A novel method for the analysis of Volatile Organic Compounds (VOCs) from red flour beetle Tribolium castaneum (H.) using Headspace-SPME Technology
Alnajim, I., Agarwal, M.ORCID: 0000-0002-8781-3850, Liu, T. and Ren, Y.
(2020)
A novel method for the analysis of Volatile Organic Compounds (VOCs) from red flour beetle Tribolium castaneum (H.) using Headspace-SPME Technology.
Current Analytical Chemistry, 16
(4).
pp. 404-412.
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Abstract
Background: The red flour beetle, Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae) is one of the world’s most serious stored grain insect pests. A method of early and rapid identification of red flour beetle in stored products is urgently required to improve control options. Specific chemical signals identified as Volatile Organic Compounds (VOCs) that are released by the beetle can serve as biomarkers.
Methods: The Headspace Solid Phase Microextraction (HS-SPME) technique and the analytical conditions with GC and GCMS were optimised and validated for the determination of VOCs released from T. castaneum.
Results: The 50/30 μm DVB/CAR/PDMS SPME fibre was selected for extraction of VOCs from T. castaneum. The efficiency of extraction of VOCs was significantly affected by the extraction time, temperature, insect density and type of SPME fibre. Twenty-three VOCs were extracted from insects in 4 mL flask at 35 ± 1°C for four hours of extraction and separated and identified with gas chromatography-mass spectroscopy. The major VOCs or chemical signals from T. castaneum were 1-pentadecene, p-Benzoquinone, 2-methyl- and p-Benzoquinone, 2-ethyl.
Conclusion: This study showed that HS-SPME GC technology is a robust and cost-effective method for extraction and identification of the unique VOCs produced by T. castaneum. Therefore, this technology could lead to a new approach in the timely detection of T. castaneum and its subsequent treatment.
Item Type: | Journal Article |
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Murdoch Affiliation(s): | School of Veterinary and Life Sciences |
Publisher: | Bentham Science Publishers |
Copyright: | © 2019 Bentham Science Publishers |
URI: | http://researchrepository.murdoch.edu.au/id/eprint/56483 |
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