《中国药典》中，传统性状鉴定法仍是中药质量标准的重要组成部分之一。然而此法多采用模糊语言表述，例如对气味评鉴为“气稍淡、香气特异”等，严重影响了实践应用中的准确性。本课题组较早将ppb级灵敏度的电子鼻技术引入中药气味数字化研究中，前期已实现其对药材产地、贮藏期等的评鉴，显示出良好的应用前景。但具体应用中发现还有较多问题尚未明确，例如如何分析电子鼻“闻”到的气味与人鼻对药材的感官认识的相关性？其化学物质基础是什么？药理活性是否一致？本项目拟以阳春砂为研究载体，首先从传感器阵列的筛选和模式识别的优化出发，建立电子鼻检测和判别方法；此外，结合传统性状鉴别、色谱分析和药效学实验，逐一探讨上述科学问题。以期发挥电子鼻对气味分析的优势、补充其不足，丰富其“闻”出气味的内涵，为传统性状鉴定的现代化提供一种手段；为构建快速、准确、无损及规范的中药“真伪优劣”质量评价体系提供实验依据与思路借鉴。

Classically, Chinese materia medica (CMM) is authenticated by a human experience panel called macroscopic identification, which considers the morphologic characteristics (shape, color, etc) and the organoleptic properties (odor, taste, etc) through observing, touching, smelling and tasting. In Pharmacopoeia of the People’s Republic of China this macroscopic identification is still an important aspect of CMM quality evaluation. However, this method is often influenced by individual ability, external factors and usually inaccurate. In recent years, our team successfully use E-nose to discriminate CMM from different species, habitats, storage times, etc., which indicates E-nose is a promising method for CMM quality evaluation. But there are some problems in its application such as the relationship between E-nose analysis and human panel, the chemical compounds of the odor from E-nose, the similarity of the samples identified into the same category by E-nose, etc. Taken Amomum villosum as the experimental object, this research will present a method for detecting and discriminating the odors from different samples by E-nose based on the screening of sensor array and the optimization of pattern recognition. Besides, related studies will be carried out including macroscopic identification, spectrum chromatographic analysis and pharmacological experiment to figure out the above problems. This research aims at developing the advantages of E-nose and enriching the E-nose odor by the other methods, so as to provide a rapid, reliable and robust technology for CMM quality evaluation.

中药传统性状鉴定基于“辨状论质”理论，采用手摸、鼻闻、嘴尝等方法，建立了一整套优质药材的评价标准；同时，在《中国药典》等标准中，“性状”标准始终占据重要地位。仿生嗅觉系统的研究已开展多年，其中以电子鼻技术的为主要代表。本项目以砂仁为研究载体，将仿生嗅觉系统——电子鼻引入到中药“气味”数字化研究中。共收集了25批样品，基于传统性状鉴别法，建立了感官评价表；确定了纵径、横径及百果重为砂仁性状测量指标；采用气相色谱法、高效液相法测定了砂仁样品中乙酸龙脑酯、樟脑以及槲皮苷的含量；采用典型相关分析法，对砂仁性状特征和内在物质基础进行相关性分析；采用单因素考察和正交试验法，确定了α-Fox3000电子鼻对砂仁气味最佳测量参数；采用逐步判别分析法、主成分分析法、BC(BestFirst+CfsSubsetEval)属性筛选法等建立了传感器阵列优化方法；采用朴素贝叶斯、径向基函数网络、随机森林等建立了最佳模式识别算法。为筛选砂仁药效指标成分，考察了砂仁水煎液口服经过消化道的多成分变化情况，实验包括人工胃/肠液温孵、在体十二指肠段肠灌流、在体空肠段肠灌流、在体回肠段肠灌流等。实验结果显示：感官评价表中样品主要分为两类；建立的GC、HPLC、电子鼻等方法均准确、有效、可靠；不同来源样品间乙酸龙脑酯含量分布规律性最强；典型相关性分析结果显示，果实较大、种子团较饱满（纵径、横径数值大）的砂仁样品中乙酸龙脑酯含量较高；确立了BC属性筛选法为最佳MOS传感器阵列的优化方法；得到了NBN、RBF、RF三种最佳分类器，同时建立了级联分析器的最佳判别模型；传感器（LY2/gCT）最大响应值可对砂仁内在成分（乙酸龙脑酯）含量进行预测，如响应值=0.04，质较优，乙酸龙脑酯的含量大多都在3.5 mg/g以上、乙酸龙脑酯/樟脑含量比值大于2.0，基本可接受为道地阳春砂；砂仁水煎液的HPLC指纹图谱，标注了19个成分，分别标号为C1-C19，人工胃肠液中，19种成分稳定；其余肠段中，部分有吸收，其余成分显示间断性的吸收，原因可能涉及到其吸收机制，可做进一步研究。