Sediment formation and analysis of the main chemical components of aqueous extracts from different parts of ginseng roots

Analysis of sediment re-formation factors after ginseng beverage clarification based on XGBoost machine learning algorithm

The aim of this study was to explore the sediment re-formation factors of ginseng beverages subjected to four clarification ways (11 subgroups) including the ethanol precipitation, enzymatic treatment, clarifier clarification, and Hollow Fiber Column (HFC) methods, based on the Extreme Gradient Boosting (XGBoost) model. The results showed that the clarity of the ginseng beverages was significantly improved by all the clarification treatments, but still formed sediment after storage. HFC method exhibited the highest transmittance, the least sediment, and stronger antioxidant activity in the clarification treatment groups. According to the results of chemical composition analyses and partition coefficients, carbohydrates, saponins, proteins and metal elements were involved in varying degrees in the re-formation of the sediments in ginseng beverage after clarification. Based on the above data, the XGBoost model predicted that protein, Rd, Na, K, and total saponins were the five most important chemical components affecting the sediment re-formation in ginseng beverages.

Physicochemical properties and in vitro digestibility of ginseng starches under citric acid-autoclaving treatment

In this study, the effects of citric acid-autoclaving (CA-A) treatment on physicochemical and digestive properties of the native ginseng starches were investigated. The results showed that ginseng starch exhibited a B-type crystal structure with a low onset pasting temperature of 44.23 ± 0.80 °C, but high peak viscosity and setback viscosity of 5897.34 ± 53.72 cP and 692.00 ± 32.36 cP, respectively. The granular morphology, crystal and short-range ordered structure of ginseng starches were destroyed after CA-A treatment. The more short-chain starches were produced, resulting in the ginseng starches solubility increased. In addition, autoclaving, citric acid (CA) and CA-A treatment promoted polymerization and recrystallization of starch molecules, increased the proportion of amylopectin B1, and B3 chains, and improved molecular weight and resistant starch (RS) content of ginseng starches. The most significant multi-scale structural change was induced by CA-A treatment, which reduced the relative crystallinity of ginseng starch from 28.26 ± 0.24 % to 2.75 ± 0.08 %, and increased the content of RS to 54.30 ± 0.14 %. These findings provided a better understanding of the structure and properties of Chinese ginseng starches and offered new ideas for the deep processing of ginseng foods.

Recognition of the rhizome of red ginseng based on spectral-image dual-scale digital information combined with intelligent algorithms

Red ginseng is a widely used and extensively researched food and medicinal product with high nutritional value, derived from steamed fresh ginseng. The components in various parts of red ginseng differ significantly, resulting in distinct pharmacological activities and efficacies. This study proposed to establish a hyperspectral imaging technology combined with intelligent algorithms for the recognition of different parts of red ginseng based on the dual-scale of spectrum and image information. Firstly, the spectral information was processed by the best combination of first derivative as pre-processing method and partial least squares discriminant analysis (PLS-DA) as classification model. The recognition accuracy of the rhizome and the main root of red ginseng is 96.79% and 95.94% respectively. Then, the image information was processed by the You Only Look Once version 5 small (YOLO v5s) model. The best parameter combination is epoch = 30, learning rate = 0.01, and activation function is leaky ReLU. In the red ginseng dataset, the highest accuracy, recall and mean Average Precision at IoU (Intersection over Union) threshold 0.5 (mAP@0.5) were 99.01%, 98.51% and 99.07% respectively. The application of spectrum-image dual-scale digital information combined with intelligent algorithms in the recognition of red ginseng is successful, which provides a positive significance for the online and on-site quality control and authenticity identification of crude drugs or fruits.

An online derivatization strategy targeting carbon-carbon double bonds by laser-ablation carbon fiber ionization mass spectrometry imaging: Unraveling the spatial characteristic in mountain-cultivated ginseng and garden-cultivated ginseng with different ages

Serving as a world-renowned tonic, ginseng contains various types of bioactive metabolites. The comprehensive profiling of these metabolites may help explore the nutritional value of ginseng. Due to high variety in chemical structures, simultaneous monitoring of these metabolites remains a challenge. Herein, a high-throughput and high-selectivity online derivatization mass spectrometry imaging strategy targeting CC was developed. As a widely existed chemical group, CC acts like a bridge connecting different kinds of metabolites. [d₀]/[d₁₀]-Bis(pyridine) iodine tetrafluoroboride reagent was chosen for the derivatization of CC, the detection sensitivity of which increased about 3 magnitudes after derivatization. Assisted by laser ablation carbon fiber ionization mass spectrometry, the spatial distribution of bioactive metabolites in mountain-cultivated and garden-cultivated ginseng were visualized. The correlation heatmap results revealed that metabolites in mountain-cultivated ginseng hold higher correlation than those in garden-cultivated ginseng. The proposed method showed potential in providing comprehensive information on the nutrient content of foods.

Emulsifying properties and bioavailability of clove essential oil Pickering emulsions stabilized by octadecylaminated carboxymethyl curdlan

In the present study, clove essential oil (CEO) Pickering emulsions were stabilized by octadecylamine-modified carboxymethyl curdlan (CMCD-ODA) at different pH values. The droplet size and negatively charged zeta potential of the CMCD-ODA emulsions decreased as the pH increased from 3.0 to 11.0. Rheology results indicated that the CMCD-ODA polymer/emulsion prepared at pH 5.0 showed higher apparent viscosity and viscoelasticity than other pH conditions, which might prevent droplets from flocculating. The Pickering emulsions obtained at pH 5.0 were spherical droplets with a uniform size distribution and a mean diameter of 9.54 μm, and they exhibited excellent stability during 28 days of storage. The morphological structures of the emulsions investigated by confocal laser scanning microscopy and scanning electron microscopy indicated that the CMCD-ODA Pickering emulsion obtained at pH 5.0 was stabilized by loading amphiphilic CMCD-ODA polymer around the spherical oil droplets and forming a weak gel network structure. The CEO-loaded CMCD-ODA emulsions had higher antioxidant capacity than free CEO after 28 days of storage at pH 5.0. Given the good emulsion stability, antioxidant activity, and great antibacterial effect, the CEO-loaded carboxymethyl curdlan Pickering emulsion has promising applications in food, cosmetic, and biomedicine industries.

Analysis of Key Chemical Components in Aqueous Extract Sediments of Panax Ginseng at Different Ages

Panax ginseng beverages have been some of the most popular plant drinks among consumers in recent years, but they become turbid and sediment are easily formed during production and marketing, these are some of the key issues that affect the quality of the beverages. In this study, we analysed the physicochemical properties of sediments in aqueous extracts of 3- to 6-year-old ginseng, and by tracing the sediment formation process from 0-40 days, we observed that the sediment was gradually beginning on day 10. The solid content of ginseng aged 5 and 6 years was significantly higher than that of ginseng aged 3 and 4 years. There was no significant difference in the sediment amount sediment in the extracts of ginseng of different ages. The light transmittance of the extracts after centrifugation was significantly higher than before centrifugation. Colour-difference analysis found that there was a significant positive correlation between ginseng age and colour-difference value (ΔE). Chemical composition analysis showed that total sugar and proteins were the main components of the sediment. In addition, ginsenosides, amino acids and minerals were also involved in sediment formation to different degrees. A stepwise regression model was established through principal component analysis (PCA), and the regression equation for predicting the sediment amount was obtained as follows: sediment amount (mg/mL) = 2.906 - 0.126 × C_{Total saponins} - 0.131 × C_{Free amino acids}.