土壤墒情监测技术研究现状与发展趋势  

Current status and development trends of soil moisture monitoring technologies

作　　者：高宁 张安琪 梅鹤波 杨兴华 甘蕾 孟志军 GAO Ning;ZHANG Anqi;MEI Hebo;YANG Xinghua;GAN Lei;MENG Zhijun(College of Engineering,Heilongjiang Bayi Agricultural University,Daqing 163319,China;Intelligent Equipment Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,China;State Key Laboratory of Intelligent Agricultural Power Equipment,Beijing 100097,China)

机构地区：[1]黑龙江八一农垦大学工程学院,黑龙江大庆163319 [2]北京市农林科学院智能装备技术研究中心,北京市100097 [3]智能农业动力装备全国重点实验室,北京市100097

出　　处：《智能化农业装备学报（中英文）》2024年第3期51-62,共12页Journal of Intelligent Agricultural Mechanization

基　　金：国家重点研发计划项目(2021YFD2000402-2);山东省重点研发计划(重大科技创新工程)项目(2022CXGC010608);云南省陈立平专家工作站(202105AF150030)。

摘　　要：随着农业生产对田间管理要求的不断提升,传统的农机设备已逐渐难以适应现代智慧农业的生产需求。在这一背景下,土壤墒情监测技术作为现代农田管理中获取土壤含水率信息的关键手段,正扮演着推动农机向自动化、智能化发展的重要角色。为此,深入梳理和分析国内外土壤墒情监测技术研究现状,重点围绕土壤墒情监测的方式及原理、模型构建算法以及信号处理方法这3个方面技术的研究进展进行阐述,通过对比分析,归纳与总结了国内外在监测方式、原理、模型构建算法和信号处理方法上的异同以及实际应用中存在的问题和面临的挑战,并提出了土壤墒情监测技术在这3个方面未来的发展趋势:土壤墒情监测方式方面,构建多源土壤墒情监测信息平台,以实现更全面的数据收集和分析;模型构建算法方面,通过采用机器学习和深度学习算法,为不同土壤环境和作业场景量身定制模型算法模块,提高监测设备准确性和适用性;信号处理方面,加强多源信号融合技术的应用,降低作业环境对监测设备的影响。As agricultural production continues to increase its requirements for field management,traditional agricultural machinery and equipment have gradually become difficult to meet the production needs of modern smart agriculture.In this context,soil moisture monitoring technology,as a key means of obtaining soil moisture information in modern agricultural management,is playing an important role in promoting the development of agricultural machinery towards intelligence and automation.Therefore,this study thoroughly reviews and analyzes the current research status of soil moisture monitoring technology at home and abroad,focusing on the research progress of three aspects of soil moisture monitoring methods and principles,model construction algorithms,and signal processing methods.Through comparative analysis,the differences and similarities in monitoring methods,principles,model construction algorithms,and signal processing methods at home and abroad,as well as the problems and challenges in practical applications,are summarized.The future development trends of soil moisture monitoring technology in these three aspects are proposed:in terms of soil moisture monitoring methods,a multi-source soil moisture monitoring information platform is constructed to achieve more comprehensive data collection and analysis;In terms of model construction algorithms,machine learning and deep learning algorithms are adopted to customize model algorithm modules for different soil environments and working scenarios,improving the accuracy and applicability of monitoring equipment;In terms of signal processing,the application of multi-source signal fusion technology is strengthened to reduce the impact of the working environment on monitoring equipment.

关 键 词：土壤墒情 机载式监测 原位监测 机器学习 深度学习 信号处理 

分 类 号：S233[农业科学—农业机械化工程]