Discrimination of wood-boring beetles infested Platycladus orientalis plants by using gas chromatography-ion mobility spectrometry
Platycladus orientalis plants in China are experiencing a serious problem with wood-boring beetles, but conventional physical detection methods cannot perform well due to hidden larvae and less obvious symptoms in the early infestation. In this study, the volatile organic compounds (VOCs) of P. orientalis were investigated using gas chromatography-ion mobility spectrometry (GC-IMS) to identify its internal infestation. An image-based evaluation method of the degree of internal wood damage was proposed, the principal component analysis (PCA) based on specific markers was applied for natural clustering of samples, and unsupervised learning approaches based on specific markers and automatically located peaks were used to create predictive models for sample classification. The results showed that the herbivore-induced plant volatiles (HIPVs) of P. orientalis samples had two main characteristics compared with undamaged plants. One was the emergence of several compounds such as C 3 -C 6 ketones, aldehydes, and alcohols, while the other was the obvious content variation of several monoterpenes and their derivatives. The classification models based on specific markers and automatically located peaks could correctly classify at least 89.5% and 87.9% of the samples, respectively. In a word, these results proved that GC-IMS based approaches combined with different feature extraction methods have the potential to identify the internal infestation of wood-boring beetles in P. orientalis .
危险品化学品经营许可证（带存储）