Precision agriculture in avocado production: Mapping the landscape of scientific and technological developments
- Autores:
-
Taramuel-Taramuel, Juan P.
Jiménez-Hernández, Claudia Nelcy
Barrios, Dursun
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2024
- Institución:
- Universidad Pedagógica y Tecnológica de Colombia
- Repositorio:
- RiUPTC: Repositorio Institucional UPTC
- Idioma:
- OAI Identifier:
- oai:repositorio.uptc.edu.co:001/21427
- Acceso en línea:
- https://repositorio.uptc.edu.co/handle/001/21427
https://revistas.uptc.edu.co/index.php/ciencias_horticolas/article/view/17428
- Palabra clave:
- Persea americana Mill.
Digital agriculture
Technological surveillance
Agriculture 4.0
Agricultural productivity
Avocados
Precision agriculture
Agricultura digital
Vigilancia tecnológica
Agricultura 4.0
Productividad agrícola
Aguacate
Agricultura de precisión
- Rights
- openAccess
- License
- Revista Colombiana de Ciencias Hortícolas - 2024
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Precision agriculture in avocado production: Mapping the landscape of scientific and technological developments |
| title |
Precision agriculture in avocado production: Mapping the landscape of scientific and technological developments |
| spellingShingle |
Precision agriculture in avocado production: Mapping the landscape of scientific and technological developments Persea americana Mill. Digital agriculture Technological surveillance Agriculture 4.0 Agricultural productivity Avocados Precision agriculture Agricultura digital Vigilancia tecnológica Agricultura 4.0 Productividad agrícola Aguacate Agricultura de precisión |
| title_short |
Precision agriculture in avocado production: Mapping the landscape of scientific and technological developments |
| title_full |
Precision agriculture in avocado production: Mapping the landscape of scientific and technological developments |
| title_fullStr |
Precision agriculture in avocado production: Mapping the landscape of scientific and technological developments |
| title_full_unstemmed |
Precision agriculture in avocado production: Mapping the landscape of scientific and technological developments |
| title_sort |
Precision agriculture in avocado production: Mapping the landscape of scientific and technological developments |
| dc.creator.fl_str_mv |
Taramuel-Taramuel, Juan P. Jiménez-Hernández, Claudia Nelcy Barrios, Dursun |
| dc.contributor.author.eng.fl_str_mv |
Taramuel-Taramuel, Juan P. Jiménez-Hernández, Claudia Nelcy Barrios, Dursun |
| dc.subject.none.fl_str_mv |
Persea americana Mill. Digital agriculture Technological surveillance Agriculture 4.0 Agricultural productivity Avocados Precision agriculture Agricultura digital Vigilancia tecnológica Agricultura 4.0 Productividad agrícola Aguacate Agricultura de precisión |
| topic |
Persea americana Mill. Digital agriculture Technological surveillance Agriculture 4.0 Agricultural productivity Avocados Precision agriculture Agricultura digital Vigilancia tecnológica Agricultura 4.0 Productividad agrícola Aguacate Agricultura de precisión |
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Abdulridha, J., Y. Ampatzidis, R. Ehsani, and A.I. de Castro. 2018. Evaluating the performance of spectral features and multivariate analysis tools to detect laurel wilt disease and nutritional deficiency in avocado. Comput. Electron. Agric. 155, 203-211. Doi: https://doi.org/10.1016/j.compag.2018.10.016 Abdulridha, J., R. Ehsani, A. Abd-Elrahman, and Y. Ampatzidis. 2019. A remote sensing technique for detecting laurel wilt disease in avocado in presence of other biotic and abiotic stresses. Comput. Electron. Agric. 156, 549-557. Doi: https://doi.org/10.1016/j.compag.2018.12.018 Abdulsalam, M., Z. Chekakta, N. Aouf, and M. Hogan. 2023. Fruity: a multi-modal dataset for fruit recognition and 6D-Pose estimation in precision agriculture. pp. 144-149. In: 31st Mediterranean Conference on Control and Automation. Limassol, Cyprus Doi: https://doi.org/10.1109/MED59994.2023.10185851 Antle, J.L. and S.T. Snyder. 2023. Smart sprayer for precision agriculture (EP 4223119 A1). Stout Industrial Tech Inc. https://lens.org/064-570-967-646-298 Aria, M. and C. Cuccurullo. 2017. Bibliometrix: an R-tool for comprehensive science mapping analysis. J. Informetr. 11(4), 959-975. Doi: https://doi.org/10.1016/j.joi.2017.08.007 Arias, J.S., A. Hurtado-Salazar, and N. Ceballos-Aguirre. 2021. Current overview of Hass avocado in Colombia. Challenges and opportunities: a review. Ciênc. Rural 51(8), e20200903. Doi: https://doi.org/10.1590/0103-8478cr20200903 Balafoutis, A., B. Beck, S. Fountas, J. Vangeyte, T. van der Wal, I. Soto, M. Gómez-Barbero, A. Barnes, and V. Eory. 2017. Precision agriculture technologies positively contributing to GHG emissions mitigation, farm productivity and economics. Sustainability 9(8), 1339. Doi: https://doi.org/10.3390/su9081339 Builes, S. and M. Duque. 2020. Socio-economic and technological typology of avocado cv. Hass farms from Antioquia (Colombia). Ciênc. Rural 50(7), e20190188. Doi: https://doi.org/10.1590/0103-8478cr20190188 Cáceres-Zambrano, J., C.N. Jiménez-Hernández, and D. Barrios. 2022a. Tendencias en investigación y desarrollo tecnológico en la cadena productiva de aguacate (Persea americana L.). Rev. EIA 19(38), 3826. Doi: https://doi.org/10.24050/reia.v19i38.1573 Cáceres-Zambrano, J., J.G. Ramírez-Gil, and D. Barrios. 2022b. Validating technologies and evaluating the technological level in avocado production systems: a value chain approach. Agronomy 12(12), 3130. Doi: https://doi.org/10.3390/agronomy12123130 Cisternas, I., I. Velásquez, A. Caro, and A. Rodríguez. 2020. Systematic literature review of implementations of precision agriculture. Comput. Electron. Agric. 176, 105626. Doi: https://doi.org/10.1016/j.compag.2020.105626 Cohen, H.L. 2018. Computer-implemented methods, computer readable medium and systems for a precision agriculture platform with a satellite data model (US 2018/0330487 A1). Cohen Harris Lee. https://lens.org/108-133-195-289-903 Da Silveira, F., F.H. Lermen, and F.G. Amaral. 2021. An overview of agriculture 4.0 development: systematic review of descriptions, technologies, barriers, advantages, and disadvantages. Comput. Electron. Agric. 189, 106405. Doi: https://doi.org/10.1016/j.compag.2021.106405 De Castro, A.I., R. Ehsani, R. Ploetz, J.H. Crane, and J. Abdulridha. 2015. Optimum spectral and geometric parameters for early detection of laurel wilt disease in avocado. Remote Sens. Environ. 171, 33-44. Doi: https://doi.org/10.1016/j.rse.2015.09.011 Díaz, R. 2021. Mercado mundial de aguacate: 60 años del liderazgo de México y su impacto en la próxima década. Anáhuac J. 21(2), 12-49. Doi: https://doi.org/10.36105/theanahuacjour.2021v21n2.01 Donadon, G., L.G. Bot, and B. Miolo. 2023. Sowing element for precision agricultural seeders and seeder including element of this kind (Patent US 202318183915 A). Maschio Gaspardo Spa. https://lens.org/106-345-708-638-710 DTN. 2023a. Agriculture. In: https://www.dtn.com/agriculture/; consulted: April, 2024. DTN. 2023b. ClearAg Viewer: change how you view your critical ag data. In: https://www.dtn.com/wp-content/uploads/2023/03/ss_clearagviewer.pdf; consulted: April, 2024. Duarte, P.F., M.A. Chaves, C.D. Borges, and C.R.B. Mendonça. 2016. Avocado: characteristics, health benefits and uses. Ciênc. Rural 46(4), 747-754. Doi: https://doi.org/10.1590/0103-8478cr20141516 EL Amraoui, K., M. Lghoul, A. Ezzaki, L. Masmoudi, M. Hadri, H. Elbelrhiti, and A.A. Simo. 2022. Avo-AirDB: an avocado UAV database for agricultural image segmentation and classification. Data Brief 45, 108738. Doi: https://doi.org/10.1016/j.dib.2022.108738 Erazo-Mesa, E., A. Echeverri-Sánchez, and J.G. Ramírez-Gil. 2022. Advances in Hass avocado irrigation scheduling under digital agriculture approach. Rev. Colomb. Cienc. Hortic. 16(1), e13456. Doi: https://doi.org/10.17584/rcch.2022v16i1.13456 FAO. 2022. Major tropical fruits: preliminary results 2021. Rome. FAOSTAT. 2022. Production quantity. Crops and livestock products. In: https://www.fao.org/faostat/en/#data/QCL; consulted: April, 2024. Gokcebag, S., H.S. Gecim, K. Aydogdu, G. Duztas, and H. Arslan. 2023. Precision agriculture kit (Patent TR 2021021521 A). Cankaya Univ. https://lens.org/083-142-523-856-356 Grant, D., S.T. Snyder, and J.L. Antle. 2023. Machine vision plant tracking system for precision agriculture (Patent US 202217672647 A). Stout Industrial Tech Inc. https://lens.org/081-466-413-442-10X Jeong, Y.-J., K.-I. Kim, C.-D. Lim, B.-K. Kim, Y.-B. Kim, J.-A. Shin, D.-K. Woo, D.-W. Ryoo, Y.-J. Lim, and S.-J. Ha. 2023. Apparatus and method for providing wide-area precision agriculture service based on collaboration between heterogeneous drones (Patent US 2023/0165182 A1). Electronics & Telecommunications Res Inst. https://lens.org/153-128-257-259-001 Jezewski, W. 2023. Hybrid system for monitoring and managing of crops, especially in agriculture (Patent EP 22178233 A). Promet Plast S C Elzbieta Jezewska Andrzej Jezewski. https://lens.org/032-288-688-260-288 Lacerda, R.T.O., L. Ensslin, and S.R. Ensslin. 2012. Uma análise bibliométrica da literatura sobre estratégia e avaliação de desempenho. Gest. Prod. 19(1), 59-78. Doi: https://doi.org/10.1590/S0104-530X2012000100005 Lee, C.-L., R. Strong, and K.E. Dooley. 2021. Analyzing precision agriculture adoption across the globe: a systematic review of scholarship from 1999-2020. Sustainabiblity 13(18), 10295. Doi: https://doi.org/10.3390/su131810295 Marconi, L., D. Mengoli, A. Sala, and R. Tazzari. 2023. Lifting system for a farm vehicle for precision agriculture and relative farm vehicle (Patent IT 202100023096 A). Univ Bologna Alma Mater Studiorum. https://lens.org/040-362-664-457-951 Mehmood, A., M. Ahmad, and Q.M. Ilyas. 2023. On precision agriculture: enhanced automated fruit disease identification and classification using a new ensemble classification method. Agriculture 13(2), 500. Doi: https://doi.org/10.3390/agriculture13020500 Mejiá-Cabrera, H.I., J. Flores, J. Sigueñas, V.A. Tuesta-Monteza, and M.G. Forero. 2020. Identification of Lasiodiplodia Theobromae in avocado trees through image processing and machine learning. 115102F. Proc. SPIE 11510, Applications of Digital Image Processing XLIII. Vol. 11510. Doi: https://doi.org/10.1117/12.2567322 Moreno-Bernal, P., P. Arizmendi-Peralta, J.A. Hernández-Aguilar, J. del Carmen Peralta-Abarca, and J.G. Velásquez-Aguilar. 2023. IoT platform for monitoring nutritional and weather conditions of avocado production. pp. 95-109. In: Nesmachnow, S., and L. Hernández Callejo (eds) Smart cities. ICSC-CITIES 2022.Communications in Computer and Information Science. Vol. 1706. Springer, Cham, Switzerland. Doi: https://doi.org/10.1007/978-3-031-28454-0_7 Moreno-Ortega, G., C. Pliego, D. Sarmiento, A. Barceló, and E. Martínez-Ferri. 2019. Yield and fruit quality of avocado trees under different regimes of water supply in the subtropical coast of Spain. Agric. Water Manag. 221, 192-201. Doi: https://doi.org/10.1016/j.agwat.2019.05.001 Ouzzani, M., H. Hammady, Z. Fedorowicz, and A. Elmagarmid. 2016. Rayyan-a web and mobile app for systematic reviews. Syst. Rev. 5(1), 210. Doi: https://doi.org/10.1186/s13643-016-0384-4 Page, M.J., J.E. McKenzie, P.M. Bossuyt, I. Boutron, T.C. Hoffmann, C.D. Mulrow, L. Shamseer, J.M. Tetzlaff, E.A. Akl, S.E. Brennan, R. Chou, J. Glanville, J.M. Grimshaw, A. Hróbjartsson, M.M. Lalu, T. Li, E.W. Loder, E. Mayo-Wilson, S. McDonald, L.A. McGuinness, L.A. Stewart, J. Thomas, A.C. Tricco, V.A. Welch, P. Whiting, and D. Moher. 2021. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Syst. Rev. 10(1), 89. Doi: https://doi.org/10.1186/s13643-021-01626-4 Pérez-Bueno, M.L., M. Pineda, C. Vida, D. Fernández-Ortuño, J.A. Torés, A. de Vicente, F.M. Cazorla, and M. Barón. 2019. Detection of white root rot in avocado trees by remote sensing. Plant Dis. 103(6), 1119-1125. Doi: https://doi.org/10.1094/PDIS-10-18-1778-RE Ramírez-Gil, J.G., G.O. Giraldo, and J.G. Morales. 2018. Design of electronic devices for monitoring climatic variables and development of an early warning system for the avocado wilt complex disease. Comput. Electron. Agric. 153, 134-143. Doi: https://doi.org/10.1016/j.compag.2018.08.002 Ramirez-Guerrero, T., M.I. Hernández-Pérez, M.S. Tabares, and E. Villanueva. 2023. Characterization of variables for modeling agroclimatic and phytosanitary events in agricultural crops using deep learning models. J. Phys. Conf. Ser. 2515(1), 012009. Doi: https://doi.org/10.1088/1742-6596/2515/1/012009 Rivera, G., R. Porras, R. Florencia, and J.P. Sánchez-Solís. 2023. LiDAR applications in precision agriculture for cultivating crops: a review of recent advances. Comput. Electron. Agric. 207, 107737. Doi: https://doi.org/10.1016/j.compag.2023.107737 Robson, A., M.M. Rahman, and J. Muir. 2017. Using worldview satellite imagery to map yield in avocado (Persea americana): a case study in Bundaberg, Australia. Remote Sens. 9(12), 1223. Doi: https://doi.org/10.3390/rs9121223 Rogovska, N., D.A. Laird, C.-P. Chiou, and L.J. Bond. 2019. Development of field mobile soil nitrate sensor technology to facilitate precision fertilizer management. Precision Agric. 20(1), 40-55. Doi: https://doi.org/10.1007/s11119-018-9579-0 Roy, S.K. and D. De. 2022. Genetic algorithm based Internet of precision agricultural things (IopaT) for agriculture 4.0. Internet Things 18, 100201. Doi: https://doi.org/10.1016/j.iot.2020.100201 Ruthes, S. and C.L. Silva. 2015. O uso de estudos prospectivos na análise de políticas públicas: uma análise bibliométrica. pp. 1-19. In: ALTEC - Congresso Latino-Iberoamericano de Gestão Da Tecnologia. Porto Alegre, Brazil. Saiz-Rubio, V. and F. Rovira-Más. 2020. From smart farming towards agriculture 5.0: a review on crop data management. Agronomy 10(2), 207. Doi: https://doi.org/10.3390/agronomy10020207 Salgadoe, A.S.A., A.J. Robson, D.W. Lamb, E.K. Dann, and C. Searle. 2018. Quantifying the severity of phytophthora root rot disease in avocado trees using image analysis. Remote Sens. 10(2), 226. Doi: https://doi.org/10.3390/rs10020226 Santos, S.D., A.R. Pereira-Moro, and L. Ensslin. 2015. State of the art of ergonomic costs as criterion for evaluating and improving organizational performance in industry. DYNA 82(191), 163-170. Doi: https://doi.org/10.15446/dyna.v82n191.43733 Schwartz, M., Y. Maldonado, L. Luchsinger, L.A. Lizana, and W. Kern. 2018. Competitive Peruvian and Chilean avocado export profile. Acta Hortic. 1194, 1079-1084. Doi: https://doi.org/10.17660/ActaHortic.2018.1194.154 Scimago. 2023. Scimago Journal & Country Rank. Scimago Journal & Country Rank. https://www.scimagojr.com/; consulted: October, 2023. Staples, T.E., R.C. Miller, M. Hoosein, and V.M. Finn. 2019. System and method for prescribing fertilizer application rates for spatial distribution of a product (Patent US 201616081327 A; US 201662303856 P; CA 2016050323 W). Nutrien Ag Solutions Canada Inc. https://lens.org/125-080-646-990-003 The Climate Corporation. 2023. Digital farming’s leading software platform.In: https://climate.com/; consulted: October, 2023. Torres-Madronero, M.C., T. Rondón, R. Franco, M. Casamitjana, and J. Trochez. 2023. Spectral characterization of avocado Persea americana Mill. cv. Hass using spectrometry and imagery from the visible to near-infrared range. TecnoLógicas 26(56), e2567. Doi: https://doi.org/10.22430/22565337.2567 Tran, V.L., T.N.C. Doan, F. Ferrero, T.L Huy, and N. Le-Thanh. 2023. The novel combination of nano vector network analyzer and machine learning for fruit identification and ripeness grading. Sensors 23(2), 952. Doi: https://doi.org/10.3390/s23020952 Tu, Y.-H., K. Johansen, S. Phinn, and A. Robson. 2019. Measuring canopy structure and condition using multi-spectral UAS imagery in a horticultural environment. Remote Sens. 11(3), 269. Doi. https://doi.org/10.3390/rs11030269 Tu, Y.-H., S. Phinn, K. Johansen, and A. Robson. 2018. Assessing radiometric correction approaches for multi-spectral UAS imagery for horticultural applications. Remote Sens. 10(11), 1684. Doi: https://doi.org/10.3390/rs10111684 USPTO. 2023. USPTO trademark & patent filings: stout industrial technology. In: https://uspto.report/company/Stout-Industrial-Technology-Inc; consulted: October, 2023. Van Eck, N.J., and L. Waltman. 2014. Visualizing bibliometric networks. pp. 285-320. In: Ding, Y., R. Rousseau, and D. Wolfram (eds.). Measuring scholarly impact: methods and practice. Springer, Cham, Switzerland. Doi: https://doi.org/10.1007/978-3-319-10377-8_13 Vasconez, J.P., J. Delpiano, S. Vougioukas, and F. Auat Cheein. 2020. Comparison of convolutional neural networks in fruit detection and counting: a comprehensive evaluation. Comput. Electron. Agric. 173, 105348. Doi: https://doi.org/10.1016/j.compag.2020.105348 Veneros, J., L. García, E. Morales, V. Gómez, M. Torres, and F. López-Morales. 2020. Aplicación de sensores remotos para el análisis de cobertura vegetal y cuerpos de agua. Idesia 38(4), 99-107. Doi: https://doi.org/10.4067/S0718-34292020000400099 White, R.D. 2015. Iteris greenlights ways to better account for its revenue. In: Los Angeles Times, https://www.latimes.com/business/la-fi-stock-spotlight-iteris-20150504-story.html; consulted: October, 2023. Yábar-Gamarra, D., D. Rosales-Gurmendi, R. Manzanares-Grados, K.I. Curasi-Anchayhua, J.S. Bulnes, and R.R. Clemente. 2023. Design of a radio frequency robot for the analysis of farmlands of avocado crops in Peru. 601. In: Proc. 21th LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI 2023). Doi: https://doi.org/10.18687/LACCEI2023.1.1.601 Zhang, N., M. Wang, and N. Wang. 2002. Precision agriculture-a worldwide overview. Comput. Electron. Agric. 36(2-3), 113-132. Doi: https://doi.org/10.1016/S0168-1699(02)00096-0 Zude-Sasse, M., S. Fountas, T.A. Gemtos, and N. Abu-Khalaf. 2016. Applications of precision agriculture in horticultural crops. Eur. J. Hortic. Sci. 81(2), 78-90. Doi: https://doi.org/10.17660/eJHS.2016/81.2.2 |
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Taramuel-Taramuel, Juan P.Jiménez-Hernández, Claudia NelcyBarrios, Dursun2024-05-01 00:00:002026-04-16T17:45:21Z2024-05-01 00:00:002024-05-012011-2173https://repositorio.uptc.edu.co/handle/001/214272422-3719https://revistas.uptc.edu.co/index.php/ciencias_horticolas/article/view/17428text/xmlapplication/pdfSociedad Colombiana de Ciencias Hortícolas-SCCH and Universidad Pedagógica y Tecnológica de Colombia-UPTCRevista Colombiana de Ciencias Hortícolas - 2024http://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccessThis work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.http://purl.org/coar/access_right/c_abf2https://revistas.uptc.edu.co/index.php/ciencias_horticolas/article/view/17428Persea americana Mill.Digital agricultureTechnological surveillanceAgriculture 4.0Agricultural productivityAvocadosPrecision agricultureAgricultura digitalVigilancia tecnológicaAgricultura 4.0Productividad agrícolaAguacateAgricultura de precisiónPrecision agriculture in avocado production: Mapping the landscape of scientific and technological developmentsArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleJournal articleinfo:eu-repo/semantics/publishedVersionTexthttp://purl.org/coar/version/c_970fb48d4fbd8a85Abdulridha, J., Y. Ampatzidis, R. Ehsani, and A.I. de Castro. 2018. Evaluating the performance of spectral features and multivariate analysis tools to detect laurel wilt disease and nutritional deficiency in avocado. Comput. Electron. Agric. 155, 203-211. Doi: https://doi.org/10.1016/j.compag.2018.10.016Abdulridha, J., R. Ehsani, A. Abd-Elrahman, and Y. Ampatzidis. 2019. A remote sensing technique for detecting laurel wilt disease in avocado in presence of other biotic and abiotic stresses. Comput. Electron. Agric. 156, 549-557. Doi: https://doi.org/10.1016/j.compag.2018.12.018Abdulsalam, M., Z. Chekakta, N. Aouf, and M. Hogan. 2023. Fruity: a multi-modal dataset for fruit recognition and 6D-Pose estimation in precision agriculture. pp. 144-149. In: 31st Mediterranean Conference on Control and Automation. Limassol, Cyprus Doi: https://doi.org/10.1109/MED59994.2023.10185851Antle, J.L. and S.T. Snyder. 2023. Smart sprayer for precision agriculture (EP 4223119 A1). Stout Industrial Tech Inc. https://lens.org/064-570-967-646-298Aria, M. and C. Cuccurullo. 2017. Bibliometrix: an R-tool for comprehensive science mapping analysis. J. Informetr. 11(4), 959-975. Doi: https://doi.org/10.1016/j.joi.2017.08.007Arias, J.S., A. Hurtado-Salazar, and N. Ceballos-Aguirre. 2021. Current overview of Hass avocado in Colombia. Challenges and opportunities: a review. Ciênc. Rural 51(8), e20200903. Doi: https://doi.org/10.1590/0103-8478cr20200903Balafoutis, A., B. Beck, S. Fountas, J. Vangeyte, T. van der Wal, I. Soto, M. Gómez-Barbero, A. Barnes, and V. Eory. 2017. Precision agriculture technologies positively contributing to GHG emissions mitigation, farm productivity and economics. Sustainability 9(8), 1339. Doi: https://doi.org/10.3390/su9081339Builes, S. and M. Duque. 2020. Socio-economic and technological typology of avocado cv. Hass farms from Antioquia (Colombia). Ciênc. Rural 50(7), e20190188. Doi: https://doi.org/10.1590/0103-8478cr20190188Cáceres-Zambrano, J., C.N. Jiménez-Hernández, and D. Barrios. 2022a. Tendencias en investigación y desarrollo tecnológico en la cadena productiva de aguacate (Persea americana L.). Rev. EIA 19(38), 3826. Doi: https://doi.org/10.24050/reia.v19i38.1573Cáceres-Zambrano, J., J.G. Ramírez-Gil, and D. Barrios. 2022b. Validating technologies and evaluating the technological level in avocado production systems: a value chain approach. Agronomy 12(12), 3130. Doi: https://doi.org/10.3390/agronomy12123130Cisternas, I., I. Velásquez, A. Caro, and A. Rodríguez. 2020. Systematic literature review of implementations of precision agriculture. Comput. Electron. Agric. 176, 105626. Doi: https://doi.org/10.1016/j.compag.2020.105626Cohen, H.L. 2018. Computer-implemented methods, computer readable medium and systems for a precision agriculture platform with a satellite data model (US 2018/0330487 A1). Cohen Harris Lee. https://lens.org/108-133-195-289-903Da Silveira, F., F.H. Lermen, and F.G. Amaral. 2021. An overview of agriculture 4.0 development: systematic review of descriptions, technologies, barriers, advantages, and disadvantages. Comput. Electron. Agric. 189, 106405. Doi: https://doi.org/10.1016/j.compag.2021.106405De Castro, A.I., R. Ehsani, R. Ploetz, J.H. Crane, and J. Abdulridha. 2015. Optimum spectral and geometric parameters for early detection of laurel wilt disease in avocado. Remote Sens. Environ. 171, 33-44. Doi: https://doi.org/10.1016/j.rse.2015.09.011Díaz, R. 2021. Mercado mundial de aguacate: 60 años del liderazgo de México y su impacto en la próxima década. Anáhuac J. 21(2), 12-49. Doi: https://doi.org/10.36105/theanahuacjour.2021v21n2.01Donadon, G., L.G. Bot, and B. Miolo. 2023. Sowing element for precision agricultural seeders and seeder including element of this kind (Patent US 202318183915 A). Maschio Gaspardo Spa. https://lens.org/106-345-708-638-710DTN. 2023a. Agriculture. In: https://www.dtn.com/agriculture/; consulted: April, 2024.DTN. 2023b. ClearAg Viewer: change how you view your critical ag data. In: https://www.dtn.com/wp-content/uploads/2023/03/ss_clearagviewer.pdf; consulted: April, 2024.Duarte, P.F., M.A. Chaves, C.D. Borges, and C.R.B. Mendonça. 2016. Avocado: characteristics, health benefits and uses. Ciênc. Rural 46(4), 747-754. Doi: https://doi.org/10.1590/0103-8478cr20141516EL Amraoui, K., M. Lghoul, A. Ezzaki, L. Masmoudi, M. Hadri, H. Elbelrhiti, and A.A. Simo. 2022. Avo-AirDB: an avocado UAV database for agricultural image segmentation and classification. Data Brief 45, 108738. Doi: https://doi.org/10.1016/j.dib.2022.108738Erazo-Mesa, E., A. Echeverri-Sánchez, and J.G. Ramírez-Gil. 2022. Advances in Hass avocado irrigation scheduling under digital agriculture approach. Rev. Colomb. Cienc. Hortic. 16(1), e13456. Doi: https://doi.org/10.17584/rcch.2022v16i1.13456FAO. 2022. Major tropical fruits: preliminary results 2021. Rome.FAOSTAT. 2022. Production quantity. Crops and livestock products. In: https://www.fao.org/faostat/en/#data/QCL; consulted: April, 2024.Gokcebag, S., H.S. Gecim, K. Aydogdu, G. Duztas, and H. Arslan. 2023. Precision agriculture kit (Patent TR 2021021521 A). Cankaya Univ. https://lens.org/083-142-523-856-356Grant, D., S.T. Snyder, and J.L. Antle. 2023. Machine vision plant tracking system for precision agriculture (Patent US 202217672647 A). Stout Industrial Tech Inc. https://lens.org/081-466-413-442-10XJeong, Y.-J., K.-I. Kim, C.-D. Lim, B.-K. Kim, Y.-B. Kim, J.-A. Shin, D.-K. Woo, D.-W. Ryoo, Y.-J. Lim, and S.-J. Ha. 2023. Apparatus and method for providing wide-area precision agriculture service based on collaboration between heterogeneous drones (Patent US 2023/0165182 A1). Electronics & Telecommunications Res Inst. https://lens.org/153-128-257-259-001Jezewski, W. 2023. Hybrid system for monitoring and managing of crops, especially in agriculture (Patent EP 22178233 A). Promet Plast S C Elzbieta Jezewska Andrzej Jezewski. https://lens.org/032-288-688-260-288Lacerda, R.T.O., L. Ensslin, and S.R. Ensslin. 2012. Uma análise bibliométrica da literatura sobre estratégia e avaliação de desempenho. Gest. Prod. 19(1), 59-78. Doi: https://doi.org/10.1590/S0104-530X2012000100005Lee, C.-L., R. Strong, and K.E. Dooley. 2021. Analyzing precision agriculture adoption across the globe: a systematic review of scholarship from 1999-2020. Sustainabiblity 13(18), 10295. Doi: https://doi.org/10.3390/su131810295Marconi, L., D. Mengoli, A. Sala, and R. Tazzari. 2023. Lifting system for a farm vehicle for precision agriculture and relative farm vehicle (Patent IT 202100023096 A). Univ Bologna Alma Mater Studiorum. https://lens.org/040-362-664-457-951Mehmood, A., M. Ahmad, and Q.M. Ilyas. 2023. On precision agriculture: enhanced automated fruit disease identification and classification using a new ensemble classification method. Agriculture 13(2), 500. Doi: https://doi.org/10.3390/agriculture13020500Mejiá-Cabrera, H.I., J. Flores, J. Sigueñas, V.A. Tuesta-Monteza, and M.G. Forero. 2020. Identification of Lasiodiplodia Theobromae in avocado trees through image processing and machine learning. 115102F. Proc. SPIE 11510, Applications of Digital Image Processing XLIII. Vol. 11510. Doi: https://doi.org/10.1117/12.2567322Moreno-Bernal, P., P. Arizmendi-Peralta, J.A. Hernández-Aguilar, J. del Carmen Peralta-Abarca, and J.G. Velásquez-Aguilar. 2023. IoT platform for monitoring nutritional and weather conditions of avocado production. pp. 95-109. In: Nesmachnow, S., and L. Hernández Callejo (eds) Smart cities. ICSC-CITIES 2022.Communications in Computer and Information Science. Vol. 1706. Springer, Cham, Switzerland. Doi: https://doi.org/10.1007/978-3-031-28454-0_7Moreno-Ortega, G., C. Pliego, D. Sarmiento, A. Barceló, and E. Martínez-Ferri. 2019. Yield and fruit quality of avocado trees under different regimes of water supply in the subtropical coast of Spain. Agric. Water Manag. 221, 192-201. Doi: https://doi.org/10.1016/j.agwat.2019.05.001Ouzzani, M., H. Hammady, Z. Fedorowicz, and A. Elmagarmid. 2016. Rayyan-a web and mobile app for systematic reviews. Syst. Rev. 5(1), 210. Doi: https://doi.org/10.1186/s13643-016-0384-4Page, M.J., J.E. McKenzie, P.M. Bossuyt, I. Boutron, T.C. Hoffmann, C.D. Mulrow, L. Shamseer, J.M. Tetzlaff, E.A. Akl, S.E. Brennan, R. Chou, J. Glanville, J.M. Grimshaw, A. Hróbjartsson, M.M. Lalu, T. Li, E.W. Loder, E. Mayo-Wilson, S. McDonald, L.A. McGuinness, L.A. Stewart, J. Thomas, A.C. Tricco, V.A. Welch, P. Whiting, and D. Moher. 2021. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Syst. Rev. 10(1), 89. Doi: https://doi.org/10.1186/s13643-021-01626-4Pérez-Bueno, M.L., M. Pineda, C. Vida, D. Fernández-Ortuño, J.A. Torés, A. de Vicente, F.M. Cazorla, and M. Barón. 2019. Detection of white root rot in avocado trees by remote sensing. Plant Dis. 103(6), 1119-1125. Doi: https://doi.org/10.1094/PDIS-10-18-1778-RERamírez-Gil, J.G., G.O. Giraldo, and J.G. Morales. 2018. Design of electronic devices for monitoring climatic variables and development of an early warning system for the avocado wilt complex disease. Comput. Electron. Agric. 153, 134-143. Doi: https://doi.org/10.1016/j.compag.2018.08.002Ramirez-Guerrero, T., M.I. Hernández-Pérez, M.S. Tabares, and E. Villanueva. 2023. Characterization of variables for modeling agroclimatic and phytosanitary events in agricultural crops using deep learning models. J. Phys. Conf. Ser. 2515(1), 012009. Doi: https://doi.org/10.1088/1742-6596/2515/1/012009Rivera, G., R. Porras, R. Florencia, and J.P. Sánchez-Solís. 2023. LiDAR applications in precision agriculture for cultivating crops: a review of recent advances. Comput. Electron. Agric. 207, 107737. Doi: https://doi.org/10.1016/j.compag.2023.107737Robson, A., M.M. Rahman, and J. Muir. 2017. Using worldview satellite imagery to map yield in avocado (Persea americana): a case study in Bundaberg, Australia. Remote Sens. 9(12), 1223. Doi: https://doi.org/10.3390/rs9121223Rogovska, N., D.A. Laird, C.-P. Chiou, and L.J. Bond. 2019. Development of field mobile soil nitrate sensor technology to facilitate precision fertilizer management. Precision Agric. 20(1), 40-55. Doi: https://doi.org/10.1007/s11119-018-9579-0Roy, S.K. and D. De. 2022. Genetic algorithm based Internet of precision agricultural things (IopaT) for agriculture 4.0. Internet Things 18, 100201. Doi: https://doi.org/10.1016/j.iot.2020.100201Ruthes, S. and C.L. Silva. 2015. O uso de estudos prospectivos na análise de políticas públicas: uma análise bibliométrica. pp. 1-19. In: ALTEC - Congresso Latino-Iberoamericano de Gestão Da Tecnologia. Porto Alegre, Brazil.Saiz-Rubio, V. and F. Rovira-Más. 2020. From smart farming towards agriculture 5.0: a review on crop data management. Agronomy 10(2), 207. Doi: https://doi.org/10.3390/agronomy10020207Salgadoe, A.S.A., A.J. Robson, D.W. Lamb, E.K. Dann, and C. Searle. 2018. Quantifying the severity of phytophthora root rot disease in avocado trees using image analysis. Remote Sens. 10(2), 226. Doi: https://doi.org/10.3390/rs10020226Santos, S.D., A.R. Pereira-Moro, and L. Ensslin. 2015. State of the art of ergonomic costs as criterion for evaluating and improving organizational performance in industry. DYNA 82(191), 163-170. Doi: https://doi.org/10.15446/dyna.v82n191.43733Schwartz, M., Y. Maldonado, L. Luchsinger, L.A. Lizana, and W. Kern. 2018. Competitive Peruvian and Chilean avocado export profile. Acta Hortic. 1194, 1079-1084. Doi: https://doi.org/10.17660/ActaHortic.2018.1194.154Scimago. 2023. Scimago Journal & Country Rank. Scimago Journal & Country Rank. https://www.scimagojr.com/; consulted: October, 2023.Staples, T.E., R.C. Miller, M. Hoosein, and V.M. Finn. 2019. System and method for prescribing fertilizer application rates for spatial distribution of a product (Patent US 201616081327 A; US 201662303856 P; CA 2016050323 W). Nutrien Ag Solutions Canada Inc. https://lens.org/125-080-646-990-003The Climate Corporation. 2023. Digital farming’s leading software platform.In: https://climate.com/; consulted: October, 2023.Torres-Madronero, M.C., T. Rondón, R. Franco, M. Casamitjana, and J. Trochez. 2023. Spectral characterization of avocado Persea americana Mill. cv. Hass using spectrometry and imagery from the visible to near-infrared range. TecnoLógicas 26(56), e2567. Doi: https://doi.org/10.22430/22565337.2567Tran, V.L., T.N.C. Doan, F. Ferrero, T.L Huy, and N. Le-Thanh. 2023. The novel combination of nano vector network analyzer and machine learning for fruit identification and ripeness grading. Sensors 23(2), 952. Doi: https://doi.org/10.3390/s23020952Tu, Y.-H., K. Johansen, S. Phinn, and A. Robson. 2019. Measuring canopy structure and condition using multi-spectral UAS imagery in a horticultural environment. Remote Sens. 11(3), 269. Doi. https://doi.org/10.3390/rs11030269Tu, Y.-H., S. Phinn, K. Johansen, and A. Robson. 2018. Assessing radiometric correction approaches for multi-spectral UAS imagery for horticultural applications. Remote Sens. 10(11), 1684. Doi: https://doi.org/10.3390/rs10111684USPTO. 2023. USPTO trademark & patent filings: stout industrial technology. In: https://uspto.report/company/Stout-Industrial-Technology-Inc; consulted: October, 2023.Van Eck, N.J., and L. Waltman. 2014. Visualizing bibliometric networks. pp. 285-320. In: Ding, Y., R. Rousseau, and D. Wolfram (eds.). Measuring scholarly impact: methods and practice. Springer, Cham, Switzerland. Doi: https://doi.org/10.1007/978-3-319-10377-8_13Vasconez, J.P., J. Delpiano, S. Vougioukas, and F. Auat Cheein. 2020. Comparison of convolutional neural networks in fruit detection and counting: a comprehensive evaluation. Comput. Electron. Agric. 173, 105348. Doi: https://doi.org/10.1016/j.compag.2020.105348Veneros, J., L. García, E. Morales, V. Gómez, M. Torres, and F. López-Morales. 2020. Aplicación de sensores remotos para el análisis de cobertura vegetal y cuerpos de agua. Idesia 38(4), 99-107. Doi: https://doi.org/10.4067/S0718-34292020000400099White, R.D. 2015. Iteris greenlights ways to better account for its revenue. In: Los Angeles Times, https://www.latimes.com/business/la-fi-stock-spotlight-iteris-20150504-story.html; consulted: October, 2023.Yábar-Gamarra, D., D. Rosales-Gurmendi, R. Manzanares-Grados, K.I. Curasi-Anchayhua, J.S. Bulnes, and R.R. Clemente. 2023. Design of a radio frequency robot for the analysis of farmlands of avocado crops in Peru. 601. In: Proc. 21th LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI 2023). Doi: https://doi.org/10.18687/LACCEI2023.1.1.601Zhang, N., M. Wang, and N. Wang. 2002. Precision agriculture-a worldwide overview. Comput. Electron. Agric. 36(2-3), 113-132. Doi: https://doi.org/10.1016/S0168-1699(02)00096-0Zude-Sasse, M., S. Fountas, T.A. Gemtos, and N. Abu-Khalaf. 2016. Applications of precision agriculture in horticultural crops. Eur. J. Hortic. Sci. 81(2), 78-90. Doi: https://doi.org/10.17660/eJHS.2016/81.2.2e174282e1742818Revista Colombiana de Ciencias Hortícolashttps://revistas.uptc.edu.co/index.php/ciencias_horticolas/article/download/17428/14876https://revistas.uptc.edu.co/index.php/ciencias_horticolas/article/download/17428/14504https://revistas.uptc.edu.co/index.php/ciencias_horticolas/article/download/17428/14148Núm. 2 , Año 2024 : Horticultural Excellence: Innovations in Quality, Technology, and SustainabilityPublicationOREORE.xmltext/xml2876https://repositorio.uptc.edu.co/bitstreams/5d453b9c-2a1c-4dba-bdfb-567a3642606f/download12d5dacf5571861ccce7f0a86506f4b3MD51falseAnonymousREAD001/21427oai:repositorio.uptc.edu.co:001/214272026-09-29 21:33:29.219http://creativecommons.org/licenses/by-nc-sa/4.0metadata.onlyhttps://repositorio.uptc.edu.coRepositorio Institucional UPTCbdigital@metabiblioteca.com |
