Search Results (31)

This study aims to further analyze the chemical characteristics of mountainous forest cultivated ginseng (MFCG) and garden ginseng (GG), concerning their calcium oxalate crystals, organic acids, and ginsenosides. The results demonstrate that MFCG had higher levels of non-free oxalate, calcium oxalate crystals, and most ginsenosides, while GG had higher fumaric acid/total organic acids. The content of non-free oxalate and calcium oxalate crystals in rhizome was the highest, showing a positive correlation with the growth years (5–20 years). In most cases, in MFCG, non-free oxalic acid ≥ 0.8%, calcium oxalate ≥ 160/mg, fumaric acid/total organic acids < 9%, Rb1 ≥ 6 mg/g, PPD/PPT was close to 2, and Rb1/Ro ≥ 2.5, while in GG, non-free oxalic acid < 0.8%, calcium oxalate ≤ 60/mg, fumaric acid/total organic acids ≥ 9%, Rb1 < 6 mg/g, PPD/PPT was close to 1, and Rb1/Ro < 2.5. These results can be used as the basis for distinguishing between GG and MFCG. Chemometric analysis of non-free oxalate, calcium oxalate crystals, and ginsenosides could distinguish MFCG from GG. Chemometric analysis of succinate, citrate, and malonic acids could mostly differentiate MFCG of over 15 years from that of less than 12 years. As far as we know, the present study is the first to determine the difference in the ratio of ginsenosides (Rb1/Ro, PPD/PPT) and the ratio of organic acids, which provides an innovative method for the distinction between the two and a scientific basis for effective quality control of MFCG. Full article

Understory-cultivated Panax ginseng possesses high pharmacological and economic value; however, its visual quality grading predominantly relies on subjective manual assessment, constraining industrial scalability. To address challenges including fine-grained morphological variations, boundary ambiguity, and complex natural backgrounds, this study proposes Ginseng-YOLO, a lightweight and deployment-friendly object detection model for automated ginseng grade classification. The model is built on the YOLOv11n (You Only Look Once11n) framework and integrates three complementary components: (1) C2-LWA, a cross-stage local window attention module that enhances discrimination of key visual features, such as primary root contours and fibrous textures; (2) ADown, a non-parametric downsampling mechanism that substitutes convolution operations with parallel pooling, markedly reducing computational complexity; and (3) Slide Loss, a piecewise IoU-weighted loss function designed to emphasize learning from samples with ambiguous or irregular boundaries. Experimental results on a curated multi-grade ginseng dataset indicate that Ginseng-YOLO achieves a Precision of 84.9%, a Recall of 83.9%, and an mAP@50 of 88.7%, outperforming YOLOv11n and other state-of-the-art variants. The model maintains a compact footprint, with 2.0 M parameters, 5.3 GFLOPs, and 4.6 MB model size, supporting real-time deployment on edge devices. Ablation studies further confirm the synergistic contributions of the proposed modules in enhancing feature representation, architectural efficiency, and training robustness. Successful deployment on the NVIDIA Jetson Nano demonstrates practical real-time inference capability under limited computational resources. This work provides a scalable approach for intelligent grading of forest-grown ginseng and offers methodological insights for the design of lightweight models in medicinal plants and agricultural applications. Full article

Forest ginseng (FG) is a rare medicinal and culinary plant in China, and its drying quality is heavily dependent on the drying method. This study investigated the effects of traditional hot air drying (HAD) and the self-developed negative-pressure circulating airflow-assisted desiccator drying (PCAD) method on the quality of FG using metabolomics and enzyme activity. The results revealed that the enzyme activities of dried FG were reduced considerably. PCAD preserved higher enzyme activity than HAD. Metabolomics data demonstrate that HAD promotes the formation of primary metabolites (amino acids, lipids, nucleotides, etc.), whereas PCAD promotes the formation of secondary metabolites (terpenoids, phenolic acids, etc.). A change-transformation network was built by combining the metabolites listed above and their biosynthetic pathways, and it was discovered that these biosynthetic pathways were primarily associated with the mevalonate (MVA) pathway, lipid metabolism, phenylpropane biosynthesis, and nucleotide metabolism. It is also believed that these findings are related to the chemical stimulation induced by thermal degradation and the ongoing catalysis of enzyme responses to drought stress. The facts presented above will give a scientific basis for the selection of FG drying processes, as well as helpful references for increasing the nutritional quality of processed FG. Full article

American ginseng (Panax quinquefolius L.) is a rare and valuable plant utilized for medicinal and culinary purposes, with its geographic origin and cultivation significantly affecting its quality and efficacy. However, the metabolic differences between cultivated and wild American ginseng are not well understood. An accurate and reliable method for tracing the origin and evaluating the quality of American ginseng is therefore urgently required. This study introduces a UHPLC-Q/TOF-MS-based comparative metabolomics and machine learning strategy for the rapid identification of wild and cultivated American ginseng. Both principal component analysis and hierarchical cluster analysis revealed distinct metabolic phenotypes between wild and cultivated American ginseng. Furthermore, the integration of univariate and multivariate statistical analyses identified eight differential metabolites in the ESI⁺ mode and three in the ESI^- mode, including seven ginsenosides. A potential ginsenosides marker panel was used to construct five machine learning models to assist in diagnosing the metabolic phenotypes of American ginseng. The Random Forest model, based on the eight differential metabolites in the ESI⁺ mode, achieved a 100% classification rate in both test and validation sets for distinguishing between wild and cultivated American ginseng. This study highlights the feasibility and application of our artificial intelligence-driven comparative metabolomics strategy for cultivar identification and geographic tracing of American ginseng, offering new insights into the molecular basis of metabolic variation in cultivated American ginseng. Full article

Quality control remains a challenge in traditional Chinese medicine (TCM). This study introduced a novel genetic-based quality control method for TCM. Genetic variations in ginseng were evaluated across whole-genome, chloroplast genome, and ITS2 DNA barcode dimensions. Significant genetic variations were found in whole-genome comparison, leading to the use of inter-simple sequence repeat markers to assess the genetic diversity of ginseng decoction pieces (PG), garden ginseng (GG), and ginseng under forest (FG). Fingerprints of ginseng samples revealed instability within some batches. These evaluations were transformed into information entropy to calculate the size of Hardy–Weinberg equilibrium population (HWEP). FG had significantly higher genetic and chemical minimum HWEP than GG (p < 0.05). Notably, a significant positive correlation was observed between the minimum HWEP for genetics and for chemistry (r = 0.857, p = 0.014). Genetic polymorphism analysis of ginseng has the potential to evaluate chemical quality consistency, offering a new method to ensure quality consistency in TCM. Full article

Wild-simulated ginseng (WSG, Panax ginseng C.A. Meyer) is one of the most valuable medicinal plants in the world. This study aimed to investigate the correlation between growth and ginsenoside content of WSG in two different cultivation environments: coniferous and mixed forests. The results showed that air temperature, soil moisture content, and solar radiation were higher in mixed forest than in coniferous forest. Regarding soil properties, electrical conductivity, organic matter, total nitrogen, exchangeable potassium, and magnesium were higher in mixed forest than in coniferous forest. However, exchangeable sodium was lower in mixed forest than in coniferous forest. The analysis of growth characteristics revealed that the number of leaflets was significantly higher in WSG cultivated in mixed forest than in WSG cultivated in coniferous forest, whereas rhizome length, root diameter, root weight, and dry weight were significantly higher in coniferous forest. In contrast, total ginsenoside content and the content of each ginsenoside were much higher in WSG cultivated in mixed forest than in WSG cultivated in coniferous forest. The growth of WSG showed significantly positive correlations with electrical conductivity, organic matter, total nitrogen, exchangeable cations (K⁺, Mg²⁺, Na⁺), and cation exchange capacity. The number of leaflets per stem showed significantly positive correlations with six ginsenosides, whereas petiole length showed significantly negative correlations with mRb1, mRc, and Rb1. In conclusion, growth characteristics of WSG were higher in coniferous forest, but ginsenoside contents were higher in mixed forest. These results might be helpful for establishing the most optimal growth model of WSG, which is affected by various environmental factors. Full article

In this study, we investigated the mechanism of conversion of active components as well as the color change of forest ginseng (FG) during the drying process with the self-developed negative-pressure circulating airflow-assisted desiccator (PCAD) drying method, using a widely targeted metabolomics analytical method based on ultraperformance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS). During the drying process, a total of 1862 metabolites were identified in FG, along with 748 differential abundant metabolites (DAMs). Further analysis of the types and metabolic pathways of the DAMs revealed that both primary and secondary metabolites changed by 50–70% moisture content (MC); secondary metabolites dominated with a 30–50% MC, and primary metabolites dominated with a 10–30% MC, which revealed the differences in the transformation of the active ingredients in the drying process. In addition, the results showed the browning characteristics during the drying process. MC-50 and MC-10 showed the smallest and largest color changes, as well as enzyme activities, compared to the other MCs, respectively. As drying proceeded, browning reactions were mainly related to lipid and nucleotide metabolism and phenylpropane and flavonoid biosynthesis. In conclusion, the present study provides theoretical support for the mechanisms of active ingredient transformation as well as the color change of FG during PCAD drying. Full article

Background: Alzheimer’s disease is a central nervous system degenerative disease closely related to age with a complex pathogenesis. As a natural medicinal plant, forest-grown ginseng (GSF) contains abundant ginsenosides and offers significant neuroprotective effects. Methods: In this study, we comprehensively investigated the effect of GSF on the cell viability of PC12 cells in an AD model alongside metabolic changes in the serum and brains of mice, combined with an efficacy evaluation of PC12 cells in vitro and UHPLC-MS-based metabolomics in vivo. The goal of this study is to clarify the potential mechanism of GSF in treating AD. Results: The PC12 cell results showed that GSF can promote the proliferation of PC12 cells, reduce the content of IL-8, increase the activity of SOD, and alleviate the inflammation and oxidative stress induced by Aβ25~35. The immunohistochemical results for the mouse brain tissue also showed that GSF could reduce the inflammatory response of mouse brain tissue by reducing the overexpression of IBa1. AD was alleviated by reducing Aβ protein deposition in the mouse brain tissue. An untargeted metabolomics analysis was performed using UHPLC-Q-Exactive MS and principal component analysis (PCA) to identify the differentially expressed metabolites in the serum and brain tissue of AD mice after treatment. Twenty and seventeen different metabolites were identified in the serum and brain tissue, respectively. The pathway enrichment analysis of differential metabolites showed that GSF could treat AD by up-regulating succinic acid semialdehyde, carbamoyl phosphate, Sphingosine 1-phosphate, L-cystathionine, 2-ketobutyric acid, Vanillylmandelic acid, and D-Ribose to regulate sphingomyelin metabolism, the synthesis and metabolism of neurotransmitters and precursors, and energy metabolism. Conclusions: GSF can reduce neuroinflammation and alleviate Alzheimer’s disease by regulating the metabolic disorders of amino acids, sphingolipids, unsaturated fatty acids, and arachidonic acid in mice serum and brain tissue metabolites. These results suggest a link between metabolite imbalance and AD, and reveal the basis for the mechanism of ginsenosides in AD treatment. Full article

The cultivation of Panax ginseng C.A. Meyer, a valuable medicinal plant, presents a number of challenges due to its physiology and life cycle. The composition of the soil and the microbiome living in it are important for plant growth and root quality. Modern analytical methods were used to identify differences in the rhizosphere soils of plants in the forest and in the plots. Microbiological and molecular genetic methods were used to isolate and identify bacterial isolates from these soils, allowing for the establishment of a working collection of potentially useful bacterial strains. Increases in soil pH in the plots and changes in the amount of macronutrients partially explained the changes in the activity of the forest and plot isolates and the composition of the cultivated strains. The cultivated strains belonged to the rhizosphere-dominant phyla Pseudomonadota, Bacillota, and Actinomycetota of the main functional groups of soil potassium, phosphorus, and nitrogen transformations. The ratio of bacteria functional groups was comparable in the forest and in the plots. The most common phylum of cultured microorganisms was Bacillota, while the main differences were observed in the functional group of potassium-solubilizing bacteria belonging to the phyla Pseudomonadota. Full article

Panax ginseng, a perennial medicinal plant, utilizes its dried roots and rhizomes for medicinal purposes. Currently, in China, ginseng cultivation employs two methods: under-forest and farmland planting. These methods create distinct habitats, significantly influencing the ginseng’s rhizome morphology and, consequently, its economic value. In this study, two-year-old ginsengs were transplanted into farmland (TCG), a larch forest (TLCG) and a Quercus mongolica forest (TQCG) to analyze the differences in rhizome phenotypes caused by habitat changes. The results showed that there were significant differences in light intensity and the soil’s available phosphorus and potassium contents between farmland and forest environments. The differences in habitats led to different adaptability of the ginseng’s rhizome morphology. Compared with TCG, the rhizomes of TLCG and TQCG were significantly elongated by 48.36% and 67.34%, respectively. After the rhizomes’ elongation in TLCG and TQCG, there was an increase in indole-3-acetic acid (IAA) contents and a decrease in lignin contents. By analyzing the expression of key genes, we found that, compared with TCG, the expression of key enzymes of lignin biosynthesis genes such as PgCOMT and PgCCR4 were down-regulated. The difference in ginseng’s rhizome length is related to the signal transduction pathway of auxin and gibberellin. In addition, we preliminarily screened out transcription factors PgWRKY75, PgDIV, and PgbHLH93.1, which can actively respond to habitat changes and play important roles in the elongation of ginseng rhizomes. In summary, this study elucidates the phenotypic plasticity strategy of ginseng rhizomes in response to habitat changes and delineates the regulatory mechanism behind phenotypic adaptation, offering novel insights into ginseng’s morphogenesis. Full article

Panax ginseng taproot serves as a crucial storage organ and constitutes a significant component of Chinese herbal medicine. In China, ginseng is cultivated using two primary methods: under-forest planting and farmland planting. These methods create distinct habitats that notably influence the morphology of ginseng taproots. However, the precise regulatory mechanisms governing ginseng taproot expansion remain to be fully elucidated. This study aimed to delineate the patterns of ginseng taproot expansion by examining taproots transplanted into farmland (TCG) and forest environments (TLCG and TQCG). Our findings indicate that light intensity and soil available potassium levels in TCG plots significantly exceed those in TLCG and TQCG plots. Compared with TLCG and TQCG, the taproot diameter of TCG increased by 11.54% and 27.73%, respectively. At the same time, combined with the microstructure of the transverse section of the taproot, it showed that the expansion of the TCG taproot was closely related to cell expansion. During TCG taproot expansion, there was an increase in indole-3-acetic acid (IAA) content, significant starch accumulation, and a decrease in lignin content. By analyzing the expression of key genes, we found that compared with TLCG and TQCG, the expression of genes PgTPS1 and PgALDH1 was upregulated, and the expression of genes PgHCT1, PgPAL3, PgPER3, and PgPER51 were downregulated in TCG taproot. Additionally, the transcription factors PgARF18.1 and PgbHLH42 were identified as responsive to habitat changes, playing pivotal roles in taproot expansion. In conclusion, this study provides foundational insights into the regulatory mechanisms of ginseng taproot expansion, offering significant implications for enhancing the quality and value of ginseng. Full article

Black ginseng is the processed product of ginseng, and it has been found that the content and types of rare ginsenosides increased after processing. However, there is limited research on the ginsenoside differences between cultivated and forest ginseng before and after processing and among various plant parts. This study investigated the effects of processing on ginsenosides in different parts of cultivated and forest ginseng. After processing, the contents of Re, Rg1, S-Rg3, Rg5, R-Rh1, Rk1, Rk3, and F4 were significantly increased or decreased, the growth age of forest ginseng was not proportional to the content of ginsenosides, and the differences in ginsenoside content in ginseng from different cultivation methods were relatively small. Chemometric analysis identified processing biomarkers showing varying percentage changes in different parts. Network pharmacology predicted the EGFR/PI3K/Akt/mTOR pathway as a potential key pathway for the anti-cancer effect of black ginseng. Full article

The flower buds of three Panax species (PGF: P. ginseng; PQF: P. quinquefolius; PNF: P. notoginseng) widely consumed as health tea are easily confused in market circulation. We aimed to develop a green, fast, and easy analysis strategy to distinguish PGF, PQF, and PNF. In this work, fast gas chromatography electronic nose (fast GC e-nose), headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) were utilized to comprehensively analyze the volatile organic components (VOCs) of three flowers. Meanwhile, a principal component analysis (PCA) and heatmap were applied to distinguish the VOCs identified in PGF, PQF, and PNF. A random forest (RF) analysis was used to screen key factors affecting the discrimination. As a result, 39, 68, and 78 VOCs were identified in three flowers using fast GC e-nose, HS-GC-IMS, and HS-SPME-GC-MS. Nine VOCs were selected as potential chemical markers based on a model of RF for distinguishing these three species. Conclusively, a complete VOC analysis strategy was created to provide a methodological reference for the rapid, simple, and environmentally friendly detection and identification of food products (tea, oil, honey, etc.) and herbs with flavor characteristics and to provide a basis for further specification of their quality and base sources. Full article

American ginseng (Panax quinquefolius L.) is known for its health benefits, which are attributed to various terpenoids. However, the specific composition and activities of these terpenoids in forest-grown wild American ginseng remain understudied. This study aimed to characterize the terpenoid composition, particularly triterpene saponins, in forest-grown wild American ginseng. The analysis revealed that triterpene saponins, notably American ginseng ginsenosides (AGGs), are the predominant active components, as identified through LC-MS/MS and HPLC. A subsequent in vitro evaluation of AGGs showcased their potent antioxidant capabilities, displaying the dose-dependent scavenging of free radicals and reducing agents. Moreover, AGGs demonstrated efficacy in reducing oxidative injury and intracellular ROS levels in RAW 264.7 macrophages treated with H₂O₂. In addition to their antioxidant properties, AGGs exhibited anti-inflammatory effects, significantly inhibiting NO and inflammatory substance production in lipopolysaccharide-treated RAW 264.7 macrophages. These findings highlight the potential of AGG-rich forest-grown wild American ginseng as a functional food with promising implications for improving human health. Full article

Due to an increase in interest towards functional and health-related foods, Panax ginseng sprout has been in the spotlight since it contains a significant amount of saponins which have anti-cancer, -stress, and -diabetic effects. To increase the amount of production as well as decrease the cultivation period, sprouted ginseng is being studied to ascertain its optimal cultivation environment in hydroponics. Although there are studies on functional components, there is a lack of research on early disease prediction along with productivity improvement. In this study, the ginseng sprouts were cultivated in four different hydroponic conditions: control treatment, hydrogen-mineral treatment, Bioblock treatment, and highly concentrated nitrogen treatment. Physical properties were measured, and environmental data were acquired using sensors. Using three algorithms (artificial neural networks, support vector machines, random forest) for germination and rottenness classification, and leaf number and length of stem prediction models, we propose a hierarchical machine learning model that predicts the growth outcome of ginseng sprouts after a week. Based on the results, a regression model predicts the number of leaves and stem length during the growth process. The results of the classifier models showed an F1-score of germination classification of about 99% every week. The rottenness classification model showed an increase from an average of 83.5% to 98.9%. Predicted leaf numbers for week 1 showed an average nRMSE value of 0.27, which decreased by about 33% by week 3. The results for predicting stem length showed a higher performance compared to the regression model for predicting leaf number. These results showed that the proposed hierarchical machine learning algorithm can predict germination and rottenness in ginseng sprout using physical properties. Full article