人工智能驱动的可持续农业作物保护优化

Priyamvada Shankar, Nicolas Werner, S. Selinger, Ole Janssen
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引用次数: 5

摘要

本文介绍了xarvio™提供的数字农业解决方案,以及这些解决方案如何有助于实现联合国可持续发展目标。通过利用人工智能的最新进展,农民可以通过有针对性的使用更有效地应用作物保护。本文介绍的各个模块,即喷雾定时器、区域喷雾、缓冲区和产品推荐,确保作物保护产品在正确的时间和只在需要的地方施用,同时确保以最佳速率施用正确的产品。这不仅减少了对环境的影响,而且还提高了农民的生产力和盈利能力。欧洲和巴西这两个主要粮食生产地区的实际案例研究证明了我们的数字解决方案的影响。在欧洲,使用人工智能驱动的喷雾定时、可变速率应用地图和产品推荐,使田间试验谷物的杀菌剂使用量减少了30%,储罐剩余物减少了72%,从而减少了环境污染。在巴西,使用计算机视觉技术创建的区域喷雾杂草地图解决方案平均节省了61%,减少了近三分之二的除草剂和水的消耗。因此,本文提出的解决方案迎合了联合国零饥饿和负责任消费和生产的可持续发展目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence Driven Crop Protection Optimization for Sustainable Agriculture
This paper introduces digital farming solutions offered by xarvio™ and how these solutions contribute towards achieving the United Nations Sustainable Development Goals. By leveraging recent advancements in Artificial Intelligence, farmers can apply crop protection more efficiently by targeted usage. Respective modules presented in this paper, namely Spray Timer, Zone Spray, Buffer Zones and Product Recommendation ensure crop protection products are applied at the right time and only where they are needed while also ensuring the right product at the optimal rate. This not only reduces the impact on the environment, but moreover increases the productivity and profitability of the farmer. The impact of our digital solutions is exemplified by real world case studies in two major food production regions: Europe and Brazil. In Europe the use of Artificial Intelligence driven spray timing, variable rate application maps and product recommendation have led to a 30% decrease in fungicide usage on field trial cereal crops and a 72% decrease in tank leftovers reducing environmental pollution. In Brazil the Zone Spray weed maps solution created using Computer Vision techniques resulted in a 61% average savings, cutting back on almost two thirds of herbicide and water consumption. As a result the solutions presented in this paper cater to the UN Sustainable Development Goals of zero hunger and responsible consumption and production.
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