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电子鼻联合化学计量学鉴别沉香精油的不同产地及提取方式

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中草药 | 药剂与工艺 2026,57(11): 4135-4146

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中草药 |药剂与工艺 2026 , 57 (11) : 4135 -4146

电子鼻联合化学计量学鉴别沉香精油的不同产地及提取方式

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李慧婷¹, 潘登¹, 黄小英¹, 余思嫒¹, 龚梦雅¹, 何华¹, 陈义¹, 杨明¹

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通讯作者:

陈义

作者简介:

李慧婷: 李慧婷，讲师，博士，从事中药新剂型、新技术、新工艺研究。Tel:(0791)87118658 E-mail:lihuiting19@163.com

Identification of Aquilariae Lignum Resinatum essential oils from different origins and extraction methods using electronic nose combined with chemometrics

LI Huiting, PAN Deng, HUANG Xiaoying, YU Siai, GONG Mengya, HE Hua, CHEN Yi, YANG Ming

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doi: 10.7501/j.issn.0253-2670.2026.11.006

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目的采用电子鼻联合化学计量学方法，系统分析不同产地及提取方式沉香Aquilariae Lignum Resinatum精油的挥发性成分差异，旨在构建一种快速鉴别沉香精油来源与提取工艺的新方法。方法收集来自7个主要产地、2种提取方式的38批沉香精油样品，采用气相色谱-质谱联用（gas chromatography-mass spectrometry，GC-MS）技术解析其化学组成，并利用电子鼻获取其整体香气指纹信息。综合运用主成分分析（principal component analysis，PCA）、偏最小二乘-判别分析（partial least squares-discriminant analysis，PLS-DA）及正交偏最小二乘-判别分析（orthogonal partial least squares-discriminant analysis，OPLS-DA）对多源数据进行模式识别。结果 GC-MS分析表明所有样品的共有主要成分为苄基丙酮、沉香螺醇、去氢呋喃酮和2-(2-苯乙基)色酮。通过变量重要性投影（variable importance projection，VIP＞1）筛选出2-(2-苯乙基)色酮、6-甲氧基-2-(2-苯乙基)色酮等7种关键差异性化合物。电子鼻响应值数据的PCA结果显示，能较好地与沉香精油样本的产地或提取方法进行关联；所建立的OPLS-DA判别模型性能优异，产地判别模型RX²＝0.839，RY²＝0.794，Q²＝0.572＞0.500，提取方式判别模型RX²＝0.790，RY²＝0.647，Q²＝0.633＞0.500，能有效对沉香精油进行分类。结论成功将电子鼻快速判别与GC-MS成分分析相结合，证实该联合策略能准确鉴别沉香精油的提取方法与产地，并明确了其物质基础，为沉香精油的分类鉴别提供了一种高效、可靠的新方法。

关键词

沉香精油 / 电子鼻 / 化学计量学 / 产地 / 提取方式 / GC-MS / 主成分分析 / 偏最小二乘-判别分析 / 正交偏最小二乘-判别分析 / 苄基丙酮 / 沉香螺醇 / 去氢呋喃酮 / 2-(2-苯乙基)色酮 / 变量重要性投影

Abstract

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Objective To systematically analyze the differences in volatile components of Chenxiang (Aquilariae Lignum Resinatum) essential oil (AEO) from various origins and extraction methods using an electronic nose combined with chemometrics, aiming to establish a novel method for rapid identification of AEO origins and extraction processes. Methods A total of 38 batches of AEO samples were collected from seven major origins using two extraction methods. Their chemical compositions were analyzed using gas chromatography-mass spectrometry (GC-MS), while overall aroma fingerprint information was obtained via electronic nose. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were comprehensively applied for pattern recognition of multi-source data. Results GC-MS analysis revealed that the common major components in all samples were benzylacetone, agarospirol, dehydrofuranone, and 2-(2-phenylethyl)chromone. Seven key differential compounds, including 2-(2-phenylethyl)chromone and 6-methoxy-2-(2-phenylethyl)chromone, were screened through variable importance projection (VIP > 1). The PCA results of the electronic nose response values show a good correlation with the origin or extraction method of AEO samples. The established OPLS-DA discriminant model exhibited excellent performance: the origin discriminant model achieved R_X² = 0.839, R_Y² = 0.794, Q² = 0.572 > 0.500, and the extraction method discriminant model achieved R_X² = 0.790, R_Y² = 0.647, Q² = 0.633 > 0.500, which can effectively classify AEO samples. Conclusion This study successfully combined the rapid identification of electronic nose with GC-MS component analysis, which confirmed that the combined strategy could accurately identify the extraction method and geographical origins of AEO, and clarified its material basis, providing an efficient and reliable new method for the classification and identification of AEO.

Key words

Aquilariae Lignum Resinatum essential oil / electronic nose / chemometrics / origin / extraction method / GC-MS / principal component analysis / partial least squares-discriminant analysis / orthogonal partial least squares-discriminant analysis / benzylacetone / agarospirol / dehydrofuranone / 2-(2-phenylethyl)chromone / variable importance projection

引用本文

李慧婷, 潘登, 黄小英, 余思嫒, 龚梦雅, 何华, 陈义, 杨明. 电子鼻联合化学计量学鉴别沉香精油的不同产地及提取方式. 中草药, 2026 , 57 (11) : 4135 -4146 . DOI: 10.7501/j.issn.0253-2670.2026.11.006

LI Huiting, PAN Deng, HUANG Xiaoying, YU Siai, GONG Mengya, HE Hua, CHEN Yi, YANG Ming. Identification of Aquilariae Lignum Resinatum essential oils from different origins and extraction methods using electronic nose combined with chemometrics[J]. Chinese Traditional and Herbal Drugs, 2026 , 57 (11) : 4135 -4146 . DOI: 10.7501/j.issn.0253-2670.2026.11.006

基金

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江西省“赣鄱英才”创新领军人才项目 (gpyc20240037); 江西省自然科学基金资助项目 (20242BAB20456); 国家自然科学基金资助项目 (82404878); 海南省重点研发项目 (ZDYF2025SHFZ055); 江西中医药大学博士科研启动基金项目 (2024BSZR016); 江西中医药大学中药科研实践创新训练项目 (24KYCX-ZD014)

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2026年第57卷第11期

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doi: 10.7501/j.issn.0253-2670.2026.11.006

接收时间：2025-12-22
首发时间：2026-09-09

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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