Chang Liu’s research while affiliated with Jilin Agricultural University and other places

During ginseng selection, marketing promotion, and sales, it is imperative to expeditiously differentiate the overall quality grades, identify the geographic traces and determine the growth ages. This facilitates the selection of the most appropriate quality grade for each product, thereby ensuring the most efficacious marketing strategy. In this study, a new method is proposed and developed for the classification of ginsengs with diverse geographical traceability and with various growth ages by combining an electronic nose (E-nose) system and machine learning with Fourier-transform infrared spectroscopy (FTIR) as a calibration technology. An investigation has been carried out to discover the differences in the secondary metabolites and odor of three types of ginseng with different geographic traceability and three growth ages of ginseng from the same geographic traceability site. In the proposed method, five types of ginseng samples have been successfully tested. The optimal Mean-SVM model combined with an E-nose system classified ginseng samples with different geographic traceability and different growth years with accuracies of 100% and 82% in the training and test sets, respectively. These results have significant implications for ginseng’s geographic traceability, growth age determination, and overall quality control. It is believed that the future implementation of the proposed method would significantly protect the health and economic interests of consumers as well as promoting the use of an E-nose in the market surveillance of consumable products such as ginseng and other foods.

Ginseng (Panax ginseng C. A. Mey.) is an important and valuable medicinal plant species used in traditional Chinese medicine, and its metabolite ginsenoside is the primary active ingredient. The FAR1/FHY3 gene family members play critical roles in plant growth and development as well as participate in a variety of physiological processes, including plant development and signaling of hormones. Studies have indicated that methyl jasmonate treatment of ginseng adventitious roots resulted in a significant increase in the content of protopanaxadiol ginsenosides. Therefore, it is highly significant to screen the FAR1/FHY3 gene family members in ginseng and preliminarily investigate their expression patterns in response to methyl jasmonic acid signaling. In this study, we screened and identified the FAR1/FHY3 family genes in the ginseng transcriptome databases. And then, we analyzed their gene structure and phylogeny, chromosomal localization and expression patterns, and promoter cis-acting elements, and made GO functional annotations on the members of this family. After that, we treated the ginseng adventitious roots with 200 mM methyl jasmonate and investigated the trend of the expression of four genes containing the largest number of methyl jasmonate cis-acting elements at different treatment times. All four genes were able to respond to methyl jasmonate, the most significant change was in the PgFAR40 gene. This study provides data support for subsequent studies of this family member in ginseng and provides experimental reference for subsequent validation of the function of this family member under methyl jasmonic acid signaling.

At present, the electronic nose has became a new technology for the rapid detection of pesticides. However, the technique may misidentify them for samples that have not been involved in training. Therefore, a hybrid model based on unsupervised and supervised learning was proposed for the first time in this paper. The model divided the detection process of soil pesticide residues into two steps: (1) an unsupervised machine learning method was used to identify whether the soil was contaminated with pesticides; (2) when the soil was contaminated with pesticides, a supervised classifier was further used to predict the types of pesticides in the soil. The experimental results showed that the model had a recognition accuracy of 99.3% and 99.27% for whether the soil was contaminated with pesticides and the pesticide type of the contaminated soil, respectively, with a detection time of 0.03 s. The results revealed that the proposed hybrid model can quickly and comprehensively reflect the soil information’s status.

Panax ginseng is an important medicinal plant, and ginsenosides are the main bioactive molecules of ginseng. The TCP (TBI, CYC, PCF) family is a group of transcription factors (TFs) that play an important role in plant growth and development, hormone signalling and synthesis of secondary metabolites. In our study, 78 PgTCP transcripts were identified from the established ginseng transcriptome database. A phylogenetic tree analysis showed that the 67 PgTCP transcripts with complete open reading frames were classified into three subfamilies, including CIN, PCF, and CYC/TB1. Protein structure analysis showed that PgTCP genes had bHLH structures. Chromosomal localization analysis showed that 63 PgTCP genes were localized on 17 of the 24 chromosomes of the Chinese ginseng genome. Expression pattern analysis showed that PgTCP genes differed among different lineages and were spatiotemporally specific. Coexpression network analysis indicated that PgTCP genes were coexpressed and involved in plant activities or metabolic regulation in ginseng. The expression levels of PgTCP genes from class I (PCF) were significantly downregulated, while the expression levels of PgTCP genes from class II (CIN and CYC/TB1) were upregulated, suggesting that TCP genes may be involved in the regulation of secondary metabolism in ginseng. As the PgTCP26-02 gene was found to be related to ginsenoside synthesis, its predicted protein structure and expression pattern were further analysed. Our results provide new insights into the origin, differentiation, evolution and function of the PgTCP gene family in ginseng, as well as the regulation of plant secondary metabolism. Supplementary Information The online version contains supplementary material available at 10.1186/s12870-024-04729-x.

Panax ginseng, renowned for its medicinal properties, relies on adventitious roots and hairy roots as crucial sources for the production of ginsenosides. Despite the widespread utilization of ginseng, investigations into its miRNAs have remained scarce. To address this gap, two samples of ginseng adventitious roots and ginseng hairy roots were collected, and subsequent construction and sequencing of small RNA libraries of ginseng adventitious roots and hairy roots were performed using the Illumina HiSeq X Ten platform. The analysis of the sequencing data unveiled total miRNAs 2432. The miR166 and miR396 were the most highly expressed miRNA families in ginseng. The miRNA expression analysis results were used to validate the qRT-PCR. Target genes of miRNA were predicted and GO function annotation and KEGG pathway analysis were performed on target genes. It was found that miRNAs are mainly involved in synthetic pathways and biological processes in plants, which include metabolic and bioregulatory processes. The plant miRNAs enriched KEGG pathways are associated with some metabolism, especially amino acid metabolism and carbohydrate metabolism. These results provide valuable insights miRNAs and their roles in metabolic processes in ginseng.