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Research Project: Integrated Pest Management of Cattle Fever Ticks

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Title: Raman-based identification of tick species (Ixodidae) by spectroscopic analysis of their feces

Author
item DOU, TIANYI - Texas A&M University
item ERMOLENKOV, ALEXEI - Texas A&M University
item HAYS, SAM - Texas A&M University
item RICH, BRIAN - Texas A&M University
item DONALDSON, TAYLOR - Texas A&M University
item Thomas, Donald
item TEEL, PETE - Texas A&M University
item KUROUSKI, DIMITRY - Texas A&M University

Submitted to: Analytical Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/25/2022
Publication Date: 4/15/2022
Citation: Dou, T., Ermolenkov, A., Hays, S., Rich, B., Donaldson, T., Thomas, D.B., Teel, P., Kurouski, D. 2022. Raman-based identification of tick species (Ixodidae) by spectroscopic analysis of their feces. Analytical Chemistry. https://doi.org/10.1016/j.saa.2022.120966.
DOI: https://doi.org/10.1016/j.saa.2022.120966

Interpretive Summary: In this study, we investigated the possibility of identification of tick species based on chemicals in their poop. For this, poop from seven different species of ticks was analyzed. Results show that a method called "Raman spectroscopy" (RS) identified differences in chemical composition among tick species. Additionally, we calculated the odds of correctly identifying poop to each species as better than 98% accuracy. Potential applications and future work to explore this technique for tick surveillance are discussed.

Technical Abstract: ABSTRACT: In this study, we investigated the possibility of identification of tick species (Ixodidae) based on spectroscopic signatures of their feces. For this, multiple spectra were collected from individual grains of feces of seven different species of ticks. Results show that Raman spectroscopy (RS) identified spectral differences in chemical composition of these excrements between tick species. Additionally, using chemometric methods, we distinguished between these different tick species with high accuracy. Potential applications and future work to explore RS for tick surveillance are discussed.