When plants are infected with pathogens, disease response can result in changes in the profiles of volatile organic compounds (VOC). These changes in volatile organic compounds (VOC) profiles can be utilized for disease detection and quantification. In this study, field asymmetric ion mobility spectrometry (FAIMS) was used to evaluate the VOC profile variability in a pea near isogenic line (Pisum sativum L.) inoculated with zoospores of Aphanomyces euteiches Drechs, which causes Aphanomyces root rot disease. Pots were filled with silica sand and six plants per pot were grown under controlled conditions in a randomized complete block design with four replications. Four treatments, namely non-inoculated, 1 × 105, 1 × 106, and 2.79 × 106 zoospores ml−1 were applied to plants at 5 and 7 days after emergence. FAIMS was used to collect volatile profiles at 2, 4, 7 and 9 days after inoculation. Specific regions of interest – extracted from the ion current intensity from the FAIMS spectra – were analyzed using ANOVA. Similarly, multiple regions of interest were evaluated using principal component analysis and k-means clustering. Ion current profiles and curvature profiles were incorporated into the analysis using k-means clustering. Other ground reference data such as root rot index and physiological parameters were also recorded. The results showed a biomarker in a specific region of interest demonstrating ample ability to quantify and differentiate treatment effects during non-destructive sampling at 14 DAE (7 DAI). Data from this region could be used for early and non-destructive quantification and differentiation of treatment effects based on zoospore inoculation levels. The k-means clustering of ion current and curvature profiles showed patterns based on the treatments. These findings demonstrated that FAIMS could be used as a tool to assess plant-pathogen interactions using volatile biomarkers to evaluate disease responses and severity under controlled conditions.

中文翻译：

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基于现场不对称离子淌度谱的豌豆Aphanomyces 根腐病评估优化


当植物感染病原体时，疾病反应会导致挥发性有机化合物 （VOC） 的概况发生变化。挥发性有机化合物 （VOC） 谱的这些变化可用于疾病检测和定量。在这项研究中，现场不对称离子迁移谱 （FAIMS） 用于评估接种 Aphanomyces euteiches Drechs 游动孢子的豌豆近等基因线 （Pisum sativum L.） 的 VOC 谱变异性，这会导致 Aphanomyces 根腐病。花盆装满硅砂，每盆六株植物在受控条件下以随机完全区组设计种植，有四次重复。在出苗后 5 天和 7 天，将未接种、1 × 105、1 × 106 和 2.79 × 106 个游动孢子 ml-1 四种处理施用于植物。FAIMS 用于收集接种后 2 、 4 、 7 和 9 天的挥发性谱。使用方差分析分析特定感兴趣区域 – 从 FAIMS 光谱的离子电流强度中提取 – 。同样，使用主成分分析和 k-means 聚类评估了多个感兴趣区域。使用 k-means 聚类将离子电流曲线和曲率曲线纳入分析中。还记录了其他地面参考数据，如根腐病指数和生理参数。结果显示，在特定感兴趣区域的生物标志物在 14 DAE （7 DAI） 的无损采样期间表现出足够的量化和区分治疗效果的能力。来自该区域的数据可用于基于游动孢子接种水平的早期和无损量化和区分处理效果。离子电流和曲率剖面的 k-means 聚类显示了基于处理的模式。 这些发现表明，FAIMS 可以用作使用挥发性生物标志物评估植物-病原体相互作用的工具，以评估受控条件下的疾病反应和严重程度。