The Development of Precision Agriculture Research in Modern Agriculture: A Bibliometric Study 2010–2024

Authors

  • Loso Judijanto IPOSS Jakarta, Indonesia

DOI:

https://doi.org/10.58812/wsa.v4i02.2901

Keywords:

Precision Agriculture, Smart Agriculture, Sustainable Development, Internet of Things (IoT), Artificial Intelligence, Machine Learning, Bibliometric Analysis

Abstract

Precision agriculture has emerged as a transformative approach in modern agriculture by integrating advanced technologies such as remote sensing, artificial intelligence, machine learning, Internet of Things (IoT), robotics, and big data analytics to improve agricultural productivity and sustainability. Given the rapid expansion of research in this field, a comprehensive understanding of its intellectual structure and development trends is essential. This study aims to analyze the evolution of precision agriculture research through a bibliometric examination of global scientific publications indexed in the Scopus database from 2010 to 2024. Bibliometric techniques were employed to evaluate publication trends, influential authors, institutions, countries, and highly cited literature. Furthermore, network visualization analyses using VOSviewer were conducted, including co-authorship, institutional collaboration, country collaboration, co-citation, keyword co-occurrence, overlay visualization, and density visualization. The findings reveal a significant increase in publication output over the study period, reflecting growing academic and practical interest in precision agriculture. India, China, the United States, and the Russian Federation emerged as the most influential contributors in terms of collaboration and research productivity. The most highly cited literature focused on nanotechnology, hyperspectral imaging, sustainable nutrient management, agricultural robotics, and smart farming technologies. Keyword analysis identified precision agriculture, sustainable development, smart agriculture, crops, Internet of Things, machine learning, and artificial intelligence as dominant research themes. Overlay visualization further demonstrated a transition from traditional topics such as soil fertility and crop management toward digitally enabled and sustainability-oriented agricultural systems. The results indicate that precision agriculture has evolved into a highly interdisciplinary field that combines technological innovation and sustainable development principles to address global agricultural challenges. The study provides valuable insights into current research trends and future directions for researchers, policymakers, and practitioners engaged in modern agricultural development.

References

[1] J. Agrawal and M. Y. Arafat, “Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture.,” Drones (2504-446X), vol. 8, no. 11, 2024.

[2] N. N. Aruwajoye and R. Coetzee, “Transitioning from linear to circular systems offers sustainable solutions for smallholder agriculture in the Global South,” Environ. Challenges, vol. 21, 2025, doi: 10.1016/j.envc.2025.101300.

[3] D. Chattopadhyay et al., “Precision Agriculture Technologies for Early Detection of Crop Pests and Diseases,” UTTAR PRADESH J. Zool., 2024, [Online]. Available: https://api.semanticscholar.org/CorpusID:273825813

[4] A. B. Tanna, R. S. Jatakia, and G. D. Nagare, “Role of AI in the Field of Precision Agriculture,” in Artificial Intelligence for Precision Agriculture, Auerbach Publications, 2024, pp. 61–79.

[5] R. Gebbers and V. I. Adamchuk, “Precision agriculture and food security,” Science (80-. )., vol. 327, no. 5967, pp. 828–831, 2010.

[6] A. Y. Adewuyi, B. Anyibama, K. B. Adebayo, J. M. Kalinzi, S. A. Adeniyi, and I. Wada, “Precision agriculture: Leveraging data science for sustainable farming,” Int. J. Sci. Res. Arch., vol. 12, no. 2, pp. 1122–1129, 2024.

[7] Y. Devarajan et al., “Adapting agriculture for climate resilience: Strategies for sustainable production and food security,” Results Eng., vol. 29, 2026, doi: 10.1016/j.rineng.2026.109632.

[8] B. S. Sekhon, “Nanotechnology in agri-food production: an overview,” Nanotechnol. Sci. Appl., pp. 31–53, 2014.

[9] M. J. Khan, H. S. Khan, A. Yousaf, K. Khurshid, and A. Abbas, “Modern trends in hyperspectral image analysis: A review,” Ieee Access, vol. 6, pp. 14118–14129, 2018.

[10] M. Rai and A. Ingle, “Role of nanotechnology in agriculture with special reference to management of insect pests,” Appl. Microbiol. Biotechnol., vol. 94, no. 2, pp. 287–293, 2012.

[11] Y. Miao, B. A. Stewart, and F. Zhang, “Long-term experiments for sustainable nutrient management in China. A review,” Agron. Sustain. Dev., vol. 31, no. 2, pp. 397–414, 2011.

[12] A. M. Ismail and T. Horie, “Genomics, physiology, and molecular breeding approaches for improving salt tolerance,” Annu. Rev. Plant Biol., vol. 68, pp. 405–434, 2017.

[13] J. Chen et al., “Environmentally friendly fertilizers: A review of materials used and their effects on the environment,” Sci. Total Environ., vol. 613, pp. 829–839, 2018.

[14] R. R. Shamshiri et al., “Research and development in agricultural robotics: A perspective of digital farming,” Int. J. Agric. Biol. Eng., vol. 11, no. 4, pp. 1–14, 2018.

[15] A. Monteiro, S. Santos, and P. Gonçalves, “Precision agriculture for crop and livestock farming—Brief review,” Animals, vol. 11, no. 8, p. 2345, 2021.

[16] V. Sharma, A. K. Tripathi, and H. Mittal, “Technological revolutions in smart farming: Current trends, challenges & future directions,” Comput. Electron. Agric., vol. 201, p. 107217, 2022.

[17] A. Soussi, E. Zero, R. Sacile, D. Trinchero, and M. Fossa, “Smart sensors and smart data for precision agriculture: a review,” Sensors, vol. 24, no. 8, p. 2647, 2024.

Downloads

Published

2026-05-30

How to Cite

The Development of Precision Agriculture Research in Modern Agriculture: A Bibliometric Study 2010–2024 (L. Judijanto, Trans.). (2026). West Science Agro, 4(02), 238-248. https://doi.org/10.58812/wsa.v4i02.2901