Fertiliser Use Efficiency with AI

利用人工智能提高肥料使用效率

• 批准号: EP/Y008154/1
• 负责人: Tiina Roose
• 金额: $ 16.19万
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY008154%2F1
• 关键词: Fertiliser; Use; Efficiency; AI

One of the biggest challenges facing the agricultural industry is achieving high yields with the use of fertilisers while simultaneously minimising the environmental side effects of the fertiliser application and production. In this highly weather-reliant industry, developing weather-dependent fertilisation strategies will help maintain crop production and reduce the greenhouse gas (GHG) emissions in the face of climate change. This is particularly important for phosphorus and nitrogen (P&N) fertilisers, which have a high environmental footprint in terms of GHG emissions and pollution. One approach to achieving this goal is by harnessing new computational technologies within a precision agriculture framework.In the first six months of 2022, fertiliser prices have significantly increased and in some cases tripled. These prices are likely to remain volatile; the increases are largely driven by disruptions to the production due to climate change (warming, droughts etc) and geopolitics (energy/gas supply, war in Ukraine etc). In addition, the Haber-Bosch process for nitrogen fertiliser production is at best of times a highly energy consuming process responsible for 1.2% of the global energy usage. While there are worldwide efforts to deal with climate change, the climate is expected to remain volatile for the foreseeable future. Computer simulations are a valuable tool for considering climate volatility, as they allow for the testing of different soil/crop management approaches under different climate scenarios. Computer simulations/models for fertiliser use efficiency (FUE) allow for fast and cheap testing of different scenarios as part of the multifaceted decision making process for fertilisation applications. Approaches to enhance FUE address at least one of the 4R's of FUE: right type of fertiliser, right rate, right time and right place of application. My ERC Consolidator Grant (CoG) DIMR-646809 created new mathematical models, which now allow us to start tackling these issues.

农业面临的最大挑战之一是通过使用化肥实现高产，同时最大限度地减少化肥施用和生产对环境的副作用。在这个高度依赖天气的行业中，开发依赖天气的施肥策略将有助于在气候变化的情况下保持作物产量并减少温室气体（GHG）排放。这对于磷和氮（P&N）肥料尤其重要，因为它们在温室气体排放和污染方面具有很高的环境足迹。实现这一目标的方法之一是在精准农业框架内利用新的计算技术。2022年前六个月，化肥价格大幅上涨，在某些情况下上涨了两倍。这些价格可能会保持波动;上涨主要是由于气候变化（变暖，干旱等）和地缘政治（能源/天然气供应，乌克兰战争等）造成的生产中断。此外，用于氮肥生产的哈伯-博世工艺在最好的情况下也是一种高能耗工艺，占全球能源使用量的1.2%。虽然全世界都在努力应对气候变化，但在可预见的未来，气候预计仍将不稳定。计算机模拟是考虑气候波动性的一个宝贵工具，因为它们允许在不同的气候情景下测试不同的土壤/作物管理方法。肥料利用效率（FUE）的计算机模拟/模型允许对不同情况进行快速和廉价的测试，作为施肥应用多方面决策过程的一部分。提高肥料利用效率的方法至少涉及肥料利用效率的4 R之一：正确的肥料类型、正确的施用率、正确的施用时间和正确的施用地点。我的ERC Consolidator Grant（CoG）DIMR-646809创建了新的数学模型，现在可以让我们开始解决这些问题。