Mechanical and Aerospace Engineering, University of California , Davis, California 95616, United States.
Anal Chem. 2014 Mar 4;86(5):2481-8. doi: 10.1021/ac403469y. Epub 2014 Feb 12.
The viability of the multibillion dollar global citrus industry is threatened by the "green menace", citrus greening disease (Huanglongbing, HLB), caused by the bacterial pathogen Candidatus Liberibacter. The long asymptomatic stage of HLB makes it challenging to detect emerging regional infections early to limit disease spread. We have established a novel method of disease detection based on chemical analysis of released volatile organic compounds (VOCs) that emanate from infected trees. We found that the biomarkers "fingerprint" is specific to the causal pathogen and could be interpreted using analytical methods such as gas chromatography/mass spectrometry (GC/MS) and gas chromatography/differential mobility spectrometry (GC/DMS). This VOC-based disease detection method has a high accuracy of ∼90% throughout the year, approaching 100% under optimal testing conditions, even at very early stages of infection where other methods are not adequate. Detecting early infection based on VOCs precedes visual symptoms and DNA-based detection techniques (real-time polymerase chain reaction, RT-PCR) and can be performed at a substantially lower cost and with rapid field deployment.
价值数十亿美元的全球柑橘产业正受到“绿色威胁”——由细菌病原体黄龙病菌（HLB）引起的柑橘绿化病的威胁。HLB 的无症状潜伏期很长，因此难以早期发现新出现的区域性感染，从而限制疾病的传播。我们已经建立了一种基于感染树木释放的挥发性有机化合物（VOCs）化学分析的新型疾病检测方法。我们发现，生物标志物“指纹”是针对致病病原体的，并且可以使用分析方法（如气相色谱/质谱法（GC/MS）和气相色谱/差分迁移率光谱法（GC/DMS）进行解释。这种基于 VOC 的疾病检测方法在一年中的准确率约为 90%，在最佳测试条件下接近 100%，甚至在其他方法不充分的早期感染阶段也是如此。基于 VOC 的早期感染检测先于视觉症状和基于 DNA 的检测技术（实时聚合酶链反应（RT-PCR）），并且可以以更低的成本和快速的现场部署进行。
