Combined imaging, spore sensing and robotic application platform, to improve the precision application of fungicides and biopesticides

自20世纪30年代农药广泛商业化以来，农药的使用提高了农业产量，使我们能够养活不断增长的人口。然而，随着人们对这些产品潜在的负面环境影响的认识提高，未来的粮食生产系统将需要继续维持我们的饮食需求，同时使用更少的化学投入。然而，目前不能通过停止使用农药来实现这一目标，因为在我们必须比以往任何时候生产更多粮食的时候，如果没有农药提供的保护，全球产量将减少30-40%。然而，通过利用现代“农业技术”的发展，我们应该有可能通过更有针对性和更及时的方式来减少农药的使用量，以保护我们的作物。许多杀虫剂，特别是杀菌剂（针对作物病害）目前都是采用“基于日历”的方法作为地膜施用于作物。这意味着整个农田都要进行杀菌剂处理，而不管作物本身是否存在病害，或者只对作物的某些部分构成风险。更有针对性的“可变速率”应用目前用于其他作物投入，如化肥，允许使用一小部分化学投入来维持（或增加）产量。然而，目前还不可能将这种“可变速率”方法用于杀菌剂的使用，因为检测和绘制作物病害图在技术上比检测和绘制作物营养胁迫图更具挑战性。在小块农田上以不同的速率准确地施用杀菌剂也是一个障碍，这需要“智能”应用技术。通过结合疾病传感技术、疾病成像能力、喷雾应用科学和基于自主机器人的农业机械发展的最新进展，现在可以设想一个能够应对挑战并推动“精准杀菌剂”应用的端到端系统。目前的项目旨在开发和整合这些领域现有的尖端科学和技术解决方案，以实现当前传统作物化学的这一愿景，并审查其未来提供新兴作物保护产品（如生物农药）的潜力。

Since their widespread commercialisation in the 1930's, the use of pesticides has driven increased yields in agriculture that have allowed us to feed an ever-growing human population. However, with raised awareness of the potentially negative environmental impacts of these products, future food production systems will need to continue to sustain our dietary needs whilst using fewer chemical inputs. This cannot currently be achieved by ceasing pesticide use however, as without the protection they offer global yields would be reduced 30-40% at a time when we must produce more food than ever before. Nevertheless, by utilising modern developments in 'agri-technology' it should be possible to reduce the amount of pesticide that we need to apply to protect our crops by applying it in a more targeted and well-timed manner.Many pesticides, and especially fungicides (that target crop diseases) are currently applied to crops using 'calendar-based' approaches as blanket applications. This means that whole fields are subject to fungicide treatment, regardless of whether crop diseases themselves are present, or only pose a risk in parts of the crop. More targeted 'variable rate' applications are currently used for other crop inputs such as fertilisers, allowing production to be maintained (or increased) using a fraction of the chemical input. However, it is not currently possible to emulate this 'variable rate' approach for fungicide use, as detecting and mapping crop disease is technologically more challenging than detecting and mapping crop nutrient stress. Accurately applying fungicides at different rates to small areas of a crop field is also a barrier, requiring 'smart' application technology.By combining recent advances in disease sensing technology, disease imaging capability, spray application science and autonomous robotics-based farm machinery development, it is now possible to envisage an end-to-end system capable of meeting the challenge and driving forward 'precision fungicide' application. The current project aims to develop and integrate available cutting-edge science and technology solutions in these areas to both realise this vision for current conventional crop chemistry, and review its future potential to deliver emerging crop protection products such as biopesticides.