Advances and prospects of precision agriculture for agricultural sustainability

Keywords: Precision agriculture, Nanotechnology, Remote Sensing, Dose Rate Technology

Abstract

Precision agriculture is an agricultural practice that uses advanced technologies, such as remote sensing, intelligent irrigation systems, and nanotechnology, to optimize natural resource management and increase agricultural productivity. This discipline emerges in response to contemporary challenges in agriculture, such as increasing food demand, resource scarcity, and environmental impacts. By collecting, analyzing, and applying large volumes of data in real-time, precision agriculture enables farmers to make informed decisions and adapt quickly to changing environmental conditions. While precision agriculture offers innovative solutions, its full potential has yet to be realized. Further research and development of new technologies are needed, as well as improved accessibility and adoption by farmers.

Downloads

Download data is not yet available.

References

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.

Published
2024-07-05
How to Cite
Guzmán Albores, J. M., Matuz Cruz, M. de J., Arana Llanes, J. Y., López Carrasco, E., Gómez Vázquez, V., & González Cárdenas, N. (2024). Advances and prospects of precision agriculture for agricultural sustainability. XIKUA Boletín Científico De La Escuela Superior De Tlahuelilpan, 12(24), 1-6. https://doi.org/10.29057/xikua.v12i24.12790

Most read articles by the same author(s)

1 2 > >>