Sistemas de Información enfocados en tecnologías de agricultura de precisión y aplicables a la caña de azúcar, una revisión
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- Enviado: julio 28, 2015
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Publicado: noviembre 7, 2015
Resumen
Los cultivos de caña de azúcar son una de las principales actividades económicas en Colombia, por ende son esenciales para el desarrollo agrícola del país. Además, las Tecnologías de la Información y las Comunicaciones (TIC) se han empezado a utilizar e implementar en todo el ciclo de vida del cultivo. Consiguientemente, las TIC son importantes al momento de definir sistemas basados en Agricultura de Precisión (AP), capaces de incrementar el rendimiento del cultivo y optimizar el uso de recursos económicos y de fertilizantes, entre otras funciones. Este artículo presenta una revisión acerca de sistemas de información basados en AP y aplicables a cultivos de caña de azúcar, haciendo énfasis en las tecnologías utilizadas, la gestión de datos y sus arquitecturas. Asimismo, se presenta la propuesta de los autores: un sistema de información integral de tres capas basado en AP, capaz de facilitar la optimización en distintas etapas del ciclo de vida de la caña de azúcar. El artículo concluye describiendo el trabajo futuro y el desarrollo de la implementación del sistema propuesto.Referencias
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[3] R. Bramley, “Lessons from nearly 20 years of Precision Agriculture research, development, and adoption as a guide to its appropriate application,” Crop. Pasture Science, vol. 60, n.° 3, pp. 197–217, 2009.
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[12] D. López et al., “Sistema integrado para recomendar dosis de fertilización en caña de azúcar (SIRDF),” Terra Latinoamericana, vol. 20, n.° 3, pp. 347-358, 2002.
[13] B. Stray, J. van Vuuren, y C. Bezuidenhout, “An optimisation-based seasonal sugarcane harvest scheduling decision support system for commercial growers in South Africa,” Computers and Electronics in Agriculture, vol. 83, pp. 21–31, 2012.
[14] C. Zhang, D. Walters, y J. M. Kovacs, “Applications of Low Altitude Remote Sensing in Agriculture upon Farmers’ Requests – A Case Study in Northeastern Ontario, Canada,” PLoS ONE, vol. 9, n.° 11, pp. 1-9, 2014.
[15] G. López, “Diseño de un programa de ortorectificación y georreferenciación de imágenes aéreas aplicadas a campos de caña de azúcar,” Pontificia Universidad Católica del Perú, Lima, Perú, 2014.
[16] G. Schneider, A. Hadad, y A. Kemerer, “Implementación de un software para el análisis de imágenes aéreas multiespectrales de caña de azúcar,” Ventana Informática, vol. 28, n.° 1, pp. 13–29, 2013.
[17] E. Hunt, C. Daughtry, S. Mirsky, y W. Hively, “Remote Sensing With Simulated Unmanned Aircraft Imagery for Precision Agriculture Applications,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, n.° 11, pp. 4566–4571, 2014.
[18] F. Urbano, “Redes de sensores inalámbricos aplicadas a optimización en agricultura de precisión para cultivos de café en Colombia,” Journal de Ciencia e Ingeniería, vol. 5, n.° 1, pp. 46–52, 2013.
[19] K. Sudduth, S. Drummond, y N. Kitchen, “Accuracy issues in electromagnetic induction sensing of soil electrical conductivity for precision agriculture,” Computers and Electronics in Agriculture, vol. 31, n.° 3, pp. 239–264, 2001.
[20] N. Nawi, G. Chen, y T. Jensen, “In-field measurement and sampling technologies for monitoring quality in the sugarcane industry: a review,” Precision Agriculture, vol. 15, n.° 6, pp. 684–703, 2014.
[21] R. Price, R. Johnson, R. Viator, J. Larsen, y A. Peters, “Fiber Optic Yield Monitor for a Sugarcane Harvester,” Transactions of the ASABE, vol. 54, n.° 1, pp. 31–39, 2011.
[22] J. Molin, F. Frasson, L. Amaral, F. Povh, y J. Salvi, “Capability of an optical sensor in verifying the sugarcane response to nitrogen rates,” Revista Brasileira de Engenharia Agrícola e Ambiental, vol. 14, n.° 12, pp. 1345–1349, 2010.
[23] Z. de Souza et al., “Analyze the soil attributes and sugarcane yield culture with the use of geostatistics and decision trees,” Ciência Rural, vol. 40, n.° 4, pp. 840–847, 2010.
[24] J. Carbonell, “Experiencia del sector cañicultor en agricultura específica por sitio,” Palmas, vol. 29, n.° 2, pp. 65–70, 2008.
[25] J. Markley y J. Hughes, “Understanding the Barriers to the Implementation of Precision Agriculture in the Central Region,” presentado en 35th Annual Conference of the Australian Society of Sugar Cane Technologists, Townsville, Australia, 2013.
[26] J. Serrano, J. Peça, J. Silva, y S. Shahidian, “Aplicação de fertilizantes: tecnologia, eficiência energética e ambiente”. Revista de Ciências Agrárias, vol. 37, n.° 3, pp. 270–279, 2014.
[27] J. Ye, B. Chen, Q. Liu, y Y. Fang, “A precision agriculture management system based on Internet of Things and WebGIS,” presentado en 2013 21st International Conference on Geoinformatics (GEOINFORMATICS), Kaifeng, China, 2013.
[28] B. Keating y R. McCown, “Advances in farming systems analysis and intervention,” Agricultural Systems, vol. 70, n.° 2–3, pp. 555–579, 2001.
[29] C. Driemeier et al., “Data Analysis Workflow for Experiments in Sugarcane Precision Agriculture,” in 2014 IEEE 10th International Conference on e-Science (e-Science), Guarujá, Brasil, 2014.
[30] Y. Wang, Y. Wang, X. Qi, y L. Xu, “OPAIMS: open architecture precision agriculture information monitoring system,” presentado en Proceedings of the 2009 International conference on Compilers, architecture, and synthesis for embedded systems, Grenoble, Francia, 2009.
[2] C. Silva, M. Moraes, y J. Molin, “Adoption and use of precision agriculture technologies in the sugarcane industry of São Paulo state, Brazil,” Precision Agriculture, vol. 12, n.° 1, pp. 67–81, 2010.
[3] R. Bramley, “Lessons from nearly 20 years of Precision Agriculture research, development, and adoption as a guide to its appropriate application,” Crop. Pasture Science, vol. 60, n.° 3, pp. 197–217, 2009.
[4] R. Plumb, “Precision agriculture in the 21st century: geospatial and information technologies in crop management,” Pest Management Science, vol. 56, n.° 8, pp. 723–723, 2000.
[5] R. Grisso, M. Alley, P. McClellan, D. Brann, y S. Donohue, “Precision Farming. A Comprehensive Approach,” Virginia Cooperative Extension, Publication 442-500, Virginia State University, 2009.
[6] A. Dobermann, S. Blackmore, S. Cook, y V. Adamchuk, “Precision Farming: Challenges and Future Directions,” presentado en Proceedings of the 4th International Crop Science Congress, Brisbane, Australia, 2004.
[7] P. Tozer, “Uncertainty and investment in precision agriculture – Is it worth the money?” Agricultural Systems, vol. 100, n.° 1–3, pp. 80–87, 2009.
[8] M. Rilwani y J. Oghenereemusua, “Geoinformatics in Agricultural Development: Challenges and Prospects in Nigeria,” Journal of Social Sciences, vol. 21, n.° 1, pp. 49–57, 2009.
[9] B. Kitchenham y S. Charters, “Guidelines for performing Systematic Literature Reviews in Software Engineering,” Keele University and Durham University Joint Report, UK, EBSE 2007-001, 2007.
[10] J. Cock et al., “Crop management based on field observations: Case studies in sugarcane and coffee,” Agricultural Systems, vol. 104, n.° 9, pp. 755–769, 2011.
[11] J. Demattê, L. Demattê, E. Alves, R. Negrão, y J. L. Morelli, “Precision agriculture for sugarcane management: a strategy applied for brazilian conditions,” Acta Scientiarum. Agronomy, vol. 36, n.° 1, pp. 111–117, 2014.
[12] D. López et al., “Sistema integrado para recomendar dosis de fertilización en caña de azúcar (SIRDF),” Terra Latinoamericana, vol. 20, n.° 3, pp. 347-358, 2002.
[13] B. Stray, J. van Vuuren, y C. Bezuidenhout, “An optimisation-based seasonal sugarcane harvest scheduling decision support system for commercial growers in South Africa,” Computers and Electronics in Agriculture, vol. 83, pp. 21–31, 2012.
[14] C. Zhang, D. Walters, y J. M. Kovacs, “Applications of Low Altitude Remote Sensing in Agriculture upon Farmers’ Requests – A Case Study in Northeastern Ontario, Canada,” PLoS ONE, vol. 9, n.° 11, pp. 1-9, 2014.
[15] G. López, “Diseño de un programa de ortorectificación y georreferenciación de imágenes aéreas aplicadas a campos de caña de azúcar,” Pontificia Universidad Católica del Perú, Lima, Perú, 2014.
[16] G. Schneider, A. Hadad, y A. Kemerer, “Implementación de un software para el análisis de imágenes aéreas multiespectrales de caña de azúcar,” Ventana Informática, vol. 28, n.° 1, pp. 13–29, 2013.
[17] E. Hunt, C. Daughtry, S. Mirsky, y W. Hively, “Remote Sensing With Simulated Unmanned Aircraft Imagery for Precision Agriculture Applications,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, n.° 11, pp. 4566–4571, 2014.
[18] F. Urbano, “Redes de sensores inalámbricos aplicadas a optimización en agricultura de precisión para cultivos de café en Colombia,” Journal de Ciencia e Ingeniería, vol. 5, n.° 1, pp. 46–52, 2013.
[19] K. Sudduth, S. Drummond, y N. Kitchen, “Accuracy issues in electromagnetic induction sensing of soil electrical conductivity for precision agriculture,” Computers and Electronics in Agriculture, vol. 31, n.° 3, pp. 239–264, 2001.
[20] N. Nawi, G. Chen, y T. Jensen, “In-field measurement and sampling technologies for monitoring quality in the sugarcane industry: a review,” Precision Agriculture, vol. 15, n.° 6, pp. 684–703, 2014.
[21] R. Price, R. Johnson, R. Viator, J. Larsen, y A. Peters, “Fiber Optic Yield Monitor for a Sugarcane Harvester,” Transactions of the ASABE, vol. 54, n.° 1, pp. 31–39, 2011.
[22] J. Molin, F. Frasson, L. Amaral, F. Povh, y J. Salvi, “Capability of an optical sensor in verifying the sugarcane response to nitrogen rates,” Revista Brasileira de Engenharia Agrícola e Ambiental, vol. 14, n.° 12, pp. 1345–1349, 2010.
[23] Z. de Souza et al., “Analyze the soil attributes and sugarcane yield culture with the use of geostatistics and decision trees,” Ciência Rural, vol. 40, n.° 4, pp. 840–847, 2010.
[24] J. Carbonell, “Experiencia del sector cañicultor en agricultura específica por sitio,” Palmas, vol. 29, n.° 2, pp. 65–70, 2008.
[25] J. Markley y J. Hughes, “Understanding the Barriers to the Implementation of Precision Agriculture in the Central Region,” presentado en 35th Annual Conference of the Australian Society of Sugar Cane Technologists, Townsville, Australia, 2013.
[26] J. Serrano, J. Peça, J. Silva, y S. Shahidian, “Aplicação de fertilizantes: tecnologia, eficiência energética e ambiente”. Revista de Ciências Agrárias, vol. 37, n.° 3, pp. 270–279, 2014.
[27] J. Ye, B. Chen, Q. Liu, y Y. Fang, “A precision agriculture management system based on Internet of Things and WebGIS,” presentado en 2013 21st International Conference on Geoinformatics (GEOINFORMATICS), Kaifeng, China, 2013.
[28] B. Keating y R. McCown, “Advances in farming systems analysis and intervention,” Agricultural Systems, vol. 70, n.° 2–3, pp. 555–579, 2001.
[29] C. Driemeier et al., “Data Analysis Workflow for Experiments in Sugarcane Precision Agriculture,” in 2014 IEEE 10th International Conference on e-Science (e-Science), Guarujá, Brasil, 2014.
[30] Y. Wang, Y. Wang, X. Qi, y L. Xu, “OPAIMS: open architecture precision agriculture information monitoring system,” presentado en Proceedings of the 2009 International conference on Compilers, architecture, and synthesis for embedded systems, Grenoble, Francia, 2009.
Cómo citar
Orozco Sarasti, O. A., & Llano Ramírez, G. (2015). Sistemas de Información enfocados en tecnologías de agricultura de precisión y aplicables a la caña de azúcar, una revisión. Revista Ingenierías Universidad De Medellín, 15(28), 103-124. https://doi.org/10.22395/rium.v15n28a6
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