Feasibility of using 3D MultiSpectral Imaging for enhanced classification of fruit ripeness and disease

鉴于果农越来越难找到手工采摘软果的工人，人们越来越需要开发水果的自动采摘系统。本项目的重点是评估3D多光谱成像系统在自动拾取系统中使用的优势和适用性。减少采摘水果的体力劳动将反过来要求自动化系统也需要在叶片和水果的疾病监测中发挥作用。使用3D成像的新传感器的开发可能会检测到症状前期疾病的存在，并改善水果收获的调度。该项目将利用Rothamsted Research的评估专业知识和英国农业技术中心之一的作物健康与保护有限公司(CHAP)的设施和设备，评估这种新的传感器技术在实验室和田间水果种植应用中的可行性，并与现有技术进行比较。该项目将试验和测试一种创新的3D成像工具，以探索其确定关键作物和水果成熟过程中疾病最初发展的潜力。这也将对果农、研究人员和需要表型鉴定的植物育种者有用。

In light of the increasing difficulty for fruit farmers to source manual workers to pick soft fruits, there is an increasing need for the development of automatic picking systems, for fruit. This project is focused on assessing the advantages and suitability of a 3D multiSpectral imaging system for use in automatic picking systems. A reduction in manual labour to pick fruit will in turn require that an automated system also needs to play a role in disease surveillance on leaves and fruit. The development of new sensors using 3D imaging may allow detection of pre-symptomatic disease presence and improve the scheduling of fruit harvesting. The project is to assess the feasibility of this new sensor technology with both laboratory and field fruit growing applications and compare to existing technology, using the assessment expertise of Rothamsted Research and the facilities and equipment of Crop Health and Protection Ltd (CHAP) - one of the UK Agri Tech centres This project will trial and test an innovative 3D imaging tool to explore its potential to determine the initial development of diseases in key crops and fruit ripening. This will also be of use to fruit growers, researchers and plant breeders requiring phenotyping.