Precision Agriculture Current Progress From a Novel Bibliometric Method
ABSTRACT Agriculture plays a crucial role in sustaining the global population, providing food to billions of people. As the world's population continues to grow, the demand for more efficient and sustainable farming practices becomes ever more critical. Precision agriculture has emerged as a transformative solution, integrating advanced technologies like sensors, data analytics, and automation. This approach allows for better resource management, reducing waste and increasing productivity, while also promoting sustainability. This study utilizes the latest bibliometric analysis methods to explore precision agriculture's current state and future prospects. By analyzing over 1000 academic articles, this method provides deeper insights into key trends, patterns, and technological innovations shaping the field. The paper focuses on two major themes: optimizing resources for sustainable farming and the integration of big data and machine learning technologies. These innovations promise to enhance farming practices, making agriculture more efficient, adaptive, and capable of meeting future food security challenges.
Authors
- Shan Chen (ORCID: https://orcid.org/0000-0002-2750-5063)
- Yuanzhao Ding (ORCID: https://orcid.org/0000-0003-0116-3648)
Institutions
- Nanyang Technological University (SG)
- University of Oxford (GB)
Publication Details
- Journal
- World Food Policy
- Published
- 2025-04-30
- DOI
- https://doi.org/10.1002/wfp2.70004
- Citations
- 1
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 1.75