Avances y perspectivas de la agricultura de precisión para la sostenibilidad agrícola
Resumen
La agricultura de precisión es una práctica agrícola que utiliza tecnologías avanzadas, como sensores remotos, sistemas de riego inteligente y nanotecnología, para optimizar la gestión de los recursos naturales y aumentar la productividad agrícola. Esta disciplina surge como respuesta a los desafíos contemporáneos de la agricultura, como el aumento de la demanda de alimentos, la escasez de recursos y los impactos ambientales. Mediante la recopilación, análisis y aplicación de grandes volúmenes de datos en tiempo real, la agricultura de precisión permite a los agricultores tomar decisiones informadas y adaptarse rápidamente a las condiciones cambiantes del entorno. Si bien la agricultura de precisión ofrece soluciones innovadoras, su pleno potencial aún no ha sido alcanzado. Es necesario continuar investigando y desarrollando nuevas tecnologías, así como mejorar la accesibilidad y la adopción por parte de los agricultores.
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Zain, M., Ma, H., Chaudhary, S., Nuruzaman, M., Azeem, I., Mehmood, F., Aiwang D. & Sun, C. (2023). Nanotechnology in precision agriculture: Advancing towards sustainable crop production. Plant Physiol. Biochem. 2006:108244.
[USDA]. United States Department of Agriculture. (2018). World Agricultural Production. Circular Series.
Zhang, N., Wang, M., & Wang, N. (2002). Precision agriculture—a worldwide overview. Comput. Electron. Agric. 36(2-3), 113-132.
Shahzad, A. N., Qureshi, M. K., Wakeel, A., & Misselbrook, T. (2019). Crop production in Pakistan and low nitrogen use efficiencies. Nat. Sustain. 2(12), 1106-1114.
Zain, M., Ma, H., Nuruzzaman, M., Chaudhary, S., Nadeem, M., Shakoor, N., Azeem I., Duan A., Sun Ch. & Ahamad, T. (2023). Nanotechnology based precision agriculture for alleviating biotic and abiotic stress in plants. Plant Stress, 100239.
Araus, J. L., & Cairns, J. E. (2014). Field high-throughput phenotyping: the new crop breeding frontier. Trends Plant Sci, 19(1), 52-6.
Aasim, M., Katirci, R., Baloch, F. S., Mustafa, Z., Bakhsh, A., Nadeem, M. A., Ali, S.A., Hatipoglu, R., Ciftci, V., Habyarimana, E., Karaköy, T. & Chung, Y. S. (2022). Innovation in the breeding of common bean through a combined approach of in vitro regeneration and machine learning algorithms. Front. Genet. 13, 897696.
Avola, G., Distefano, M., Torrisi, A., & Riggi, E. (2024). Precision agriculture and patented innovation: State of the art and current trends. World Patent Information, 76, 102262.
Nowak, B. (2021). Precision agriculture: Where do we stand? A review of the adoption of precision agriculture technologies on field crops farms in developed countries. Agric. Res. 10(4), 515-522.
Bennur, P. J., & Taylor, R. K. (2010). Evaluating the response time of a rate controller used with a sensor-based, variable rate application system. Appl. Eng. Agric. 26(6), 1069-1075.
Dwivedi, R. S. (2017). Remote sensing of soils (Vol. 497). Berlin/Heidelberg, Germany: springer.
Ashraf, A., Ahmad, L., Ferooz, K., Ramzan, S., Ashraf, I., Khan, J. N., Shehnaz, E., Ul-Shafiq, M., Akhter S., Nabi, A., Rasool R. & Nazir, S. (2023). Remote Sensing as a Management and Monitoring Tool for Agriculture: Potential Applications. International Journal of Environment and Climate Change, 13(8), 324-343.
Zhang, Q. (2016). Precision agriculture technology for crop farming (p. 374). Taylor & Francis.
Monteiro, A., Santos, S., & Gonçalves, P. (2021). Precision agriculture for crop and livestock farming—Brief review. Animals. 11(8), 2345, 1-18.
Dudhani, S., Sinha, A. K., & Inamdar, S. S. (2006). Assessment of small hydropower potential using remote sensing data for sustainable development in India. Energy policy, 34(17), 3195-3205.
Avtar, R., Kumar, P., Oono, A., Saraswat, C., Dorji, S., & Hlaing, Z. (2017). Potential application of remote sensing in monitoring ecosystem services of forests, mangroves and urban areas. Geocarto Int. 32(8), 874-885.
Holloway, J., & Mengersen, K. (2018). Statistical machine learning methods and remote sensing for sustainable development goals: A review. Remote Sens. 10(9), 1365.
Bucci, G., Bentivoglio, D., & Finco, A. (2018). Precision agriculture as a driver for sustainable farming systems: state of art in literature and research. Calitatea, 19(S1), 114-121.
Researcheu E. Precision Farming: Sowing the Seeds of a New Agricultural Revolution. The Community Research and Development Information Service (CORDIS). Luxembourg; 2017.
Shi, J., Wu, X., Zhang, M., Wang, X., Zuo, Q., Wu, X., Zhang, H. & Ben-Gal, A. (2021). Numerically scheduling plant water deficit index-based smart irrigation to optimize crop yield and water use efficiency. Agric. Water Manag., 248, 106774.
Rodriguez-Ortega, W. M., Martinez, V., Rivero, R. M., Camara-Zapata, J. M., Mestre, T., & Garcia-Sanchez, F. (2017). Use of a smart irrigation system to study the effects of irrigation management on the agronomic and physiological responses of tomato plants grown under different temperatures regimes. Agric. Water Manag. 183, 158-168.
Goap, A., Sharma, D., Shukla, A. K., & Krishna, C. R. (2018). An IoT based smart irrigation management system using Machine learning and open-source technologies. Comput. Electron Agri. 155, 41-49.
Rai, V., Acharya, S., & Dey, N. (2012). Implications of nanobiosensors in agriculture.
Prasad, R., Pandey, R., & Barman, I. (2016). Engineering tailored nanoparticles with microbes: quo vadis?. Wiley Interdisciplinary Reviews: Wires Nanomed. Nanobi. 8(2), 316-330.
Seleiman, M. F., Almutairi, K. F., Alotaibi, M., Shami, A., Alhammad, B. A., & Battaglia, M. L. (2020). Nano-fertilization as an emerging fertilization technique: Why can modern agriculture benefit from its use?. Plants, 10(1), 2.
Ryu, H., Thompson, D., Huang, Y., Li, B., & Lei, Y. (2020). Electrochemical sensors for nitrogen species: A review. Sensors and Actuators Reports, 2(1), 100022.
Pedersen, S. M., & Lind, K. M. (Eds.). (2017). Precision agriculture: Technology and economic perspectives (pp. 52-53). Cham, Switzerland: Springer International Publishing.
Wollenhaupt, N. C., Mulla, D. J., & Gotway Crawford, C. A. (1997). Soil sampling and interpolation techniques for mapping spatial variability of soil properties. The state of site-specific management for agriculture, 19-53.
Derechos de autor 2024 Jorge Martín Guzmán Albores, Manuel de Jesús Matuz Cruz, Julia Yazmín Arana Llanes, Elizabeth López Carrasco, Vidalia Gómez Vázquez, Noé González Cárdenas
Esta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial-SinObrasDerivadas 4.0.