基于航空图像处理和精确除草剂喷洒的智能杂草管理综述

IF 2.5 2区 农林科学 Q1 AGRONOMY
Armin Ehrampoosh , Pushpika Hettiarachchi , Anand Koirala , Jahan Hassan , Nahina Islam , Biplob Ray , Md Nurun Nabi , Mohamed Tolba , Abdul Md Mazid , Cheng-Yuan Xu , Nanjappa Ashwath , Pavel Dzitac , Steven Moore
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引用次数: 0

摘要

现代农业越来越多地采用智能技术来提高生产力,同时最大限度地降低生产成本,减少对环境的不利影响。这种协同作用的一个主要例子是使用图像处理来识别杂草,使机器人和无人机等自主设备能够有针对性地喷洒除草剂。这种方法不仅降低了生产成本,还确保了可持续农业,同时最大限度地减少了对环境的负面影响。设计一个智能杂草管理系统需要多学科的方法,结合农业、大数据处理、机器学习、计算机科学、机器人和植物科学。目前,独立的研究集中在其中的一些方面,但很少有人采取整体的方法来解决这个问题。本文重点介绍了在开发创新和生态可持续的农业杂草管理系统方面所采取的方法。它还介绍了杂草管理系统的全面概述,该系统集成了协调的杂草检测和喷洒,详细介绍了其独特的组成部分。本文回顾和对比了用于杂草检测的各种图像分析技术,特别是那些采用人工智能和无人驾驶飞行器(uav)捕获的图像。此外,本文还强调了图像处理平台的最新进展,例如向本地和边缘计算的转变,以及农业应用中对近实时处理的日益增长的需求。它还探讨了商用杂草喷洒无人机的发展,并讨论了自主杂草控制系统的各个方面,包括设计、导航和定向应用的喷洒机制。最后,本文确定了开发基于人工智能的靶向除草剂喷洒系统的关键研究需求,该系统可以为可持续、经济可行和高效的农业实践做出重大贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent weed management using aerial image processing and precision herbicide spraying: An overview
Modern agriculture is increasingly adopting intelligent technologies to enhance productivity while minimizing production costs and reducing adverse environmental impacts. A prime example of this synergy is the use of image processing to identify weeds, enabling targeted herbicide spraying with autonomous devices such as robots and drones. This approach not only reduces production costs but also ensures sustainable farming while minimizing negative environmental impacts. Designing an intelligent weed management system requires a multidisciplinary approach, combining agriculture, big data processing, machine learning, computer science, robotics, and plant science. Currently, independent studies have focused on some of these aspects, but few have taken a holistic approach to address the issue. This paper highlights the approach taken in developing innovative and ecologically sustainable weed management systems for agriculture. It also presents a comprehensive overview of a weed management system that integrates coordinated weed detection and spraying, detailing its unique components. The paper reviews and contrasts various image analysis techniques used in weed detection, particularly those employing artificial intelligence and imagery captured by unmanned aerial vehicles (UAVs). Furthermore, the paper highlights recent advancements in image processing platforms, such as the shift towards local and edge computing, and the growing need for near-real-time processing in agricultural applications. It also explores the development of commercial weed-spraying drones and discusses various aspects of an autonomous weed control system, including design, navigation, and spraying mechanisms for targeted application. Finally, the paper identifies key research needs for developing an AI-based, targeted herbicide spraying system that could significantly contribute to sustainable, economically viable, and efficient agricultural practices.
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来源期刊
Crop Protection
Crop Protection 农林科学-农艺学
CiteScore
6.10
自引率
3.60%
发文量
200
审稿时长
29 days
期刊介绍: The Editors of Crop Protection especially welcome papers describing an interdisciplinary approach showing how different control strategies can be integrated into practical pest management programs, covering high and low input agricultural systems worldwide. Crop Protection particularly emphasizes the practical aspects of control in the field and for protected crops, and includes work which may lead in the near future to more effective control. The journal does not duplicate the many existing excellent biological science journals, which deal mainly with the more fundamental aspects of plant pathology, applied zoology and weed science. Crop Protection covers all practical aspects of pest, disease and weed control, including the following topics: -Abiotic damage- Agronomic control methods- Assessment of pest and disease damage- Molecular methods for the detection and assessment of pests and diseases- Biological control- Biorational pesticides- Control of animal pests of world crops- Control of diseases of crop plants caused by microorganisms- Control of weeds and integrated management- Economic considerations- Effects of plant growth regulators- Environmental benefits of reduced pesticide use- Environmental effects of pesticides- Epidemiology of pests and diseases in relation to control- GM Crops, and genetic engineering applications- Importance and control of postharvest crop losses- Integrated control- Interrelationships and compatibility among different control strategies- Invasive species as they relate to implications for crop protection- Pesticide application methods- Pest management- Phytobiomes for pest and disease control- Resistance management- Sampling and monitoring schemes for diseases, nematodes, pests and weeds.
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