Processing Pipeline of Sugarcane Spectral Response to Characterize the Fallen Plants Phenomenon

Autores
Solano, Agustín; Kemerer, Alejandra Cecilia; Hadad, Alejandro Javier
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Trabajo presentado al 20th Argentinean Bioengineering Society Congress, SABI 2015 (XX Congreso Argentino de Bioingeniería y IX Jornadas de Ingeniería Clínica)28–30 October 2015, San Nicolás de los Arroyos, Argentina
Nowadays, in agronomic systems it is possible to make a variable management of inputs to improve the efficiency of agronomic industry and optimize the logistics of the harvesting process. In this way, it was proposed for sugarcane culture the use of remote sensing tools and computational methods to identify useful areas in the cultivated lands. The objective was to use these areas to make variable management of the crop. When at the moment of harvesting the sugarcane there are fallen stalks, together with them some strange material (vegetal or mineral) is collected. This strange material is not millable and when it enters onto the sugar mill it causes important looses of efficiency in the sugar extraction processes and affects its quality. Considering this issue, the spectral response of sugarcane plants in aerial multispectral images was studied. The spectral response was analyzed in different bands of the electromagnetic spectrum. Then, the aerial images were segmented to obtain homogeneous regions useful for producers to make decisions related to the use of inputs and resources according to the variability of the system (existence of fallen cane and standing cane). The obtained segmentation results were satisfactory. It was possible to identify regions with fallen cane and regions with standing cane with high precision rates.
EEA Paraná
Fil: Solano, A. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; Argentina
Fil: Kemerer, Alejandra Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná. Grupo Recursos Naturales y Factores Abióticos; Argentina
Fil: Kemerer, Alejandra Cecilia. IUniversidad Nacional de Entre Ríos. Facultad de Ciencias Agrarias; Argentina
Fil: Hadad, Alejandro Javier. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; Argentina
Fuente
Journal of Physics: Conference Series 705 : 012025. (2016)
Materia
Caña de Azúcar
Teledetección
Imágenes Multiespectrales
Manejo del Cultivo
Sugar Cane
Remote Sensing
Multispectral Imagery
Crop Management
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/14770
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oai_identifier_str oai:localhost:20.500.12123/14770
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spelling Processing Pipeline of Sugarcane Spectral Response to Characterize the Fallen Plants PhenomenonSolano, AgustínKemerer, Alejandra CeciliaHadad, Alejandro JavierCaña de AzúcarTeledetecciónImágenes MultiespectralesManejo del CultivoSugar CaneRemote SensingMultispectral ImageryCrop ManagementTrabajo presentado al 20th Argentinean Bioengineering Society Congress, SABI 2015 (XX Congreso Argentino de Bioingeniería y IX Jornadas de Ingeniería Clínica)28–30 October 2015, San Nicolás de los Arroyos, ArgentinaNowadays, in agronomic systems it is possible to make a variable management of inputs to improve the efficiency of agronomic industry and optimize the logistics of the harvesting process. In this way, it was proposed for sugarcane culture the use of remote sensing tools and computational methods to identify useful areas in the cultivated lands. The objective was to use these areas to make variable management of the crop. When at the moment of harvesting the sugarcane there are fallen stalks, together with them some strange material (vegetal or mineral) is collected. This strange material is not millable and when it enters onto the sugar mill it causes important looses of efficiency in the sugar extraction processes and affects its quality. Considering this issue, the spectral response of sugarcane plants in aerial multispectral images was studied. The spectral response was analyzed in different bands of the electromagnetic spectrum. Then, the aerial images were segmented to obtain homogeneous regions useful for producers to make decisions related to the use of inputs and resources according to the variability of the system (existence of fallen cane and standing cane). The obtained segmentation results were satisfactory. It was possible to identify regions with fallen cane and regions with standing cane with high precision rates.EEA ParanáFil: Solano, A. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; ArgentinaFil: Kemerer, Alejandra Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná. Grupo Recursos Naturales y Factores Abióticos; ArgentinaFil: Kemerer, Alejandra Cecilia. IUniversidad Nacional de Entre Ríos. Facultad de Ciencias Agrarias; ArgentinaFil: Hadad, Alejandro Javier. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; ArgentinaIOP Science2023-07-18T17:49:15Z2023-07-18T17:49:15Z2016info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/14770https://iopscience.iop.org/article/10.1088/1742-6596/705/1/0120251742-6596https://doi.org/10.1088/1742-6596/705/1/012025Journal of Physics: Conference Series 705 : 012025. (2016)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-10-16T09:31:12Zoai:localhost:20.500.12123/14770instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-16 09:31:12.566INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Processing Pipeline of Sugarcane Spectral Response to Characterize the Fallen Plants Phenomenon
title Processing Pipeline of Sugarcane Spectral Response to Characterize the Fallen Plants Phenomenon
spellingShingle Processing Pipeline of Sugarcane Spectral Response to Characterize the Fallen Plants Phenomenon
Solano, Agustín
Caña de Azúcar
Teledetección
Imágenes Multiespectrales
Manejo del Cultivo
Sugar Cane
Remote Sensing
Multispectral Imagery
Crop Management
title_short Processing Pipeline of Sugarcane Spectral Response to Characterize the Fallen Plants Phenomenon
title_full Processing Pipeline of Sugarcane Spectral Response to Characterize the Fallen Plants Phenomenon
title_fullStr Processing Pipeline of Sugarcane Spectral Response to Characterize the Fallen Plants Phenomenon
title_full_unstemmed Processing Pipeline of Sugarcane Spectral Response to Characterize the Fallen Plants Phenomenon
title_sort Processing Pipeline of Sugarcane Spectral Response to Characterize the Fallen Plants Phenomenon
dc.creator.none.fl_str_mv Solano, Agustín
Kemerer, Alejandra Cecilia
Hadad, Alejandro Javier
author Solano, Agustín
author_facet Solano, Agustín
Kemerer, Alejandra Cecilia
Hadad, Alejandro Javier
author_role author
author2 Kemerer, Alejandra Cecilia
Hadad, Alejandro Javier
author2_role author
author
dc.subject.none.fl_str_mv Caña de Azúcar
Teledetección
Imágenes Multiespectrales
Manejo del Cultivo
Sugar Cane
Remote Sensing
Multispectral Imagery
Crop Management
topic Caña de Azúcar
Teledetección
Imágenes Multiespectrales
Manejo del Cultivo
Sugar Cane
Remote Sensing
Multispectral Imagery
Crop Management
dc.description.none.fl_txt_mv Trabajo presentado al 20th Argentinean Bioengineering Society Congress, SABI 2015 (XX Congreso Argentino de Bioingeniería y IX Jornadas de Ingeniería Clínica)28–30 October 2015, San Nicolás de los Arroyos, Argentina
Nowadays, in agronomic systems it is possible to make a variable management of inputs to improve the efficiency of agronomic industry and optimize the logistics of the harvesting process. In this way, it was proposed for sugarcane culture the use of remote sensing tools and computational methods to identify useful areas in the cultivated lands. The objective was to use these areas to make variable management of the crop. When at the moment of harvesting the sugarcane there are fallen stalks, together with them some strange material (vegetal or mineral) is collected. This strange material is not millable and when it enters onto the sugar mill it causes important looses of efficiency in the sugar extraction processes and affects its quality. Considering this issue, the spectral response of sugarcane plants in aerial multispectral images was studied. The spectral response was analyzed in different bands of the electromagnetic spectrum. Then, the aerial images were segmented to obtain homogeneous regions useful for producers to make decisions related to the use of inputs and resources according to the variability of the system (existence of fallen cane and standing cane). The obtained segmentation results were satisfactory. It was possible to identify regions with fallen cane and regions with standing cane with high precision rates.
EEA Paraná
Fil: Solano, A. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; Argentina
Fil: Kemerer, Alejandra Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná. Grupo Recursos Naturales y Factores Abióticos; Argentina
Fil: Kemerer, Alejandra Cecilia. IUniversidad Nacional de Entre Ríos. Facultad de Ciencias Agrarias; Argentina
Fil: Hadad, Alejandro Javier. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; Argentina
description Trabajo presentado al 20th Argentinean Bioengineering Society Congress, SABI 2015 (XX Congreso Argentino de Bioingeniería y IX Jornadas de Ingeniería Clínica)28–30 October 2015, San Nicolás de los Arroyos, Argentina
publishDate 2016
dc.date.none.fl_str_mv 2016
2023-07-18T17:49:15Z
2023-07-18T17:49:15Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/14770
https://iopscience.iop.org/article/10.1088/1742-6596/705/1/012025
1742-6596
https://doi.org/10.1088/1742-6596/705/1/012025
url http://hdl.handle.net/20.500.12123/14770
https://iopscience.iop.org/article/10.1088/1742-6596/705/1/012025
https://doi.org/10.1088/1742-6596/705/1/012025
identifier_str_mv 1742-6596
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IOP Science
publisher.none.fl_str_mv IOP Science
dc.source.none.fl_str_mv Journal of Physics: Conference Series 705 : 012025. (2016)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
_version_ 1846143560442707968
score 12.712165

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