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Development of an automatic monitoring system for rice light-trap pests based on machine vision

机译:基于机器视觉的水稻光害虫自动监测系统的开发

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摘要

Monitring pest populations in paddy fields is important to effectively implement integrated pest management.Light traps are widely used to monitor field pests all over the world.Most conventional light traps still involve manual identification of target pests from lots of trapped insects,which is time-consuming,labor-intensive and error-prone,especially in pest peak periods.In this paper,we developed an automatic monitoring system for rice light-trap pests based on machine vision.This system is composed of an itelligent light trap,a computer or mobile phone client platform and a cloud server.The light trap firstly traps,kills and disperses insects,then collects images of trapped insects and sends each image to the cloud server.Five target pests in images are automatically identifed and counted by pest identification models loaded in the server.To avoid light-trap insects piling up,a vibration plate and a moving rotation conveyor belt are adopted to disperse these trapped insects.There was a close correlation(r=0.92)between our automatic and manual identification methods based on the daily pest number of one-year images from one light trap.Field experiments demonstrated the effectiveness and accuracy of our automatic light trap monitoring system.
机译:稻田的孤独害虫群是有效实施综合虫害管理的重要.Light陷阱广泛用于监测世界各地的野外害虫。大多数传统的光陷阱仍然涉及从许多捕获的昆虫中手动识别目标害虫,这是时候 - 消耗,劳动密集型和容易出错,特别是在害虫高峰期。在本文中,我们开发了一种基于机器视觉的稻米轻型捕捉害虫的自动监测系统。该系统由易射门轻陷阱,计算机或计算机组成手机客户端平台和云服务器。灯陷阱首先陷阱,杀死和分散昆虫,然后收集被困昆虫的图像,并将每个图像发送到云服务器。通过加载的有害生物识别模型自动识别图像中的目标虫害。在服务器中。要避免堆积的轻陷阱昆虫,采用振动板和移动旋转传送带来分散这些被困的昆虫。基于从一个灯陷阱的每日害虫数量的一年图像的每日害虫数量,我们的自动和手动识别方法之间是紧密相关性(r = 0.92).Field实验证明了我们自动光陷阱监测系统的有效性和准确性。

著录项

  • 来源
    《农业科学学报:英文版》 |2020年第010期|P.2500-2513|共14页
  • 作者单位

    School of Information Science and Technology Zhejiang Sci-Tech University Hangzhou 310018 P.R.China;

    School of Information Science and Technology Zhejiang Sci-Tech University Hangzhou 310018 P.R.China;

    State Key Laboratory of Rice Biology China National Rice Research Institute Hangzhou 310006 P.R.China;

    Plant Protection Quarantine and Pesticide Management Station of Zhejiang Hangzhou 310020 P.R.China;

    Zhejiang Top Cloud-agri Technology Co Ltd. Hangzhou 310015 P.R.China;

    State Key Laboratory of Rice Biology China National Rice Research Institute Hangzhou 310006 P.R.China;

    School of Information Science and Technology Zhejiang Sci-Tech University Hangzhou 310018 P.R.China;

    Agricultural Technology Extension Center of Shangyu Shaoxing 312300 P.R.China;

    School of Information Science and Technology Zhejiang Sci-Tech University Hangzhou 310018 P.R.China;

    School of Information Science and Technology Zhejiang Sci-Tech University Hangzhou 310018 P.R.China;

    School of Information Science and Technology Zhejiang Sci-Tech University Hangzhou 310018 P.R.China;

    Agricultural Technology Extension Center of Keerqin Keerqin 137713 P.R.China;

  • 收录信息 中国科学引文数据库(CSCD);
  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类 计算技术、计算机技术;
  • 关键词

    automatic monitoring system; light trap; rice pest; machine vision; image processing; convolutional neural network;

    机译:自动监控系统;陷阱;大米害虫;机器视觉;图像处理;卷积神经网络;
  • 入库时间 2022-08-19 04:44:58
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