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Dissertation
Identifying biomarkers of Little Cherry/X-disease in Prunus avium using volatile sensing technologies.
Doctor of Philosophy (PhD), Washington State University
2024
Abstract
Little cherry disease (LCD)/X-disease has been critically affecting the production and marketability of sweet cherry (Prunus avium) crop grown in the Pacific Northwest. Infected trees produce small, light colored, misshaped and bland tasting fruits. Insect vector management and removal of the symptomatic trees are the only mitigation strategies to manage the disease. Hence, technologically sound methods are needed for early stage and rapid disease symptoms detection. This is a major drawback with existing detection methods that rely on subjective visual scouting or laborious laboratory molecular analysis. This dissertation thus focuses on exploring the suitability of volatile headspace sampling techniques namely, field asymmetric ion mobility spectrometry (FAIMS) and thermal desorption gas chromatography-mass spectrometry (GC-MS), for LCD/X-disease linked biomarkers identification in key sweet cherry cultivars (‘Bing’, and ‘Skeena’). FAIMS analysis of volatile headspace from symptomatic and asymptomatic samples across cultivars (‘Benton’, ‘Cristalina’, ‘Tieton’) showed higher ion currents in infected samples and had signature peak that can potentially be used for rapid detection. Static headspace sampling driven GC-MS analysis identified key volatiles such as ethanol, E-2-hexenal, propanoic acid, and acetone differentiating symptomatic and asymptomatic trees for the Bing cultivar. Whereas for Skeena cultivar, the key volatile biomarkers were E-2-hexenal, Z-3-hexen-1-ol, acetaldehyde, acetoin and methanol. Dynamic headspace sampling with GC-MS effectively identified key volatiles but showed a weak correlation with titer levels, possibly due to the sample tissue type and sampling approach. Further research is warranted to further evaluate volatile sensing-based techniques for LCD/X-disease detection in other commercially critical cherry cultivars and also robust validation with healthy control samples. Overall, outcomes from this dissertation would help in developing rapid sensing technologies and/or training canines for early-stage detection of X-disease/LCD infestation.
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Details
- Title
- Identifying biomarkers of Little Cherry/X-disease in Prunus avium using volatile sensing technologies.
- Creators
- Gajanan Suryakant Kothawade
- Contributors
- Lav R. Khot (Advisor)Scott J. Harper (Committee Member)Kirti Rajagopalan (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Department of Biological Systems Engineering
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Number of pages
- 156
- Identifiers
- 99901393898901842
- Language
- English
- Resource Type
- Dissertation