Henan University of Traditional Chinese Medicine, China.
Anal Methods. 2020 Nov 7;12(41):4987-4995. doi: 10.1039/d0ay01257b. Epub 2020 Oct 2.
Black sesame (Sesamum indicum L.) is a Chinese dietary herb that has been widely used in the medical and healthcare fields in China. According to the theory of Traditional Chinese medicine processing, reasonable processing (steaming and drying many times) can increase the tonic effect and reduce the adverse factors generated during long-term use. At present, the processing degree of black sesame is mainly judged based on subjective experience. However, due to the lack of objective and quantitative control indicators, quality fluctuations easily occur. Therefore, for better application, its processing technology needs scientific monitoring methods. Herein a gas chromatography-ion mobility spectrometry (GC-IMS) technique was applied as a monitoring method to differentiate the processed products of black sesame in different processing stages. The response data of volatile components obtained from the samples were processed by the built-in data processing software in the instrument to identify the different components for further principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). From fingerprint comparison, 70 differential signal peaks were screened, 32 of which were qualitatively identified, mainly monomers and dimers of 20 compounds. On this basis, the PCA model shows that there was a significant difference between the raw product (S1) and the processed products (H1-9); moreover, there was a certain correlation between the differential changes of samples in different processing stages (H1-9) and the processing times. The OPLS-DA model specifically shows the differential components in the processing with potential characteristics peaks of 41, 105, n-nonanal, 2 and ethanol can discriminate whether the BS has undergone the first processed. And the dynamic changes of the three characteristic peaks of 1-hexanol, acetic acid and 107 can determine the specific degree of processing of BS. The research proves that GC-IMS combined with a multivariate analysis model can provide scientific data for identifying the characteristic odor components of black sesame.
黑芝麻（Sesamum indicum L.）是一种中国药食同源植物，在中国的医药和保健领域得到了广泛应用。根据中药炮制理论，合理炮制（多次蒸晒）可以提高滋补效果，减少长期使用产生的不利因素。目前，黑芝麻的炮制程度主要依据主观经验判断。但是，由于缺乏客观、定量的控制指标，容易出现质量波动。因此，为了更好地应用，需要对其炮制工艺进行科学监测。本研究采用气相色谱-离子迁移谱（GC-IMS）技术作为监测方法，对不同炮制阶段的黑芝麻炮制产品进行区分。采用仪器内置的数据处理软件对样品中挥发性成分的响应数据进行处理，识别不同的成分，进一步进行主成分分析（PCA）和正交偏最小二乘判别分析（OPLS-DA）。从指纹图谱比较中，筛选出 70 个差异信号峰，其中 32 个被定性鉴定，主要为 20 种化合物的单体和二聚体。在此基础上，PCA 模型显示，生品（S1）和炮制品（H1-9）之间存在显著差异；此外，不同炮制阶段（H1-9）样品的差异变化与炮制次数之间存在一定的相关性。OPLS-DA 模型具体显示了加工过程中的差异成分，具有潜在特征峰的 41、105、n-壬醛、2 和乙醇可以区分 BS 是否经过第一次加工。BS 加工程度的三个特征峰 1-己醇、乙酸和 107 的动态变化可以确定。研究证明，GC-IMS 结合多元分析模型可以为识别黑芝麻的特征气味成分提供科学数据。
