed Central, 2005 14(2018), 1 vom: 06. Juli (DE-627)500321191 (DE-600)2203723-8 1746-4811 nnns volume:14 year:2018 number:1 day:06 month:07 https://dx.doi.org/10.1186/s13007-018-0322-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2018 1 06 07
allfieldsSound	10.1186/s13007-018-0322-7 doi (DE-627)SPR029410037 (SPR)s13007-018-0322-7-e DE-627 ger DE-627 rakwb eng do Prado Ribeiro, Leandro verfasserin aut Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2018 Background In studies of plant stress signaling, a major challenge is the lack of non-invasive methods to detect physiological plant responses and to characterize plant–plant communication over time and space. Results We acquired time series of phytocompound and hyperspectral imaging data from maize plants from the following treatments: (1) individual non-infested plants, (2) individual plants experimentally subjected to herbivory by green belly stink bug (no visible symptoms of insect herbivory), (3) one plant subjected to insect herbivory and one control plant in a separate pot but inside the same cage, and (4) one plant subjected to insect herbivory and one control plant together in the same pot. Individual phytocompounds (except indole-3acetic acid) or spectral bands were not reliable indicators of neither insect herbivory nor plant–plant communication. However, using a linear discrimination classification method based on combinations of either phytocompounds or spectral bands, we found clear evidence of maize plant responses. Conclusions We have provided initial evidence of how hyperspectral imaging may be considered a powerful non-invasive method to increase our current understanding of both direct plant responses to biotic stressors but also to the multiple ways plant communities are able to communicate. We are unaware of any published studies, in which comprehensive phytocompound data have been shown to correlate with leaf reflectance. In addition, we are unaware of published studies, in which plant–plant communication was studied based on leaf reflectance. Reflectance profiling (dpeaa)DE-He213 Phytocompounds (dpeaa)DE-He213 Plant stress signalling (dpeaa)DE-He213 Plant defences (dpeaa)DE-He213 Insect–plant interaction (dpeaa)DE-He213 Plant phenomics (dpeaa)DE-He213 Klock, Adriana Lídia Santana aut Filho, João Américo Wordell aut Tramontin, Marco Aurélio aut Trapp, Marília Almeida aut Mithöfer, Axel aut Nansen, Christian (orcid)0000-0003-1324-1949 aut Enthalten in Plant methods London : BioMed Central, 2005 14(2018), 1 vom: 06. Juli (DE-627)500321191 (DE-600)2203723-8 1746-4811 nnns volume:14 year:2018 number:1 day:06 month:07 https://dx.doi.org/10.1186/s13007-018-0322-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2018 1 06 07
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topic_facet	Reflectance profiling Phytocompounds Plant stress signalling Plant defences Insect–plant interaction Plant phenomics
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Results We acquired time series of phytocompound and hyperspectral imaging data from maize plants from the following treatments: (1) individual non-infested plants, (2) individual plants experimentally subjected to herbivory by green belly stink bug (no visible symptoms of insect herbivory), (3) one plant subjected to insect herbivory and one control plant in a separate pot but inside the same cage, and (4) one plant subjected to insect herbivory and one control plant together in the same pot. Individual phytocompounds (except indole-3acetic acid) or spectral bands were not reliable indicators of neither insect herbivory nor plant–plant communication. However, using a linear discrimination classification method based on combinations of either phytocompounds or spectral bands, we found clear evidence of maize plant responses. 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author	do Prado Ribeiro, Leandro
spellingShingle	do Prado Ribeiro, Leandro misc Reflectance profiling misc Phytocompounds misc Plant stress signalling misc Plant defences misc Insect–plant interaction misc Plant phenomics Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory
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topic_title	Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory Reflectance profiling (dpeaa)DE-He213 Phytocompounds (dpeaa)DE-He213 Plant stress signalling (dpeaa)DE-He213 Plant defences (dpeaa)DE-He213 Insect–plant interaction (dpeaa)DE-He213 Plant phenomics (dpeaa)DE-He213
topic	misc Reflectance profiling misc Phytocompounds misc Plant stress signalling misc Plant defences misc Insect–plant interaction misc Plant phenomics
topic_unstemmed	misc Reflectance profiling misc Phytocompounds misc Plant stress signalling misc Plant defences misc Insect–plant interaction misc Plant phenomics
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title	Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory
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title_full	Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory
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title_sort	hyperspectral imaging to characterize plant–plant communication in response to insect herbivory
title_auth	Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory
abstract	Background In studies of plant stress signaling, a major challenge is the lack of non-invasive methods to detect physiological plant responses and to characterize plant–plant communication over time and space. Results We acquired time series of phytocompound and hyperspectral imaging data from maize plants from the following treatments: (1) individual non-infested plants, (2) individual plants experimentally subjected to herbivory by green belly stink bug (no visible symptoms of insect herbivory), (3) one plant subjected to insect herbivory and one control plant in a separate pot but inside the same cage, and (4) one plant subjected to insect herbivory and one control plant together in the same pot. Individual phytocompounds (except indole-3acetic acid) or spectral bands were not reliable indicators of neither insect herbivory nor plant–plant communication. However, using a linear discrimination classification method based on combinations of either phytocompounds or spectral bands, we found clear evidence of maize plant responses. Conclusions We have provided initial evidence of how hyperspectral imaging may be considered a powerful non-invasive method to increase our current understanding of both direct plant responses to biotic stressors but also to the multiple ways plant communities are able to communicate. We are unaware of any published studies, in which comprehensive phytocompound data have been shown to correlate with leaf reflectance. In addition, we are unaware of published studies, in which plant–plant communication was studied based on leaf reflectance. © The Author(s) 2018
abstractGer	Background In studies of plant stress signaling, a major challenge is the lack of non-invasive methods to detect physiological plant responses and to characterize plant–plant communication over time and space. Results We acquired time series of phytocompound and hyperspectral imaging data from maize plants from the following treatments: (1) individual non-infested plants, (2) individual plants experimentally subjected to herbivory by green belly stink bug (no visible symptoms of insect herbivory), (3) one plant subjected to insect herbivory and one control plant in a separate pot but inside the same cage, and (4) one plant subjected to insect herbivory and one control plant together in the same pot. Individual phytocompounds (except indole-3acetic acid) or spectral bands were not reliable indicators of neither insect herbivory nor plant–plant communication. However, using a linear discrimination classification method based on combinations of either phytocompounds or spectral bands, we found clear evidence of maize plant responses. Conclusions We have provided initial evidence of how hyperspectral imaging may be considered a powerful non-invasive method to increase our current understanding of both direct plant responses to biotic stressors but also to the multiple ways plant communities are able to communicate. We are unaware of any published studies, in which comprehensive phytocompound data have been shown to correlate with leaf reflectance. In addition, we are unaware of published studies, in which plant–plant communication was studied based on leaf reflectance. © The Author(s) 2018
abstract_unstemmed	Background In studies of plant stress signaling, a major challenge is the lack of non-invasive methods to detect physiological plant responses and to characterize plant–plant communication over time and space. Results We acquired time series of phytocompound and hyperspectral imaging data from maize plants from the following treatments: (1) individual non-infested plants, (2) individual plants experimentally subjected to herbivory by green belly stink bug (no visible symptoms of insect herbivory), (3) one plant subjected to insect herbivory and one control plant in a separate pot but inside the same cage, and (4) one plant subjected to insect herbivory and one control plant together in the same pot. Individual phytocompounds (except indole-3acetic acid) or spectral bands were not reliable indicators of neither insect herbivory nor plant–plant communication. However, using a linear discrimination classification method based on combinations of either phytocompounds or spectral bands, we found clear evidence of maize plant responses. Conclusions We have provided initial evidence of how hyperspectral imaging may be considered a powerful non-invasive method to increase our current understanding of both direct plant responses to biotic stressors but also to the multiple ways plant communities are able to communicate. We are unaware of any published studies, in which comprehensive phytocompound data have been shown to correlate with leaf reflectance. In addition, we are unaware of published studies, in which plant–plant communication was studied based on leaf reflectance. © The Author(s) 2018
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title_short	Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory
url	https://dx.doi.org/10.1186/s13007-018-0322-7
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author2	Klock, Adriana Lídia Santana Filho, João Américo Wordell Tramontin, Marco Aurélio Trapp, Marília Almeida Mithöfer, Axel Nansen, Christian
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up_date	2024-07-04T00:51:00.357Z
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Results We acquired time series of phytocompound and hyperspectral imaging data from maize plants from the following treatments: (1) individual non-infested plants, (2) individual plants experimentally subjected to herbivory by green belly stink bug (no visible symptoms of insect herbivory), (3) one plant subjected to insect herbivory and one control plant in a separate pot but inside the same cage, and (4) one plant subjected to insect herbivory and one control plant together in the same pot. Individual phytocompounds (except indole-3acetic acid) or spectral bands were not reliable indicators of neither insect herbivory nor plant–plant communication. However, using a linear discrimination classification method based on combinations of either phytocompounds or spectral bands, we found clear evidence of maize plant responses. Conclusions We have provided initial evidence of how hyperspectral imaging may be considered a powerful non-invasive method to increase our current understanding of both direct plant responses to biotic stressors but also to the multiple ways plant communities are able to communicate. We are unaware of any published studies, in which comprehensive phytocompound data have been shown to correlate with leaf reflectance. 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Hyperspectral imaging to characterize plant–plant communication in response to insect herbivory

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