Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia
Citrus greening disease (Huanglongbing-HLB) is considered the most destructive citrus disease worldwide. Of the three species of Candidatus liberibacter associated with HLB, two have been recently reported in Latin America. The first report of HLB in Colombia was in March 2016. In this paper, a data...
- Autores:
-
Chavarro Mesa, Edisson
De la Hoz Domínguez, Enrique José
Fennix Agudelo, Mary Andrea
Miranda-Castro, Wendy
Ángel-Díaz, Jorge Evelio
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/10025
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/10025
https://ieeexplore.ieee.org/document/9247900
- Palabra clave:
- Diaphorina citri
Random Forest
K-Nearest Neighbors
LEMB
- Rights
- closedAccess
- License
- http://purl.org/coar/access_right/c_14cb
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Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia |
| title |
Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia |
| spellingShingle |
Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia Diaphorina citri Random Forest K-Nearest Neighbors LEMB |
| title_short |
Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia |
| title_full |
Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia |
| title_fullStr |
Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia |
| title_full_unstemmed |
Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia |
| title_sort |
Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia |
| dc.creator.fl_str_mv |
Chavarro Mesa, Edisson De la Hoz Domínguez, Enrique José Fennix Agudelo, Mary Andrea Miranda-Castro, Wendy Ángel-Díaz, Jorge Evelio |
| dc.contributor.author.none.fl_str_mv |
Chavarro Mesa, Edisson De la Hoz Domínguez, Enrique José Fennix Agudelo, Mary Andrea Miranda-Castro, Wendy Ángel-Díaz, Jorge Evelio |
| dc.subject.keywords.spa.fl_str_mv |
Diaphorina citri Random Forest K-Nearest Neighbors |
| topic |
Diaphorina citri Random Forest K-Nearest Neighbors LEMB |
| dc.subject.armarc.none.fl_str_mv |
LEMB |
| description |
Citrus greening disease (Huanglongbing-HLB) is considered the most destructive citrus disease worldwide. Of the three species of Candidatus liberibacter associated with HLB, two have been recently reported in Latin America. The first report of HLB in Colombia was in March 2016. In this paper, a dataset was extracted for six departments in the northern zone of Colombia, where has been previously reported, applying image georeferencing with QGIS Software. Preliminary Random Forest and K-Nearest Neighbors (KNN) machine learning models were used in order to test and validate the obtained results, for disease monitoring and HLB incidence prediction. The performance of both models was also compared, obtaining a 100% AUC value with Random Forest model. |
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2020 |
| dc.date.issued.none.fl_str_mv |
2020-11-09 |
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2021-02-16T15:09:08Z |
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2021-02-16T15:09:08Z |
| dc.date.submitted.none.fl_str_mv |
2021-02-12 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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info:eu-repo/semantics/lecture |
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http://purl.org/coar/resource_type/c_8544 |
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publishedVersion |
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E. Chavarro-Mesa, E. Delahoz-Domínguez, M. Fennix-Agudelo, W. Miranda-Castro and J. E. Ángel-Díaz, "Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia," 2020 IEEE Colombian Conference on Applications of Computational Intelligence (IEEE ColCACI 2020), Cali, Colombia, 2020, pp. 1-4, doi: 10.1109/ColCACI50549.2020.9247900. |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/10025 |
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https://ieeexplore.ieee.org/document/9247900 |
| dc.identifier.doi.none.fl_str_mv |
10.1109/ColCACI50549.2020.9247900 |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
E. Chavarro-Mesa, E. Delahoz-Domínguez, M. Fennix-Agudelo, W. Miranda-Castro and J. E. Ángel-Díaz, "Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia," 2020 IEEE Colombian Conference on Applications of Computational Intelligence (IEEE ColCACI 2020), Cali, Colombia, 2020, pp. 1-4, doi: 10.1109/ColCACI50549.2020.9247900. 10.1109/ColCACI50549.2020.9247900 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
| url |
https://hdl.handle.net/20.500.12585/10025 https://ieeexplore.ieee.org/document/9247900 |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
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closedAccess |
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4 páginas |
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application/pdf |
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Cartagena de Indias |
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2020 IEEE Colombian Conference on Applications of Computational Intelligence (IEEE ColCACI 2020) |
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Chavarro Mesa, Edisson800ba77d-129a-48f9-bc50-2a8c25be1208De la Hoz Domínguez, Enrique José140641a4-ba89-4a1d-bbcb-0c3f2d597b0dFennix Agudelo, Mary Andreab6da7c0e-a860-4d45-a87b-3d6871885959Miranda-Castro, Wendy42268df0-ad55-478f-ba40-62bdc92ac36bÁngel-Díaz, Jorge Evelio1ddbfb9b-542f-4e38-99b4-3cb2c41a1d132021-02-16T15:09:08Z2021-02-16T15:09:08Z2020-11-092021-02-12E. Chavarro-Mesa, E. Delahoz-Domínguez, M. Fennix-Agudelo, W. Miranda-Castro and J. E. Ángel-Díaz, "Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombia," 2020 IEEE Colombian Conference on Applications of Computational Intelligence (IEEE ColCACI 2020), Cali, Colombia, 2020, pp. 1-4, doi: 10.1109/ColCACI50549.2020.9247900.https://hdl.handle.net/20.500.12585/10025https://ieeexplore.ieee.org/document/924790010.1109/ColCACI50549.2020.9247900Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarCitrus greening disease (Huanglongbing-HLB) is considered the most destructive citrus disease worldwide. Of the three species of Candidatus liberibacter associated with HLB, two have been recently reported in Latin America. The first report of HLB in Colombia was in March 2016. In this paper, a dataset was extracted for six departments in the northern zone of Colombia, where has been previously reported, applying image georeferencing with QGIS Software. Preliminary Random Forest and K-Nearest Neighbors (KNN) machine learning models were used in order to test and validate the obtained results, for disease monitoring and HLB incidence prediction. The performance of both models was also compared, obtaining a 100% AUC value with Random Forest model.4 páginasapplication/pdfeng2020 IEEE Colombian Conference on Applications of Computational Intelligence (IEEE ColCACI 2020)Preliminary machine learning model for citrus greening disease (Huanglongbing-HLB) prediction in Colombiainfo:eu-repo/semantics/lectureinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_8544http://purl.org/coar/version/c_970fb48d4fbd8a85Diaphorina citriRandom ForestK-Nearest NeighborsLEMBinfo:eu-repo/semantics/closedAccesshttp://purl.org/coar/access_right/c_14cbCartagena de IndiasInvestigadoresM. M. Robles-González et al., "Síntomas del Huanglongbing (HLB) enárboles de limón mexicano [Citrus aurantifolia (Christm) Swingle] y su dispersión en el estado de Colima México", Rev. Chapingo. Ser. Hortic, vol. 19, no. 1, pp. 15-31, 2013.C. Santivañez, G. Mora Aguilera, G. Díaz Padilla, J. I. Lopez Arrollo and P. Vernal Hurtado, "Citrus: Marco estratégico para la gestión regional del Huanglongbing en América Latina y el Caribe", 2013.T. H. Hung, S. C. Hung, C. N. Chen, M. H. Hsu and H. J. Su, "Detection by PCR of Candidatus Liberibacter asiaticus the bacterium causing citrus huanglongbing in vector psyllids: Application to the study of vector-pathogen relationships", Plant Pathol, 2004.K. L. Manjunath, S. E. Halbert, C. Ramadugu, S. Webb and R. F. Lee, "Detection of ‘Candidatus Liberibacter asiaticus’ in Diaphorina citri and its importance in the management of citrus huanglongbing in Florida", Phytopathology, 2008."La amenaza del HLB (Huanglongbing de los cítricos) para la citricultura nacional", Nov 2013, [online] Available: http://www.senasa.gov.ar/contenido.php?to=nin=11io=18493.Comunicado de prensa: autoridades del SFE confirman presencia de ‘Dragón Amarillo’ en árboles de la Zona Norte. In: Ministerio de Agricultura y Ganadería de Costa Rica, Sep 2011, [online] Available: https://www.sfe.go.cr/documentos/comunicados/2011/2102 2011 SFE confirma presencia HLB en zona norte.pdf.K. L. Manjunath, C. Ramadugu, V. M. Majil, S. Williams, M. Irey and R. F. Lee, "First report of the citrus huanglongbing associated bacterium ‘candidatus liberibacter asiaticus’ from sweet orange mexican lime and Asian citrus psyllid in Belize", Plant Dis, 2010.Y. Martínez et al., "First report of ‘Candidatus Liberibacter asiaticus’ associated with Huanglongbing in Cuba", Plant Pathol, vol. 58, no. 2, pp. 389, 2009."Detection of Huanglongbing (’Candidatus Liberibacter asiaticus’) in the municipality of Tizimin Yucatan Mexico. Official pest reports", Phytosanitary Alert System, Nov 2009, [online] Available: http://www.pestalert.org/oprDetail.cfm?oprID=384.L. Matos, M. E. Hilf and J. Camejo, "First report of ‘candidatus liberibacter asiaticus’ associated with citrus huanglongbing in the Dominican Republic", Plant Disease, 2009.D. D. C. Teixeira et al., "Citrus huanglongbing in São Paulo State Brazil: PCR detection of the ‘Candidatus’ Liberibacter species associated with the disease", Mol. Cell. Probes, 2005.J. M. Bové, "Huanglongbing: A destructive newly-emerging centuryold disease of citrus", Journal of Plant Pathology, 2006.E. E. Ebratt-Ravelo, L. T. Rubio-González, V. A. Costa, E. M. Zambrano-Gómez, Á. P. Castro-Ávila and M. Y. Santamaría-Galindo, "Primer Registro de Tamarixia radiata (Waterston 1922)(Hymenoptera: Eulophidae) en Colombia", Rev. Fac. Nac. Agron, vol. 64, no. 2, pp. 6141-6146, 2011.E. E. Ebratt-Ravelo, L. T. Rubio-González, V. A. Costa, Á. P. Castro-Ávila, E. M. Zambrano-Gómez and J. E. Ángel-Díaz, "Diaphorina citri (Kuwayama 1907) and Tamarixia radiata (Waterson 1922) in citrus crops of Cundinamarca Colombia", Agron. Colomb, vol. 29, no. 3, pp. 487-493, 2011.J. E. Ángel et al., "Citrus huanglongbing: Validación de PCR en tiempo real para la detección de Candidatus Liberibacter asiaticus y Candidatus Liberibacter americanus en Colombia", Agron. Colomb, 2014.J. E. Ángel et al., "Comparisión de métodos de extracción ADN para detección de huanglongbing en Colombia", Agron. Colomb, 2014."Boletín No. 8: Alerta Amarilla todos unidos contra el Huanglongbing (HLB) de los cítricos y su vector Diaphorina citri Kuwayama", Subgerencia de Protección Vegetal del ICA, 2015.A. Pourreza, W. S. Lee, R. Ehsani, J. K. Schueller and E. Raveh, "An optimum method for real-time in-field detection of Huanglongbing disease using a vision sensor", Comput. Electron. Agric, 2015.S. R. Maniyath et al., "Plant disease detection using machine learning", Proceedings - 2018 International Conference on Design Innovations for 3Cs Compute Communicate Control ICDI3C 2018, 2018.S. Futch, S. Weingarten and M. Irey, "Determining HLB Infection Levels using Multiple Survey Methods in Florida Citrus", Procedings Florida State Hortic. Soc, 2009.J. J. Garza-Saldaña, S. Varela-Fuentes and W. Gómez-Flores, "Métodos para la detección presuntiva de Huanglongbing (HLB) en cítricos", CienciaUAT, 2017.L. Emmi, M. Gonzalez-De-Soto and P. Gonzalez-De-Santos, "Configuring a fleet of ground robots for agricultural tasks", Advances in Intelligent Systems and Computing, 2014.J. M. Peña, J. Torres-Sánchez, A. Serrano-Pérez, A. I. de Castro and F. López-Granados, "Quantifying efficacy and limits of unmanned aerial vehicle (UAV) technology for weed seedling detection as affected by sensor resolution", Sensors, 2015.S. K. Sarkar, J. Das, R. Ehsani and V. Kumar, "Towards autonomous phytopathology: Outcomes and challenges of citrus greening disease detection through close-range remote sensing", 2016 IEEE International Conference on Robotics and Automation (ICRA), pp. 5143-5148, 2016.C. B. Wetterich, R. Felipe de Oliveira Neves, J. Belasque, R. Ehsani and L. G. Marcassa, "Detection of Huanglongbing in Florida using fluorescence imaging spectroscopy and machine-learning methods", Appl. Opt, 2017.C. B. Wetterich, R. Kumar, S. Sankaran, J. Belasque Junior, R. Ehsani and L. G. Marcassa, "A comparative study on application of computer vision and fluorescence imaging spectroscopy for detection of Huanglongbing citrus disease in the Usa and Brazil", J. Spectrosc, 2013.B. Sandika, S. Avil, S. Sanat and P. Srinivasu, "Random forest based classification of diseases in grapes from images captured in uncontrolled environments", International Conference on Signal Processing Proceedings ICSP, 2016.K. P. Ferentinos, "Deep learning models for plant disease detection and diagnosis", Comput. Electron. Agric, 2018.S. P. Mohanty, D. P. Hughes and M. Salathé, "Using deep learning for image-based plant disease detection", Front. Plant Sci, 2016.L. Breiman, "Random forests", Mach. Learn, 2001.M. N. Wright and A. Ziegler, "Ranger: A fast implementation of random forests for high dimensional data in C++ and R", J. Stat. Softw, 2017.A. Kataria and M. D. Singh, "A Review of Data Classification Using K-Nearest Neighbour Algorithm", Int. J. Emerg. Technol. Adv. 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