An optical detector for latent fungal infection in produce

食物浪费是一个重大问题，会对环境和经济产生巨大影响。造成浪费的一个重要原因是真菌感染。理想情况下，被感染的水果应该尽快从储存中取出，以防止感染的传播和潜在的整个商店的损失。然而，真菌感染在其早期阶段通常是潜伏的，这意味着它们是不活跃的离子或仅在表面以下，无法在早期阶段检测到，例如在水果储存之前。这些潜伏感染在贮藏过程中进展迅速，感染扩散到邻近的农产品，造成重大损失。如果有一种可靠的方法来检测这种潜伏感染，就有可能显著减少浪费。高分辨率光学成像方法在医学上作为一种检测疾病的手段已经显示出巨大的前景，通常是在早期阶段。因此，将这项技术转化为农业的潜力是显而易见的。特别是，光学相干断层扫描允许在大约一秒的时间尺度内获得3D图像，穿透1-2毫米进入组织。它提供的结构信息分辨率小于10微米（0.01毫米），无需破坏性采样，染色或以任何方式制备样品。然而，尽管OCT在植物和水果成像方面有一定的应用前景，但它提供的简单结构信息可能无法提供与潜在真菌感染相关的细微变化的可靠检测。在这个项目中，我们将研究和展示一种早期检测水果真菌感染的新方法。我们将把肯特大学应用光学组在光学成像系统设计和开发方面的专业知识与NIAB EMR病虫害和病原体生态学团队的园艺和植物病理学专业知识结合起来。我们将开发一种新的成像设备，用于检测潜伏的早期真菌感染，并使用已知携带真菌念珠菌的樱桃样品进行测试。该设备的物理原理与传统OCT的基本结构相似，使用激光扫描探头、宽带光源和快速光谱仪的组合来实现快速3D成像。然而，与传统OCT提供样本结构的静态快照不同，新的调查模式将基于OCT领域的最新发展用于生物医学诊断。在获取多种形式的功能或动态信息的基础上，这些将用于对水果样品进行更精细的分析，包括观察样品的微观结构如何对外部机械刺激作出反应，以及测量细胞成分规模上的内在波动的幅度和频率。这三种技术，即光学相干弹性成像（OCE）、散斑方差（SV）和新兴的动态OCT （DyOCT）将在单个设备中实现，从而可以对水果进行全面评估。光学工具（OCT， OCE， SV, DyOCT）的灵敏度和准确性将使用破坏性方法进行基准测试，例如活病原体的分离，荧光显微镜的定位和定量PCR的真菌生物量。

Food waste is a major problem, with huge environmental and economic impact. A significant cause of waste are fungal infections. Ideally, fruit that has been infected should be removed from storage as soon as possible to prevent spread of the infection and potentially the loss of the entire store. However, fungal infections are often latent in their early stages, meaning they are inactive ion or just below the surface and cannot be detected at an early stage, e.g. before the fruit is stored. These latent infection can quickly progress during the storage, infection spreading to the neighbouring produce causing significant losses. If there was a reliable method to detect this latent infection, there is potential to significantly reduce wastage.High-resolution optical imaging methods have shown huge promise in medicine as a means of detecting disease, often at an early stage. There is therefore an obvious potential to translate this technology to agriculture. In particular, optical coherence tomography allows 3D images to be acquired in timescales of around a second, penetrating 1-2 mm into tissue. It provides structural information down to a resolution of less than 10 microns (0.01 mm) without the need for destructive sampling, staining or preparation of the sample in any way. However, while OCT has shown some promise for imaging plants and fruit for some applications, the simple structural information it provides may not provide reliable detection of the subtle changes associated with latent fungal infection.In this project we will investigate and demonstrate a new approach for early detection of fungal infection in fruits. We will bring together the expertise in the design and development of optical imaging systems at the Applied Optics Group, University of Kent, with the horticulture and plant pathology expertise of the Pest and Pathogen Ecology team at NIAB EMR. We will develop a new imaging device designed for the detection of latent, early stage fungus infection and test it using cherry samples known to be carrying the fungus Monilinia laxa.The physical principles of the device will be similar in its elementary structure to the conventional OCT, using a combination of a laser-scanning probe head, a broadband optical source and a fast spectrometer to allow fast 3D imaging. However, unlike in conventional OCT, which provides a static snapshot of the structure of the sample, new investigative modalities will be harnessed based on recent developments in the OCT field for biomedical diagnosis. These will be implemented to perform a more subtle analysis of fruit samples, based on acquiring multiple forms of functional or dynamic information, including looking at how the microstructure of the sample responds to an external mechanical stimulus, and measuring both the magnitude and the frequency of intrinsic fluctuations on the scale of cellular components. These three techniques, known as optical coherence elastography (OCE), speckle variance (SV), and the newly emerging dynamic OCT (DyOCT) will be implemented in a single device, allowing the fruit to be comprehensively evaluated.The sensitivity and accuracy of the optical tools (OCT, OCE, SV, DyOCT) will be benchmarked using destructive methods such as isolation of live pathogen, localisation using fluorescent microscopy and quantification of fungal biomass with quantitative PCR.