[Establishment of a fast discriminant model with electronic nose for Polygonati Rhizoma mildew based on odor variation].

The odor fingerprint of Pollygonati Rhizoma samples with different mildewing degrees was analyzed and the relationship between the odor variation and the mildewing degree was explored. A fast discriminant model was established according to the response intensity of electronic nose. The α-FOX3000 electronic nose was applied to analyze the odor fingerprint of Pollygonati Rhizoma samples with different mildewing degrees and the radar map was used to analyze the main contributors among the volatile organic compounds. The feature data were processed and analyzed by partial least squares discriminant analysis(PLS-DA), K-nearest neighbor(KNN), sequential minimal optimization(SMO), random forest(RF) and naive Bayes(NB), respectively. According to the radar map of the electronic nose, the response values of three sensors, namely T70/2, T30/1, and P10/2, increased with the mildewing, indicating that the Pollygonati Rhizoma produced alkanes and aromatic compounds after the mildewing. According to PLS-DA model, Pollygonati Rhizoma samples of three mildewing degrees could be well distinguished in three areas. Afterwards, the variable importance analysis of the sensors was carried out and then five sensors that contributed a lot to the classification were screened out: T70/2, T30/1, PA/2, P10/1 and P40/1. The classification accuracy of all the four models(KNN, SMO, RF, and NB) was above 90%, and KNN was most accurate(accuracy: 97.2%). Different volatile organic compounds were produced after the mildewing of Pollygonati Rhizoma, and they could be detected by electronic nose, which laid a foundation for the establishment of a rapid discrimination model for mildewed Pollygonati Rhizoma. This paper shed lights on further research on change pattern and quick detection of volatile organic compounds in moldy Chinese herbal medicines.

[Comparison between macroscopic identification and DNA barcoding identification of Amomi Fructus].

This study aims to explore the consistency between macroscopic identification and DNA barcoding identification of Amomi Fructus. With the DNA barcoding identification results, we evaluated the reliability of identifying Amomi Fructus quality by combining macroscopic traits with main volatile chemical components. Thirteen batches of Amomi Fructus samples were collected for identification. Firstly, the morphological and sensory characteristics of each sample were observed and recorded according to the standard in Chinese Pharmacopoeia(2020 edition). The 100-fruit weight, longitudinal diameter, transverse diameter, and longitudinal diameter-to-transverse diameter ratio were measured, which correspond to large, solid, and full kernel representing good quality in the sensory evaluation. The odor value detected by electronic nose and major volatile components(borneol, camphor, limonene, and borneol acetate) correspond to the sensory evaluation of strong odor representing good quality. Secondly, DNA barcoding was employed to identify the 13 batches of samples. Finally, clustering analysis was performed for the main volatile components and macroscopic traits, and the identification results were compared with those of DNA barcoding. Except two batches of samples(No.6 and No.10), the macroscopic identification showed the results consistent with those of DNA barcoding, with an identification rate of 84.62%. The clustering results of the content of four volatile chemical components and macroscopic traits were also consistent with the DNA barcoding identification results. DNA barcoding can verify the results of macroscopic identification and provide a scientific basis for the inheritance and development of macroscopic identification. Moreover, the combination of macroscopic traits and chemical components demonstrates higher accuracy in the quality evaluation of Chinese medicinal materials.