Precision Agriculture Applied to Sustainable Bermuda Grass (Cynodon dactylon) Production: An IoT Sensor-Based Technological Proposal for Irrigation Optimization in Sports Turf Surfaces
DOI:
https://doi.org/10.47230/ra.v9i1.152Keywords:
precision agriculture, Bermuda grass, IoT sensors, automated irrigation, water sustainabilityAbstract
Efficient water management represents one of the main challenges for the sustainable maintenance and production of sports turf, particularly in regions where water availability is influenced by climatic and environmental factors. In this context, Bermuda grass (Cynodon dactylon) is one of the most widely used species for sports surfaces due to its adaptability, traffic tolerance, and rapid vegetative growth. However, inadequate irrigation management can significantly affect its quality, coverage, and agronomic performance. The objective of this study was to analyze the application of precision agriculture technologies in order to formulate a technological proposal based on Internet of Things (IoT) sensors aimed at optimizing irrigation and sustainable production of Cynodon dactylon on sports fields.
The research was conducted through a descriptive and documentary literature review considering scientific publications indexed between 2015 and 2026. Studies related to precision agriculture, soil moisture sensors, Internet of Things technologies, automated irrigation systems, and agronomic management of sports turf were analyzed. The collected information enabled the identification of the main technologies currently employed for environmental monitoring and intelligent irrigation control in agricultural and landscaping systems.
The findings indicate that integrating IoT sensors into automated irrigation systems promotes more efficient water management by adjusting water application according to the actual requirements of the crop. Furthermore, scientific evidence reports improvements in water-use efficiency, reductions in operational costs, and enhanced plant growth conditions when precision agriculture tools are implemented. Based on these findings, a conceptual technological proposal was designed, integrating soil moisture sensors, remote monitoring platforms, and automated irrigation control systems for future applications in sports turf management.
It is concluded that precision agriculture constitutes a viable technological alternative to improve sustainability and efficiency in the management of Cynodon dactylon, contributing to the modernization of sports turf maintenance systems through rational water use and the incorporation of digital technologies.
Keywords: precision agriculture, Bermuda grass, IoT sensors, automated irrigation, water sustainability.
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References
Antony, A. P., Leith, K., Jolley, C., Lu, J., & Sweeney, D. J. (2020). A review of practice and implementation of the Internet of Things (IoT) for smallholder agriculture. Sustainability, 12(9), 3750. https://doi.org/10.3390/su12093750
Beard, J. B. (2002). Turf management for golf courses (2nd ed.). Ann Arbor Press.
Burton, G. W. (1964). Tifgreen bermudagrass. Crop Science, 4(1), 107.
Carrow, R. N., Waddington, D. V., & Rieke, P. E. (2001). Turfgrass soil fertility and chemical problems: Assessment and management. John Wiley & Sons.
Christians, N. E., Patton, A. J., & Law, Q. D. (2016). Fundamentals of turfgrass management (5th ed.). Wiley.
Fry, J., & Huang, B. (2004). Applied turfgrass science and physiology. John Wiley & Sons.
García, L., Parra, L., Jiménez, J. M., Lloret, J., & Lorenz, P. (2020). IoT-based smart irrigation systems: An overview on the recent trends on sensors and IoT systems for irrigation in precision agriculture. Sensors, 20(4), 1042. https://doi.org/10.3390/s20041042
Huang, B. (2006). Plant-environment interactions in turfgrass systems. Springer.
Li, W. (2020). Review of sensor network-based irrigation systems using IoT and remote sensing. Advances in Meteorology, 2020, 8396164. https://doi.org/10.1155/2020/8396164
Navarro, E., Costa, N., & Pereira, A. (2020). A systematic review of IoT solutions for smart farming. Sensors, 20(15), 4231. https://doi.org/10.3390/s20154231
Pannell, D. J., Griffin, T., Ferraro, P., Ribaudo, M., & Walter, C. (2014). Sustainable intensification in agriculture. Australian Journal of Agricultural and Resource Economics, 58(1), 1–17.
Pierce, F. J., & Nowak, P. (1999). Aspects of precision agriculture. Advances in Agronomy, 67, 1–85.
Qin, Y., & Zhang, X. (2020). Applications of remote sensing in precision agriculture: A review. Remote Sensing, 12(19), 3136. https://doi.org/10.3390/rs12193136
Stowell, L. J., Gelernter, W., Johnson, M. E., Brown, C. D., & Kopec, D. M. (2005). Turfgrass growth and quality responses to irrigation management. Crop Science, 45(6), 2511–2520.
Trenholm, L. E., Unruh, J. B., & Cisar, J. L. (2012). Warm-season turfgrass management. University Press of Florida.
Turgeon, A. J. (2012). Turfgrass management (9th ed.). Pearson Education.
United States Golf Association. (2018). Recommendations for a method of putting green construction. USGA.
Food and Agriculture Organization. (2017). Water for sustainable food and agriculture. FAO.
Food and Agriculture Organization. (2021). The state of the world’s land and water resources for food and agriculture. FAO.
Kumar, S. V., Singh, C. D., & Upendar, K. (2020). Review on IoT based precision irrigation system in agriculture. Current Journal of Applied Science and Technology, 39(45), 15–26. https://doi.org/10.9734/cjast/2020/v39i4531156
Patton, A. J., Richardson, M. D., & Karcher, D. E. (2017). Turfgrass establishment and management practices. Crop Science, 57(6), 2919–2934.
Bell, G. E., Martin, D. L., Wiese, S. G., Dobson, D. D., Smith, M. W., Stone, M. L., & Solie, J. B. (2000). Vehicle-mounted optical sensing: An objective means for evaluating turf quality. Crop Science, 40(5), 1488–1495.
Jones, H. G. (2004). Irrigation scheduling: Advantages and pitfalls of plant-based methods. Journal of Experimental Botany, 55(407), 2427–2436.
Evans, R. G., & Sadler, E. J. (2008). Methods and technologies to improve efficiency of water use. Water Resources Research, 44(7), 1–15.
Gebbers, R., & Adamchuk, V. I. (2010). Precision agriculture and food security. Science, 327(5967), 828–831.
Zhang, N., Wang, M., & Wang, N. (2002). Precision agriculture—A worldwide overview. Computers and Electronics in Agriculture, 36(2–3), 113–132.
Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. J. (2017). Big data in smart farming. Agricultural Systems, 153, 69–80.
Khanna, M., & Kaur, P. (2019). Internet of Things (IoT), applications and challenges. Procedia Computer Science, 132, 321–326.
Ayaz, M., Ammad-Uddin, M., Sharif, Z., Mansour, A., & Aggoune, E. H. M. (2019). Internet-of-Things (IoT)-based smart agriculture. Wireless Communications and Mobile Computing, 2019, 1–11.
Benke, K., & Tomkins, B. (2017). Future food-production systems. Sustainability: Science, Practice and Policy, 13(1), 13–26.
Elshafie, A. H., Al-Muqdadi, S. W., & Al-Rousan, M. A. (2015). Automated irrigation systems for sustainable agriculture. Agricultural Water Management, 157, 1–10.
Da Silva, J. M., & Teixeira, E. I. (2018). Smart irrigation technologies for sustainable water management. Agricultural Engineering International, 20(4), 123–134.
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