NOVEL DIGITAL HEALTH PLATFORM FOR PRECISION FARMING

粮食安全是人类面临的全球性挑战之一。到2050年，全球粮食产量必须增加50%，才能养活100亿人（世界资源研究所，2018年）。与此同时，气候变化加剧了对农田的压力，降低了农业生产率，使世界更接近粮食安全危机。在英国，由于生物和非生物胁迫，每年在田间损失62,000吨土豆（EIT Food, 2011）。据估计，英国每年因马铃薯损失超过1亿英镑。农药的使用不能为作物提供充分的保护，成本高，不可持续，而非生物胁迫的不可预测性日益增加，使农民没有时间做出反应。因此，有必要通过更有针对性地使用农业投入，快速查明病害和非生物胁迫，以便更有效地管理作物和减少作物损失。FITOvol有限公司的成立就是为了应对这一挑战。FITOvol寻求通过开发快速的非侵入性作物胁迫检测诊断工具来减少作物损失，这些工具可由农民在田间使用其专有技术平台。它得到了杜伦大学（DU）、杜伦城市孵化器（DCI）和北方加速器的支持，并可以使用杜伦大学最先进的设施。我们的团队结合了世界领先的专家和鼓舞人心的年轻领导者，体现了跨代的伙伴关系。该项目将开发一个基于图像的识别诊断平台，该平台将由一个简单的相机（例如智能手机）和一个由我们的深度学习模型驱动的应用程序组成。这一创新解决方案将为目前的作物胁迫诊断方法提供一种补充方法，并使农民能够在不需要额外专业知识的情况下评估作物健康状况。它将实现作物管理的实时决策，并成为精准农业的宝贵资源（估计到2025年价值95亿英镑）。成功将导致在前3年的销售中产生约100万英镑的累计收入，创造2个就业机会，产生新的技术诀窍，并引入一种新的植物健康诊断方法，对英国农业产生潜在的非常重大的经济和社会影响。

Food security is one of the global challenges facing humanity. By 2050, 50% more food must be produced globally to feed 10B people (WRI, 2018). Meanwhile, climate change is aggravating the stresses on fields, lowering agricultural productivity and pushing the world closer to a food security crisis. In the UK 62,000 tonnes of potatoes are lost annually in the field due to both biotic and abiotic stresses (EIT Food, 2011). Annual potato losses in the UK are estimated at over £100M. The application of pesticides does not offer full protection to crops, incurs high costs and is unsustainable, whilst the increasing unpredictability of abiotic stresses don't allow farmers time to react. Thus, there is a need for rapid disease and abiotic stress identification for a more efficient crop management and crop loss reduction, through a more targeted use of agricultural inputs.FITOvol Ltd was established to address this challenge. FITOvol seeks to reduce crop losses by developing rapid non-invasive diagnostic tools for crop stress detection that can be used by farmers in the field using its proprietary technology platform. It is supported by Durham University (DU), Durham City Incubator (DCI) and Northern Accelerator and has access to DU's state of the art facilities. Its team combines the world leading experts and inspiring young leaders and embodies a cross-generation partnership.The project will develop an image-based recognition diagnostic platform that will consist of a simple camera (e.g. smartphone) and an app powered by our deep learning model.This innovative solution will offer a complementary approach to the current crop stress diagnostic methods and empower farmers to assess crop health without requiring additional expertise. It will enable real-time decision-making for crop management and become a valuable resource for precision farming (estimated £9.5B for 2025).Success will result in the generation of cumulative revenues of ca. £1M over the first 3 years of sales, 2 jobs created, generation of new know-how and introducing a novel plant health diagnostic with potentially very significant economic and social impact to the UK agriculture industry.