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人工智能在现代农业气象领域应用的研究进展

Research Progress in Application of Artificial Intelligence in Modern Agrometeorology Field

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【作者】 程敬雅; 景元书; 薛晓萍; 张继波; 李楠; 董智强; 张玉双;

【Author】 CHENG Jing-ya;JING Yuan-shu;XUE Xiao-ping;ZHANG Ji-bo;LI Nan;DONG Zhi-qiang;ZHANG Yu-shuang;Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters;School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology;Shandong Climate Center;

【通讯作者】 景元书;

【机构】 气象灾害预报预警与评估协同创新中心; 南京信息工程大学生态与应用气象学院; 山东省气候中心;

【摘要】 从传统农业气象方法的局限性以及人工智能在现代农业气象中的应用现状出发,通过分析具体的研究案例和进展,探讨了人工智能在农业气象中的重要作用。在作物产量预测方面,人工智能促使农民能够更加准确地了解气象对作物的影响,优化农业管理策略,提高作物产量并降低风险;在病虫害预测方面,人工智能可通过实时预测监测为农民提供及时、有效的防控策略;在农业气象灾害预警方面,人工智能可为农民提供更加准确、可靠的气象信息,及时防控,从而降低灾害对作物的影响;在农田土壤水分监测方面,人工智能可实现对农田土壤水分的实时监测、精准预测和智能管理。最后,展望了人工智能在农业生产中的巨大应用潜力。

【Abstract】 This paper discusses the important role of artificial intelligence in agrometeorology from the limitations of traditional agrometeorology methods, the application of artificial intelligence technology in modern agrometeorology and the specific research progress and cases. In terms of crop yield forecasting, the application of artificial intelligence technology enables farmers to more accurately understand the impact of weather on crops, optimize agricultural management strategies,increase yields and reduce risks. In the forecasting of pests and diseases, real-time forecasting and monitoring can be carried out to provide timely and effective prevention and control strategies for farmers. In agricultural meteorological disaster prediction and early warning, artificial intelligence technology can provide more accurate and reliable meteorological information, so as to reduce the impact of disasters on crops by timely prevention and control. In terms of farmland soil moisture monitoring, it can realize real-time monitoring, accurate prediction and intelligent management of farmland soil moisture. Finally, this paper looks forward to the great potential and opportunities of the application of artificial intelligence technology in agricultural production.

【关键词】 人工智能; 农业气象; 监测; 模型; 应用;
【Key words】 Artificial intelligence; Agrometeorology; Monitoring; Model; Application;
【基金】 教育部新农科建设项目(2020N0148);新一代人工智能国家科技重大专项“基于大数据的产量智能预测与灾损评估”(2022ZD0119503);山东省气象局气象科研重点项目(2023sdqxz12);南京信息工程大学课程思政项目(2023XKCSZ16)
  • 【文献出处】 江西农业学报 ,Acta Agriculturae Jiangxi , 编辑部邮箱 ,2024年07期
  • 【分类号】S16;TP18
  • 【下载频次】44
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