N2Vision+: A robot-enabled, data-driven machine vision tool for nitrogen diagnosis of arable soils

N2Vision：一种由机器人驱动、数据驱动的机器视觉工具，用于耕地土壤的氮诊断

• 批准号: 10091423
• 金额: $ 30.18万
• 依托单位: AUTODISCOVERY LTD.
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10091423
• 关键词: N2Vision+; robot; enabled; data; driven

Increasing crop productivity while minimising resource use and environmental impact is a global challenge for food production. Among all farmer-controlled input factors, Nitrogen (N) has the second-largest impact on crop growth after water, and arable soils are a predominant source of N in many cropping systems. Optimal N fertilisation can increase crop production and enhance soil fertility. On the other hand, high N inputs are costly for farmers and result in reductions in plant biodiversity, pollution of natural ecosystems and increases in emissions of the potent greenhouse gas, nitrous oxide. UK farmers currently spend £1.345 billion on fertilisers, often applying excessive N due to the lack of precise information about soil N levels.Driven by the needs of the growers, our previous feasibility project (N2Vision), addressed this challenge by developing a non-destructive robot-enabled AI vision system for automated N diagnosis in plants and soil (TRL 5). This system automatically collected data using a mobile robot with image cameras and intelligently diagnosed crop and soil N levels using AI algorithms. Initial assessments showed potential cost reductions of 27%, increased farm profitability by 17%, and emission savings of 65% compared to current practices. To make this technology practical for farmers and further advance its adoption, we aim to raise its TRL and move closer to commercialization.Building upon our N2Vision innovations, our follow-on project, N2Vision+, aims to develop a commercial product for automated soil nitrogen monitoring at a higher TRL. We will enhance our existing innovations by adding optional modular sensors like 3D mapping (360-degree) and soil probes, enabling cost-effective data collection and scalable N monitoring. Additionally, we will conduct field trials to simulate robotic foliar nitrogen application, potentially reducing N usage and costs.This precision agriculture solution will revolutionise food production by optimising N use, increasing farm profitability, and contributing to net-zero emissions. It offers early detection of crop and soil N levels, precise information on N use efficiency, and soil quality assessment, positioning UK precision agriculture technologies at the forefront of new industries and driving economic growth in the UK.

增加农作物的产量，同时最大程度地减少资源使用和环境影响是粮食生产的全球挑战。在所有由农民控制的输入因素中，氮（N）对水后农作物的生长有第二大影响，而在许多农作物系统中，可耕地是N的主要来源。最佳的N受精可以增加农作物的产量并增强土壤生育能力。另一方面，高N投入对于农民来说是昂贵的，并导致植物生物多样性的减少，自然生态系统的污染以及有效的温室气体（一二氮氧化物）排放的增加。英国农民目前在肥料上花费134.5亿英镑，通常施加过多的N，因为缺乏有关土壤N级别的精确信息，我们以前的可行性项目（N2Vision）的需求驱动了这一挑战，通过开发非损害机器人的AI诊断植物和土壤中的无损害机器人的AI诊断系统（Trl 5）。该系统使用带有图像摄像机的移动机器人自动收集数据，并使用AI算法智能地诊断出作物和土壤N水平。初步评估显示，与当前做法相比，潜在的成本降低了27％，农场盈利能力增加了17％，排放节省了65％。为了使这项技术对农民进行实用并进一步提高采用，我们旨在提高其TRL并更接近商业化。建立我们的N2Vision创新，我们的后续项目N2Vision+，旨在开发用于自动化的盐氮监测的商业产品，以更高的TRL进行。我们将通过添加可选的模块化传感器，例如3D映射（360度）和土壤问题来增强我们的现有创新，从而实现具有成本效益的数据收集和可扩展的N监视。此外，我们将进行现场试验，以模拟机器人叶面氮的应用，可能降低N使用和成本。这种精确的农业解决方案将通过优化N使用，提高农场的盈利能力并促进零零排放来彻底改变粮食生产。它提供了早期检测作物和土壤N水平，有关N使用效率的精确信息以及土壤质量评估，将英国精确农业技术定位在新行业的最前沿，并推动英国的经济增长。