Detection of huanglongbing disease using differential mobility spectrometry

Alexander A. Aksenov, Alberto Pasamontes, Daniel J. Peirano, Weixiang Zhao, Abhaya M. Dandekar, Oliver Fiehn, Reza Ehsani, Cristina E Davis

Research output: Contribution to journalArticlepeer-review

66 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)2481-2488
Number of pages8
JournalAnalytical Chemistry
Volume86
Issue number5
DOIs
StatePublished - Mar 4 2014

ASJC Scopus subject areas

  • Analytical Chemistry

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