Weeds are amongst the most impacting abiotic factors in agriculture, causing important yield loss worldwide. Integrated Weed Management coupled with the use of Unmanned Aerial Vehicles (drones), allows for Site-Specific Weed Management, which is a highly efficient methodology as well as beneficial to the environment. The identification of weed patches in a cultivated field can be achieved by combining image acquisition by drones and further processing by machine learning techniques. Specific algorithms can be trained to manage weeds removal by Autonomous Weeding Robot systems via herbicide spray or mechanical procedures. However, scientific and technical understanding of the specific goals and available technology is necessary to rapidly advance in this field. In this review, we provide an overview of precision weed control with a focus on the potential and practical use of the most advanced sensors available in the market. Much effort is needed to fully understand weed population dynamics and their competition with crops so as to implement this approach in real agricultural contexts.

中文翻译：

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无人机和传感器技术用于可持续杂草管理：回顾

杂草是农业中影响最大的非生物因素之一，在全球范围内造成重要的产量损失。综合杂草管理与无人飞行器（无人机）的结合使用，可以实现针对特定地点的杂草管理，这是一种高效的方法，并且对环境有益。可以通过结合无人机采集的图像和机器学习技术的进一步处理来实现对耕地中杂草斑块的识别。可以训练特定算法，以通过除草剂喷雾或机械程序通过自动除草机器人系统管理除草。但是，对特定目标和可用技术的科学和技术理解对于在该领域迅速发展是必需的。在这篇评论中，我们提供了精确除草的概述，重点是市场上最先进的传感器的潜力和实际使用。为了充分了解杂草种群动态及其与农作物的竞争，需要付出大量的努力，才能在实际的农业环境中实施这种方法。