成分分析

基于感官评价和电子鼻技术表征2种羌活挥发油气味特征及无损检测模型建立

  • 欧阳辉发 ,
  • 李林致 ,
  • 吴佳颖 ,
  • 胡慧玲
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  • 成都中医药大学药学院 西南特色中药资源国家重点实验室,成都 611137
第一作者 Tel:14779594766;E-mail:2641558532@qq.com
* Tel:13550332778;E-mail:huhuiling@cdutcm.edu.cn

收稿日期: 2024-01-09

  网络出版日期: 2025-01-07

Flavor characterization of two kinds of Notopterygii Rhizoma et Radix volatile oils based on sensory evaluation and electronic nose technology, and establishment of nondestructive detection models

  • OUYANG Hui-fa ,
  • LI Lin-zhi ,
  • WU Jia-ying ,
  • HU Hui-ling
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  • State Key Laboratory of Southwestern Traditional Chinese Medicine Resources,College of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China

Received date: 2024-01-09

  Online published: 2025-01-07

摘要

目的:通过对羌活和宽叶羌活2个品种中所含的主要有效部位挥发油进行气味分析,为快速、准确鉴别2种羌活挥发油差异提供良好可行的方法,丰富传统评价内涵的同时,为以挥发油为主的提取物的质量评价提供参考。方法:采用感官评价和电子鼻技术对2种羌活挥发油样品进行气味分析,进一步采用主成分分析(PCA)、线性判别分析(LDA)对获得的电子鼻数据进行分析与识别,建立Fisher判别和多层感知器(MLP)神经网络判别2种无损检测模型对样品进行品种区分。结果:感官评价结果表明,松脂味、清凉味和木质味是2种羌活挥发油的主要气味特征;变质腐竹味是影响2种羌活挥发油接受度与区分度的关键气味属性,且宽叶羌活挥发油中变质腐竹味气味属性比羌活挥发油的更加强烈;电子鼻结果显示,宽叶羌活挥发油中氮氧类化合物的响应值明显高于羌活挥发油,而氢化物、醇醚醛酮类化合物的响应值相较于羌活挥发油略低;Fisher判别模型对2种羌活挥发油的训练集与预测集的总体判别率分别为93.8%和87.5%,MLP神经网络判别模型对2种羌活挥发油的训练集与预测集的总体判别率分别为89.3%和91.7%。其中,MLP模型适用于判别羌活挥发油,而Fisher模型更适用于判别宽叶羌活挥发油。结论:人工感官与智能感官结合,从主观与客观2个层面进行表征,可明确2种羌活挥发油的气味差异;建立的Fisher判别函数和MLP判别模型可快速、准确鉴别2种羌活挥发油,可在传统评价角度为羌活挥发油的质量控制奠定前期基础,提供新的思路和方向。

本文引用格式

欧阳辉发 , 李林致 , 吴佳颖 , 胡慧玲 . 基于感官评价和电子鼻技术表征2种羌活挥发油气味特征及无损检测模型建立[J]. 药物分析杂志, 2024 , 44(11) : 1852 -1862 . DOI: 10.16155/j.0254-1793.2024-0016

Abstract

Objective: To conduct odor analysis of the main effective components, namely volatile oils, contained in two varieties, Notopterygium incisum Ting ex H.T.Chang and Notopterygium franchetii H.de Boiss, to provide a feasible method for promptly and accurately distinguishing between the differences in volatile oils of these two varieties of Notopterygii Rhizoma et Radix. This enriches the traditional evaluation content and serves as a reference for assessing the quality of extracts predominantly governed by volatile oils. Methods: The flavors of two samples of Notopterygii Rhizoma et Radix volatile oil were analyzed using electronic nose technology and sensory evaluation. The electronic nose data obtained were subjected to analysis and identification through principal component analysis (PCA) and linear discriminant analysis (LDA). Additionally, two nondestructive testing models-Fisher discrimination and multilayer perceptron (MLP) neural network discrimination were established for sample differentiation. Results: Sensory evaluation results indicated that pine resin flavor, cool flavor and woody flavor were the primary odor characteristics of both Notopterygii Rhizoma et Radix volatile oils. Additionally, the key flavor attribute influencing acceptance and differentiation was identified as spoiled yuba flavor, with the Notopterygium franchetii H. de Boiss volatile oil exhibiting a stronger presence of this attribute than the Notopterygium incisum Ting ex H. T. Chang volatile oil. The electronic nose results revealed that the nitrogen oxides’ response values in Notopterygium franchetii H. de Boiss volatile oil were significantly higher than those in Notopterygium incisum Ting ex H. T. Chang volatile oil. Meanwhile, the response values of hydrides, alcohol ether aldehydes, and ketones were slightly lower in Notopterygium franchetii H. de Boiss volatile oil compared to Notopterygium incisum Ting ex H. T. Chang volatile oil. The Fisher discriminant model demonstrated overall discrimination rates of 93.8% for the training set and 87.5% for the prediction set of the two volatile oils. In contrast, the MLP model achieved discrimination rates of 89.3% for the training set and 91.7% for the prediction set. Notably, the MLP model proved effective for identifying volatile oils, while the Fisher model exhibited greater suitability for discriminating volatile oils with broad-leaved characteristics. Conclusion: The combination of artificial senses and intelligent senses can be characterized from both subjective and objective perspectives, elucidating the flavor differences between the two kinds of Notopterygii Rhizoma et Radix volatile oils. The established Fisher discriminant function and MLP discriminant models can rapidly and accurately distinguish between the two kinds of Notopterygii Rhizoma et Radix volatiles. This lays a preliminary foundation for quality control in Notopterygii Rhizoma et Radix volatiles and offers new ideas and directions.

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