Non-Destructive Detection of Below-Ground Plant Pathogens: VOC Profiling by Frequency Comb Spectroscopy

病虫害研究对于实现确保粮食安全的目标至关重要。空中病虫害更容易量化和识别。然而，检测和确定土壤传播生物的病原体负担要困难得多。植物寄生线虫就是一个例子，它对全世界的植物生产力造成了毁灭性的影响。这既是研究上的问题，也是该领域的战略问题。目前的采样方法耗时、破坏性大、成本高。迫切需要新的检测方法来加快对这些病原体的研究。植物寄生线虫是对全球农业生产的重要威胁。尽管如此，作为土壤传播的病原体，植物寄生线虫通常诊断不足。线虫表现出广泛的寄生策略。一些在植物根部移动时具有破坏性，而另一些则对根细胞进行重新编程，形成一种新的营养汇，可以持续数周。这些不同的寄生策略导致不同程度的植物直接伤害和植物生理变化，因此可能引起不同的植物反应。因此，植物寄生线虫是一个很好的病理系统，围绕它可以开发和测试一种新的植物疾病检测和诊断系统。挥发性有机化合物（VOCs）是所有陆地和海洋生态系统中生物体排放的大量化学物质。植物释放的挥发性有机化合物的化学成分及其丰度可以携带有关植物生理状态和所受胁迫的信息。挥发性有机化合物是植物防御系统的重要组成部分，是对害虫和病原体攻击的反应。我们已经确定植物对植物寄生线虫的感染会释放挥发性有机化合物，并建议开发新的技术来检测和监测挥发性有机化合物，以建立线虫感染的挥发性有机化合物“指纹”。红外光谱就像一种化学“指纹”机制，因为每个分子都能在特定的、独特的频率上吸收红外光。然而，植物排放的挥发性有机化合物通常处于十亿分之一（ppb）的低水平，这可能会测试仪器灵敏度的极限，并且不同挥发性有机化合物的红外光谱重叠可能是低光谱分辨率技术的一个问题。本文将建立一种新型频率梳状激光-傅里叶变换红外光谱仪（FC-FTIR），利用较长的相互作用路径长度，利用同时宽带和高分辨率红外激光的分子选择性，达到必要的ppb级分子灵敏度。因此，用FC-FTIR收集的红外光谱可以获得有关植物挥发性有机化合物排放的总体概况，甚至是挥发性有机化合物的身份和数量的信息。健康植物与受感染植物VOC排放谱的统计分析将有助于确定植物的相对健康状况，并可能将排放谱与特定植物病原体联系起来。这项工作解决了当前需要发展一种既敏感又有选择性的技术，以便识别在不同病原体负荷下排放的植物挥发性有机化合物的概况，同时仍然足够普遍，以检测所有可能排放的挥发性有机化合物（即不针对基于假设的植物疾病的特定挥发性有机化合物组成）。这项技术有可能以一种非破坏性的方式实时识别各种植物病原体。因此，它对植物科学和其他领域的广泛生物学科产生了影响。理想情况下，由于使用相干光源的高度方向性，该仪器还能够监测田间VOC概况，以便在作物内定位受感染区域，确保快速响应补救行动，从而最大限度地减少感染影响并减轻作物损失。

Research into pests and diseases is essential to fulfil the goal of ensuring food security. Aerial pests and disease are easier to quantify and identify. However, the detection and determination of the pathogen burden is far more difficult for soil-borne organisms. An example are the plant parasitic nematodes that have devastating impacts on plant productivity throughout the world. This is an issue both in research and strategically in the field. Currently sampling methods are time consuming, destructive and costly. New methods of detection are urgently required to speed up research into these pathogens.Plant parasitic nematodes represent an important global threat to agricultural production. Despite this, as soil-borne pathogens plant parasitic nematodes are classically under-diagnosed. The nematodes display a wide range of parasitic strategies. Some feed destructively as they move through plant roots whilst others reprogramme root cells to form a novel nutrient sink from which they feed for many weeks. These diverse parasitic strategies result in differing levels of direct plant damage and changes to plant physiology and thus are likely to elicit different plant responses. Plant parasitic nematodes are therefore an excellent patho-system around which to develop and test a novel system for detection and diagnosis of plant disease. Volatile organic compounds (VOCs) are abundant chemicals that are emitted by organisms in all terrestrial and marine ecosystems. The chemical composition of plant-emitted VOCs and their abundance can carry information about the plants' physiological status and the stresses to which they have been subjected. VOCs are an essential part of plant defense systems and are emitted in response to pest and pathogen attack. We have established that plants release VOCs in response to infection by plant-parasitic nematodes and propose to develop new technology to detect and monitor VOCs in order to establish a VOC 'fingerprint' for nematode infection. Infrared spectroscopy acts as a chemical 'fingerprinting' mechanism since every molecule that can absorb infrared light does so at specific, unique frequencies. However, VOCs emitted by plants are oftentimes in the low parts-per-billion (ppb) levels, which can test the limits of instrumentation sensitivity, and the overlapping infrared spectra of different VOCs can be an issue for low spectral resolution techniques. A new frequency comb laser-Fourier transform infrared spectrometer (FC-FTIR) will be built to reach the necessary ppb level molecular sensitivities by using a long interaction path length, with the molecular selectivity being a result of the simultaneously broadband and high resolution infrared laser. Thus, the infrared spectra collected with FC-FTIR can yield information about an overall profile of plant VOCs emitted, and even the identity and quantity of the VOCs. Statistical analysis of healthy versus infected plant VOC emission profiles will aid in determining the relative health of the plant and potentially linking the emission profile to a specific plant pathogen. This work addresses the current need to move towards a technology that is both sensitive and selective in order to identify a profile of plant VOCs emitted under different pathogen burdens, while still being general enough to detect all possible emitted VOCs (i.e. not targeting a specific VOC composition based on an assumed plant disease). This technology potentially allows the identification of a broad range of plant pathogens in a non-destructive manner, in real time. It therefore has impact across a wide range of biological disciplines in plant science and beyond. Ideally, this instrument would also be able to monitor VOC profiles in the field in order to locate infected areas within crops because of the highly directional nature of using a coherent light source, ensuring a rapid response for remedial action thus minimizing infection impact and mitigating crop loss.