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农业土壤信息检测与传感技术研究进展与展望

Progress and Prospects of Agricultural Soil Information Monitoringand Sensing Technology Research
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摘要 土壤是农业生产的基础,其质量直接关系到农业的高效生产和可持续发展。土壤信息的精准监测和管理对于农业生产至关重要。该文综述了近年来农业土壤信息监测与传感技术的研究进展,重点分析了土壤水分、养分、温度、pH值、有机质含量等关键参数的传感器技术及其应用。同时,探讨了多传感器数据融合、无线传感网络、物联网(IoT)和大数据分析在土壤信息监测中的应用前景,并提出了未来研究的方向和发展趋势,应该进一步提升传感器精度、优化数据处理算法及提高系统集成度。通过研究和探索,农业土壤信息监测与传感技术有望在提升农业生产效率、保障农产品安全和促进生态环境保护方面取得更大突破。 Soil is the foundation of agricultural production,and its quality is directly related to the efficient production and sustainable development of agriculture.Accurate monitoring and management of soil information is crucial for agricultural production.This paper reviews the research progress of agricultural soil information monitoring and sensing technology in recent years,focusing on the analysis of sensor technology for key parameters such as soil moisture,nutrients,temperature,pH,organic matter content and their applications.Meanwhile,the application prospects of multi-sensor data fusion,wireless sensor network,Internet of Things(IoT)and big data analysis in soil information monitoring are discussed,and the direction and development trend of future research are proposed,which should further improve the sensor accuracy,optimize the data processing algorithm and improve the system integration.Through the research and exploration in this paper,agricultural soil information monitoring and sensing technology is expected to make greater breakthroughs in enhancing agricultural production efficiency,ensuring the safety of agricultural products and promoting ecological environmental protection.
作者 温英楠 王玉彪 WEN Yingnan;WANG Yubiao(Zhenlai County Agricultural Products Quality and Safety Supervision and Testing Center,Zhenlai 137300,China;Zhenlai County Agricultural Mechanization Technical Promotion Station,Zhenlai 137300,China)
出处 《农机使用与维修》 2024年第9期53-56,60,共5页 Agricultural Machinery Using & Maintenance
关键词 土壤信息监测 土壤水分 土壤养分 无线传感网络 多传感器数据融合 soil information monitoring soil moisture soil nutrients wireless sensor networks multi-sensor data fusion
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