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Xiaoxia Gao
State Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Guangdong Institute of Microbiology, Guangzhou 510070, PR China
Corresponding Author
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Background: Agarwood is widely used as a traditional medicine all over the world. Distinction between the qualities of natural and artificial agarwood is a current hot research topic among agarwood research communities. An important sensory characteristic of agarwood lies in its incense smoke, and an analysis of incense smoke has been traditionally used to evaluate the agarwood quality since ancient times. The aim of this study is to establish a rapid detection method using electronic nose (E-nose) systems to distinguish between natural and artificial agarwood.
Result: Incense smokes of 45 natural and artificial agarwood samples were analyzed by E-nose, and principal component analysis (PCA) was employed to cluster the E-nose data. The chemical markers which could be used to distinguish between artificial and natural agarwood were identified by GC-MS combined with information value and decision tree algorithm. The results showed that the smellprints of artificial agarwood contained more peaks, while those of natural agarwood had higher response intensities. The compounds that were different between the two types of agarwood were three sesquiterpenes and six chromone derivatives. The result from decision tree algorithm further showed that 6-hydroxy-2-(2-phenylethyl)chromone was the chemical marker that could be used to distinguish between artificial and natural agarwood. Nootkatone and 2-(2-phenylethyl)chromone were the chemical markers that may contributed to the clustering of the E-nose data; the two compounds can be used to evaluate the incense smoke of agarwood.
Conclusion: We demonstrated that our developed E-nose-based method could rapidly distinguish between the incense smokes of artificial and natural agarwood; this method could be applied to evaluate the quality of agarwood in the future.
Keywords
Agarwood, Electronic nose system, GC-MS, Chemical marker, Smellprint
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research
Xiaoxia Gao
State Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Guangdong Institute of Microbiology, Guangzhou 510070, PR China
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 31 Dec, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Agarwood is widely used as a traditional medicine all over the world. Distinction between the qualities of natural and artificial agarwood is a current hot research topic among agarwood research communities. An important sensory characteristic of agarwood lies in its incense smoke, and an analysis of incense smoke has been traditionally used to evaluate the agarwood quality since ancient times. The aim of this study is to establish a rapid detection method using electronic nose (E-nose) systems to distinguish between natural and artificial agarwood.
Result: Incense smokes of 45 natural and artificial agarwood samples were analyzed by E-nose, and principal component analysis (PCA) was employed to cluster the E-nose data. The chemical markers which could be used to distinguish between artificial and natural agarwood were identified by GC-MS combined with information value and decision tree algorithm. The results showed that the smellprints of artificial agarwood contained more peaks, while those of natural agarwood had higher response intensities. The compounds that were different between the two types of agarwood were three sesquiterpenes and six chromone derivatives. The result from decision tree algorithm further showed that 6-hydroxy-2-(2-phenylethyl)chromone was the chemical marker that could be used to distinguish between artificial and natural agarwood. Nootkatone and 2-(2-phenylethyl)chromone were the chemical markers that may contributed to the clustering of the E-nose data; the two compounds can be used to evaluate the incense smoke of agarwood.
Conclusion: We demonstrated that our developed E-nose-based method could rapidly distinguish between the incense smokes of artificial and natural agarwood; this method could be applied to evaluate the quality of agarwood in the future.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
This is a list of supplementary files associated with this preprint. Click to download.
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