中国媒介生物学及控制杂志 ›› 2023, Vol. 34 ›› Issue (5): 686-690.DOI: 10.11853/j.issn.1003.8280.2023.05.018

• 调查研究 • 上一篇    下一篇

内蒙古西部农区基于智能物联网的鼠害监测系统待机时间及影响因素分析

郭承德1, 秦萌2, 韩立亮3, 付和平4,5, 刘宝玉6, 苏元红6, 肖彩虹7, 阿拉塔1, 蔺永生1, 段锐1, 王登云1, 乔靖然7   

  1. 1. 内蒙古巴彦淖尔市磴口县农牧业技术推广中心植保植检股, 内蒙古 磴口 015200;
    2. 全国农业技术推广服务中心, 北京 100125;
    3. 青岛清数科技有限公司, 山东 青岛 266000;
    4. 内蒙古农业大学草原与资源环境学院/内蒙古自治区高等学校草地啮齿动物生态学与鼠害控制重点实验室, 内蒙古 呼和浩特 010011;
    5. 内蒙古农业大学草地资源教育部重点实验室, 内蒙古 呼和浩特 010011;
    6. 内蒙古巴彦淖尔市现代农牧事业发展中心, 内蒙古 临河 015000;
    7. 中国林业科学院沙漠林业实验中心, 内蒙古 磴口 015200
  • 收稿日期:2023-03-07 出版日期:2023-10-20 发布日期:2023-10-27
  • 作者简介:郭承德,男,高级农艺师,主要从事农区鼠害智能监测研究,E-mail:nmggcd@163.com

A rodent surveillance system based on intelligent internet of things in western agricultural area of Inner Mongolia Autonomous Region, China: Standby time and associated correlation analysis

GUO Cheng-de1, QIN Meng2, HAN Li-liang3, FU He-ping4,5, LIU Bao-yu6, SU Yuan-hong6, XIAO Cai-hong7, Alata1, LIN Yong-sheng1, DUAN Rui1, WANG Deng-yun1, QIAO Jing-ran7   

  1. 1. Plant Protection Plant Inspection Unit of Agriculture and Animal Husbandry Technology Extension Center of Dengkou County, Bayannur City, Inner Mongolia, Dengkou, Inner Mongolia 015200, China;
    2. National Agro-tech Extension and Service Center, Beijing 100125, China;
    3. Qingdao Qingshu Technology Co., Ltd., Qingdao, Shandong 266000, China;
    4. College of Grassland Resources and Environment, Inner Mongolia Agricultural University/Key Laboratory of Grassland Rodent Ecology and Rodent Control, Inner Mongolia University, Hohhot, Inner Mongolia 010011, China;
    5. Key Laboratory of Grassland Resources of Ministry of Education, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia 010011, China;
    6. Modern Agriculture and Animal Husbandry Development Center of Bayannur City, Linhe, Inner Mongolia 015000, China;
    7. Experimental Center of Desert Forestry, Chinese Academy of Forestry, Dengkou, Inner Mongolia 015200, China
  • Received:2023-03-07 Online:2023-10-20 Published:2023-10-27

摘要: 目的对内蒙古自治区(内蒙古)西部巴彦淖尔市2019年9月-2022年12月应用鼠害智能监测系统的待机时间及影响因素进行统计分析,明确鼠密度与待机时间的相关关系。方法采用智能物联网终端VIMS 4.0系统监测害鼠,应用Excel 2016软件对各智能终端的待机正常运行天数、过机害鼠数量、鼠密度、待机时间等多项指标,在第1只鼠同一鼠种、县(旗)及不同风险等级地区等层面分别进行统计分析。结果在3个有效监测点,10套(台)有效终端系统,共2 730 d的有效监测时间内,监测到害鼠8种231只,数量从高到低排前5位的依次是小毛足鼠、子午沙鼠、阿拉善黄鼠、黑线仓鼠和小家鼠,总鼠密度为8.46%,害鼠平均活动频率为2.54只/(月·台)。小毛足鼠占57.58%,为优势鼠种。待机时间平均为118.20 d,集中于21~98 d,最短21 d,最长329 d,待机时间较长。通过终端的第1只鼠鼠种有4种,在第1只鼠同一鼠种所在各终端层面:所有鼠种平均鼠密度从大到小,排前3位的第1只鼠鼠种依次是小家鼠、阿拉善黄鼠、子午沙鼠;平均待机时间从小到大,排前3位的第1只鼠鼠种依次是小家鼠、阿拉善黄鼠、子午沙鼠。第1只鼠同一鼠种所在各终端的平均待机时间与鼠密度呈中度相关(r=-0.634);未标示风险等级的地区待机时间与鼠密度呈中度相关(r=-0.533)。结论首次明确智能终端系统的平均待机时间与鼠密度在一定的空间尺度上存在相关关系。

关键词: 鼠害, 农区, 内蒙古西部, 智能物联网, 监测, 待机时间

Abstract: Objective To analyze the standby time of an intelligent rodent surveillance system and its influencing factors in Bayannur in western Inner Mongolia Autonomous Region (Inner Mongolia), China from September 2019 to December 2022, and to determine the correlation between rodent density and standby time.Methods Rodents were monitored using the intelligent internet of things terminal system VIMS 4.0. Statistical analysis was performed using Excel 2016 on the days of normal standby operation, number of rodents videoed, rodent density, standby time, and other indicators of the intelligent terminals, by different aspects (the first rodents of the same species, counties/banners, and different risk levels regions).Results A total of 231 rodents of eight species were detected by 10 effective terminal systems at three effective monitoring sites during the total effective monitoring time of 2 730 d. The top five most common species were Phodopus roborovskii, Meriones meridianus, Spermophilus alaschanicus, Cricetulus barabensis, and Mus musculus. The overall rodent density was 8.46%, and the mean activity frequency was 2.54 rodents/month·terminal system. The dominant species was P. roborovskii, which accounted for 57.58%. The standby time averaged 118.20 d, and ranged from 21 d to 329 d, mostly in 21-98 d, indicating a long standby time. The first rodents crossing the terminals involved four species. For terminals with the same species of the first rodents: in the descending order of rodent density, the top three species of the first rodents were Mu. musculus, S. alaschanicus, and Me. meridianus; in the ascending order of mean standby time, the top three species of the first rodents were Mu. musculus, S. alaschanicus, and Me. meridianus. The mean standby time of the terminals with the same species of the first rodents was moderately correlated with rodent density (r=-0.634); the standby time was moderately correlated with rodent density in the area without definite risk levels (r=-0.533).Conclusion This study first demonstrated a significant negative correlation between the mean standby time and rodent density in a certain space range and at a certain time scale.

Key words: Rodent infestation, Agricultural area, Western Inner Mongolia, Intelligent internet of things, Surveillance, Standby time

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