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Resumen
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
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dc.contributor.author | Solano, Agustín | |
dc.contributor.author | Kemerer, Alejandra Cecilia | |
dc.contributor.author | Hadad, Alejandro Javier | |
dc.date.accessioned | 2023-07-18T17:49:15Z | |
dc.date.available | 2023-07-18T17:49:15Z | |
dc.date.issued | 2016 | |
dc.identifier.issn | 1742-6596 | |
dc.identifier.other | https://doi.org/10.1088/1742-6596/705/1/012025 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12123/14770 | |
dc.identifier.uri | https://iopscience.iop.org/article/10.1088/1742-6596/705/1/012025 | |
dc.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 | es_AR |
dc.description.abstract | 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. | eng |
dc.format | application/pdf | es_AR |
dc.language.iso | eng | es_AR |
dc.publisher | IOP Science | es_AR |
dc.rights | info:eu-repo/semantics/openAccess | es_AR |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | es_AR |
dc.source | Journal of Physics: Conference Series 705 : 012025. (2016) | es_AR |
dc.subject | Caña de Azúcar | es_AR |
dc.subject | Sugar Cane | eng |
dc.subject | Teledetección | es_AR |
dc.subject | Remote Sensing | eng |
dc.subject | Imágenes Multiespectrales | es_AR |
dc.subject | Multispectral Imagery | eng |
dc.subject | Manejo del Cultivo | es_AR |
dc.subject | Crop Management | eng |
dc.title | Processing Pipeline of Sugarcane Spectral Response to Characterize the Fallen Plants Phenomenon | es_AR |
dc.type | info:ar-repo/semantics/artículo | es_AR |
dc.type | info:eu-repo/semantics/article | es_AR |
dc.type | info:eu-repo/semantics/publishedVersion | es_AR |
dc.rights.license | Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) | es_AR |
dc.description.origen | EEA Paraná | es_AR |
dc.description.fil | Fil: Solano, A. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; Argentina | es_AR |
dc.description.fil | Fil: Kemerer, Alejandra Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná. Grupo Recursos Naturales y Factores Abióticos; Argentina | es_AR |
dc.description.fil | Fil: Kemerer, Alejandra Cecilia. IUniversidad Nacional de Entre Ríos. Facultad de Ciencias Agrarias; Argentina | es_AR |
dc.description.fil | Fil: Hadad, Alejandro Javier. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Grupo de Investigación en Inteligencia Artificial; Argentina | es_AR |
dc.subtype | cientifico |
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