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.

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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
Controls
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article

Precision Agriculture Current Progress From a Novel Bibliometric Method

Shan Chen, Yuanzhao Ding
1 citations
World Food Policy
Smart Agriculture and AI
1.75
article

Precision Agriculture Current Progress From a Novel Bibliometric Method

Shan Chen, Yuanzhao Ding
article en
1 citations

Abstract

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.

World Food PolicyVol. 11(1)
Nanyang Technological University (SG), University of Oxford (GB)
Openalex Percentile: Top 16%
Smart Agriculture and AI
1.75
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Precision Agriculture Current Progress From a Novel Bibliometric Method — Shan Chen, Yuanzhao Ding · World Food Policy (2025) | TGRS Research Map | TGRS