表面解吸常压化学电离质谱法快速判别樟树化学型

doi:10.7503/cjcu20150684

高等学校化学学报 ›› 2016, Vol. 37 ›› Issue (4): 654.doi: 10.7503/cjcu20150684

表面解吸常压化学电离质谱法快速判别樟树化学型

刘星星¹, 方小伟², 黄学勇¹, 张婷婷¹, 陈焕文², 罗丽萍¹()

1. 南昌大学食品科学与技术国家重点实验室, 南昌 330047
2. 东华理工大学江西省质谱科学与仪器重点实验室, 南昌 330013

收稿日期:2015-09-01 出版日期:2016-04-10 发布日期:2016-01-13
基金资助:
“十二五”农村领域国家科技课题(批准号: 2012BDA29B01-3)、国家自然科学基金(批准号:31370384)、江西省高等学校科技落地计划项目(批准号: KJLD12051)、江西省科技计划项目(批准号:20142BCB24005)和南昌大学食品科学与技术国家重点实验室自由探索课题(批准号: SKLF-ZZB-201516)资助

Rapid Discrimination of Chemotypes of Cinnamomum camphora by Surface Desorption Atmospheric Pressure Chemical Ionization Mass Spectrometry^†

LIU Xingxing¹, FANG Xiaowei², HUANG Xueyong¹, ZHANG Tingting¹, CHEN Huanwen², LUO Liping^1,^*()

1. State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China
2. Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China Institute of Technology, Nanchang 330013, China

Received:2015-09-01 Online:2016-04-10 Published:2016-01-13
Contact: LUO Liping E-mail:lluo2@126.com
Supported by:
† Supported by the “Twelve Five” Issues in Rural Areas of National Science and Technology Plan Project, China(No.2012BDA29B01-3), the National Natural Science Foundation of China(No.31370384), the Floor Plan of Scientific and Technological Projects in Jiangxi Province, China(No.KJLD12051), the Science and Technology Planning Project at the Ministry of Science and Technology of Jiangxi Province, China(No.20142BCB24005) and the Autonomous Research Projects of State Key Laboratory of Food Science and Technology in Nanchang University, China(No.SKLF-ZZB-201516)

摘要/Abstract

摘要：

采用表面解吸常压化学电离质谱(SDAPCI-MS)技术直接对5种化学型的樟树叶粉末片剂进行分析, 获得其化学指纹谱图信息. 采用主成分分析(PCA)、聚类分析(CA)和反向传输人工神经网络(BP-ANN)对谱图信息进行分析, 获得各化学型樟树叶粉末片剂的特征质谱信息, 进而对不同化学型样品进行判别. 结果表明, 在正离子模式下, SDAPCI-MS能快速获取樟树的化学指纹谱图; PCA分析中的PC1, PC2和PC3贡献率分别为79.9%, 12.9%和4.2%, 共计97.0%. SDAPCI-MS结合CA和BP-ANN测试样本准确率均为100%, 能够快速、有效地判别出樟树化学型.

关键词: 樟树, 化学型, 表面解吸常压化学电离质谱, 多变量分析

Abstract:

Surface desorption atmospheric pressure chemical ionization mass spectrometry(SDAPCI-MS) was selected to detect five chemotypes of C. camphora leaves powder and the raw mass spectral fingerprints of the powder samples were obtained. Principal component analysis(PCA), cluster analysis(CA) and the back propagation artificial neural network technology(BP-ANN) were used to analyze the spectral information. The results showed that the SDAPCI-MS technique could got mass spectral fingerprints of C. camphora quickly in positive ion mode. The contribution rates of PC1, PC2, PC3 were 79.9%, 12.9% and 4.2%, respectively, with a total of 97.0% in PCA. The accuracy of discrimination of CA and BP-ANN of SDAPCI-MS was 100%.

Key words: Cinnamomum camphora, Chemotype, Surface desorption atmospheric pressure chemical ionization mass spectrometry(SDAPCI-MS), Multivariate analysis

中图分类号:

O657

TrendMD:

刘星星, 方小伟, 黄学勇, 张婷婷, 陈焕文, 罗丽萍. 表面解吸常压化学电离质谱法快速判别樟树化学型. 高等学校化学学报, 2016, 37(4): 654.

LIU Xingxing, FANG Xiaowei, HUANG Xueyong, ZHANG Tingting, CHEN Huanwen, LUO Liping. Rapid Discrimination of Chemotypes of Cinnamomum camphora by Surface Desorption Atmospheric Pressure Chemical Ionization Mass Spectrometry^†. Chem. J. Chinese Universities, 2016, 37(4): 654.

图/表 8

Fig.1 Schematic illustration of SDAPCI-MS of camphor leaves tablet

Fig.2 SDAPCI-MS spectral fingerprints of 5 chemotypes of C. camphora leaves ^(A) Linalool-type; (B) borneol-type; (C) camphora-type; (D) cineole-type; (E) isoborneol-type.

Fig.3 SDAPCI-MS2(A) and MS3(B) spectra of precursor ions of m/z 153

Fig.4 PCA results of 5 chemotypes of C. camphora leaves using SDAPCI-MS^ Linalool-type; borneol-type; camphora-type; cineole-type; isoborneol-type.

Fig.5 Corresponding PCA loading plots

Fig.6 Dendrogram of cluster analysis ^(A1—A5) Linalool-type; (B1—B5) borneol-type; (C1—C5) camphora-type; (D1—D5) isoborneol-type; (E1—E5) cineole-type.

Fig.7 Training procedure chart of BP network^Best validation performance is 1.0581×10-6 at epoch 110.

Table 1 Accuracy of C. camphora leaves using BP network

Set	Linalool-type		Borneol-type		Camphora-type		Isoborneol-type		Cineole-type
Set	Correct	Error	Correct	Error	Correct	Error	Correct	Error	Correct	Error
Training set	98	0	104	0	103	0	112	0	107	0
Test set	22	0	31	0	24	0	17	0	19	0
Validation set	30	0	15	0	23	0	21	0	24	0
All set	150	0	150	0	150	0	150	0	150	0

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表面解吸常压化学电离质谱法快速判别樟树化学型

Rapid Discrimination of Chemotypes of Cinnamomum camphora by Surface Desorption Atmospheric Pressure Chemical Ionization Mass Spectrometry^†

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表面解吸常压化学电离质谱法快速判别樟树化学型

Rapid Discrimination of Chemotypes of Cinnamomum camphora by Surface Desorption Atmospheric Pressure Chemical Ionization Mass Spectrometry†

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被引次数

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参考文献 34

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Rapid Discrimination of Chemotypes of Cinnamomum camphora by Surface Desorption Atmospheric Pressure Chemical Ionization Mass Spectrometry^†