Smart Farming Technologies and Agricultural Productivity: Evidence from Precision Agriculture Adoption
Keywords:
AgriTech, smart farming, precision agriculture, agricultural productivityAbstract
The integration of smart farming technologies has transformed modern agriculture by enabling data-driven decision-making and efficient resource utilization. This study examines the impact of precision agriculture technologies—such as sensor-based monitoring, GPS-guided machinery, and data analytics—on agricultural productivity and input efficiency. Using empirical data from commercial farms adopting smart farming practices, the results show significant improvements in crop yield, water-use efficiency, and cost reduction. The findings highlight the role of AgriTech solutions in supporting sustainable and resilient agricultural systems.
References
1. Gebbers, R., & Adamchuk, V. I. (2010). Precision agriculture and food security. Science, 327(5967), 828–831.
2. Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. J. (2017). Big data in smart farming. Agricultural Systems, 153, 69–80.
3. Rose, D. C., & Chilvers, J. (2018). Agriculture 4.0. Global Food Security, 18, 72–77.
4. Klerkx, L., Jakku, E., & Labarthe, P. (2019). A review of social science on digital agriculture. NJAS – Wageningen Journal of Life Sciences, 90–91, 100315.
5. Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine learning in agriculture. Sensors, 18(8), 2674.
6. Zhang, Q., Pierce, F. J., & Elliott, T. V. (2002). Precision agriculture technologies. Computers and Electronics in Agriculture, 36(2–3), 113–132.
7. Balafoutis, A. T., et al. (2017). Precision agriculture technologies positively affect yields. Sustainability, 9(8), 1339.
8. Eastwood, C., Klerkx, L., Ayre, M., & Dela Rue, B. (2019). Managing smart farming technologies. NJAS – Wageningen Journal of Life Sciences, 90–91, 100314.
9. Finger, R., Swinton, S. M., El Benni, N., & Walter, A. (2019). Precision farming at the farm level. Annual Review of Resource Economics, 11, 313–335.
10. OECD. (2023). Digital technologies in agriculture. OECD Publishing.
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