Chemometric Analysis of a Ternary Mixture of Caffeine, Quinic Acid, and Nicotinic Acid by Terahertz Spectroscopy

Vicatia thibetica de Boiss: Botany, Traditional Uses, Phytochemistry, Quantitative Analysis, and Pharmacology

BACKGROUND

Vicatia thibetica de Boiss is a common Tibetan medicine used for both medicine and food, belonging to the family Apiaceae. This plant has the functions of dispelling wind, removing dampness, dispersing cold, and relieving pain. It has great development potential and application prospects in food development and medicinal value.

METHODS

The related references on botany, traditional uses, phytochemistry, quantitative analysis, and pharmacology of V. thibetica de Boiss had been retrieved from both online and offline databases, including PubMed, ScienceDirect, Web of Science, Elsevier, Willy, SpringLink, SciFinder, Google Scholar, Baidu Scholar, ACS publications, SciHub, Scopus, and CNKI.

RESULTS

V. thibetica de Boiss exerts nourishing, appetizing, and digestive effects according to the theory of Tibetan medicine. Phytochemical reports have revealed that V. thibetica de Boiss contains flavonoids, coumarins, sterols, and organic acids. Meanwhile, the quantitative analysis of the chemical constituents of V. thibetica de Boiss has been done by means of UPLC-Q-TOF-MS. It has also been found that V. thibetica de Boiss possesses multiple pharmacological activities, including anti-fatigue, anti-oxidant, anti-aging, and non-toxic activities.

CONCLUSION

This paper has comprehensively summarized botany, traditional uses, phytochemistry, quantitative analysis, and pharmacology of V. thibetica de Boiss. It will not only provide an important clue for further studying V. thibetica de Boiss, but also offer an important theoretical basis and valuable reference for in-depth research and exploitation of this plant in the future.

Distinguishing pericarpium citri reticulatae of different origins using terahertz time-domain spectroscopy combined with convolutional neural networks

The geographical indication of pericarpium citri reticulatae (PCR) is very important in grading the quality and price of PCRs. Therefore, terahertz time-domain spectroscopy (THz-TDS) technology combined with convolutional neural networks (CNN) was proposed to distinguish PCRs of different origins without damage in this study. The one-dimensional CNN (1D-CNN) model with an accuracy of 82.99% based on spectral data processed with SNV was established. The two-dimensional image features were transformed from unprocessed spectral data using the gramian angular field (GAF), the Markov transition field (MTF) and the recurrence plot (RP), which were used to build a two-dimensional CNN (2D-CNN) model with an accuracy of 78.33%. Further, the CNN models with different fusion methods were developed for fusing spectra data and image data. In addition, the adding spectra and images based on the CNN (Add-CNN) model with an accuracy of 86.17% performed better. Eventually, the Add-CNN model based on ten frequencies extracted using permutation importance (PI) achieved the identification of PCRs from different origins. Overall, the current study would provide a new method for identifying PCRs of different origins, which was expected to be used for the traceability of PCRs products.

Terahertz Spectroscopic Analysis of Lactose in Infant Formula: Implications for Detection and Quantification

Lactose plays a significant role in daily lives as a constituent of various food and pharmaceutical products. Yet, lactose intolerance conditions demand low-lactose and lactose-free products in the market. These increasing nutritional claims and labels on food products entail simple and reliable methods of analysis that can be used for meeting quality standards, nutritional claims and legal requirements. In this study, terahertz time-domain spectroscopy (THz-TDS) was employed to analyse α-lactose monohydrate qualitatively and quantitatively in food products. Both absorption spectra and absorption coefficient spectra were investigated for their prediction performance. Regression models for lactose quantification using peak area and height of the absorption peaks 0.53 and 1.37 THz were developed and assessed in infant formula samples. Satisfactory prediction results were achieved in ideal conditions with pure standards, but not in all predictions of infant formula samples. Reasons and further implications are discussed.