This paper focuses on determining the authenticity and identifying the species of Fritillariae cirrhosae using electronic nose, electronic tongue, and electronic eye sensors, near infrared and mid-level data fusion. 80 batches of Fritillariae cirrhosae and its counterfeits (including several batches of Fritillaria unibracteata Hsiao et K.C. Hsia, Fritillaria przewalskii Maxim, Fritillaria delavayi Franch and Fritillaria ussuriensis Maxim) were initially identified by Chinese medicine specialists and by criteria in the 2020 edition of Chinese Pharmacopoeia. After obtaining the information from several sensors we constructed single-source PLS-DA models for authenticity identification and single-source PCA-DA models for species identification. We selected variables of interest by VIP value and Wilk’s lambda value, and we subsequently constructed the three-source fusion model of intelligent senses and the four-source fusion model of intelligent senses and near-infrared spectroscopy. We then explained and analyzed the four-source fusion models based on the sensitive substances detected by key sensors. The accuracies of single-source authenticity PLS-DA identification models based on electronic nose, electronic eye, electronic tongue sensors and near-infrared were respectively 96.25%, 91.25%, 97.50% and 97.50%. The accuracies of single-source PCA-DA species identification models were respectively 85%, 71.25%, 97.50% and 97.50%. After three-source data fusion, the accuracy of the authenticity identification of the PLS-DA identification model was 97.50% and the accuracy of the species identification of the PCA-DA model was 95%. After four-source data fusion, the accuracy of the authenticity of the PLS-DA identification model was 98.75% and the accuracy of the species identification of the PCA-DA model was 97.50%. In terms of authenticity identification, four-source data fusion can improve the performance of the model, while for the identification of the species the four-source data fusion failed to optimize the performance of the model. We conclude that electronic nose, electronic tongue, electronic eye data and near-infrared spectroscopy combined with data fusion and chemometrics methods can identify the authenticity and determine the species of Fritillariae cirrhosae. Our model explanation and analysis can help other researchers identify key quality factors for sample identification. This study aims to provide a reference method for the quality evaluation of Chinese herbs.
Amomi fructus is rich in volatile components and valuable as a medicine and edible spice. However, the quality of commercially available A. fructus varies, and issues with mixed sources and adulteration by similar products are common. In addition, due to incomplete identification methods, rapid detection of the purchased A. fructus quality is still an issue. In this study, we developed qualitative and quantitative evaluation models to assess the variety and quality of A. fructus using GC, electronic tongue, and electronic nose to provide a rapid and accurate variety and quality evaluation method of A. fructus. The models performed well; the qualitative authenticity model had an accuracy of 1.00 (n = 64), the accuracy of the qualitative origin model was 0.86 (n = 44), and the quantitative model was optimal on the sensory fusion data from the electronic tongue and electronic nose combined with borneol acetate content, with R2 = 0.7944, RMSEF = 0.1050, and RMSEP = 0.1349. The electronic tongue and electronic nose combined with GC quickly and accurately evaluated the variety and quality of A. fructus, and the introduction of multi-source information fusion technology improved the model prediction accuracy. This study provides a useful tool for quality evaluation of medicine and food.
Background. Traditional Chinese medicine decoction (TCMD) is an oral liquid made by decocting crude medicinal compounds with water. It has complex compositions and diverse odor and taste, most of which have an unacceptable level of bitterness which seriously affects patients’ medication compliance. To solve this problem, a variety of taste-masking pathways and different types of taste-masking excipients were combined, using the application of coffee-mate to mask the bitterness of coffee as an existing example. Three composite taste-masking adjuvants were developed to improve the taste of TCMD, referred to as the Chinese Medicine Decoction-Mate (CMD-M). However, whether CMD-M has a good taste-masking effect and whether it affects the chemical compositions and pharmacological effects of the medicine remain unclear. Method. The commonly used pediatric medicine Qingre Huazhi Decoction (QRHZD) and the personalized decoctions used in clinical practices were used as the masking research carriers. The taste-masking effect of CMD-M on QRHZD was evaluated by both healthy volunteers and an electronic tongue, and the personalized decoctions were evaluated by clinical subjects. The changes of chemical components of QRHZD before and after taste-masking were evaluated by HPLC. The changes in anti-inflammatory effects were evaluated by establishing mice as an acute inflammatory model. Results. The taste-masking effect evaluation results showed that the bitterness of QRHZD was significantly reduced after adding CMD-M. There was no significant difference in the relative peak areas change rate and total peak areas ratio of common peaks of QRHZD before and after taste-masking ( P > 0.05 ), shown by HPLC analysis. The inhibitory rates of QRHZD on ear swelling in mice before and after taste-masking also showed no significant difference ( P > 0.05 ). Conclusions. CMD-M can effectively mask the bitterness of decoctions while bringing no significant difference overall in chemical compositions and pharmacological effects before and after QRHZD masking.
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