Research Progress on Soil Nutrient Detection Sensors Based on Bibliometrics

GUO Jialong; HU Feng; YANG Zhangqing; ZHANG Jie; ZANG Hezang; CHANG Baofang; LI Guoqiang; XIN Yinping

doi:10.11924/j.issn.1000-6850.casb2025-0778

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Chin Agric Sci Bull ›› 2026, Vol. 42 ›› Issue (10) : 171-178. DOI: 10.11924/j.issn.1000-6850.casb2025-0778

Research Progress on Soil Nutrient Detection Sensors Based on Bibliometrics

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Abstract

This study aims to systematically sort out the research dynamics and development laws in the global field of soil nutrient detection sensors, providing data support for the research and development of next-generation sensor technologies. It took 598 relevant literature included in the Web of Science Core Collection from 2015 to 2024 as the research object, and adopted CiteSpace bibliometric software to conduct visual analysis. The results showed that the research trend in this field could be divided into three stages: the initial exploration and accumulation period of technology (2015-2016), the steady growth period (2017-2021), and the explosive growth period (2022-2024). The research exhibited a remarkable interdisciplinary nature, with environmental science and analytical chemistry as the main supporting disciplines. China and the United States performed prominently in research in this field, and scientific research institutions continuously promoted technological development. The research hotspots focused on precision agriculture, core sensing technology, and key nutrient index detection, while the research frontiers gradually extended to the application of intelligent algorithms, specific nutrient detection, and the monitoring of soil properties and environmental effects. Although technological innovation continues to advance, this field still faced key bottlenecks such as fragmentation of technical paths, insufficient coordination between near-ground and remote sensing data, and lack of a standardized evaluation system, and most research results had not yet been applied in the field. Future research needs to make breakthroughs in four directions: technology integration, data collaboration, standard establishment, and scenario implementation, so as to provide technical support for agricultural sustainable development and ecological protection.

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soil nutrient detection sensor / bibliometrics / Web of Science / visual analysis / precision agriculture / machine learning / intelligent detection

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GUO Jialong , HU Feng , YANG Zhangqing , et al . Research Progress on Soil Nutrient Detection Sensors Based on Bibliometrics[J]. Chinese Agricultural Science Bulletin. 2026, 42(10): 171-178 https://doi.org/10.11924/j.issn.1000-6850.casb2025-0778

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