As a secondary metabolite, sesquiterpenes are not only have important functions in plant defense and signaling, but also play potential roles in basic materials for pharmaceuticals, cosmetic and flavor. As a traditional Chinese herbal medicine, Senecio scandens exhibits effects of anti-inflammatory and immunosuppressive, as well as invigorating the blood and removing extravasated blood. Over 600 sesquiterpenes with diverse structures were isolated from S. scandens and related species in the same genus. selleck chemicals To characterize sesquiterpenes synthesis, two FPS genes(SsFPS1 and SsFPS2) were identified in S. scandens through transcriptomic analysis. Bioinformatic analysis showed that both SsFPSs have conserved motifs for FPS function. Both SsFPSs exhibited constitutive gene expression in S. scandens tissues and SsFPS2 accumulated higher transcript in leaves and roots than SsFPS1. Meanwhile consistent with constitutive sesquiterpene accumulation in S.scandens tissues, most of these sesquiterpenes were detected in leaves and roots more than stems and flowers. Recombinant expression through Escherichia coli metabolic engineering, SsFPS1 or SsFPS2 was co-transformed with ZmTPS11(maize β-macrocarpene synthase) into BL21 competent cells. The results showed that the content of β-macrocarpene was increased by co-transformation with SsFPSs. It is demonstrated that SsFPS1 and SsFPS2 catalyzed E,E-FPP formation and provided FPP precursor for downstream sesquiterpene synthases. Characterization of SsFPSs provided the foundation for the exploration of biosynthesis of sesquiterpenoid with diverse structures and potential pharmaceutical values in S.scandens, and provide an important theoretical basis for the development of S. scandens abundant resources.In this study, the roots, stems and leaves of diploid and autotetraploid Dendrobium huoshanense were used as materials to compare their contents of polysaccharides and alkaloids, and the transcriptome sequencing analysis was carried out. The results showed that the contents of polysaccharides and alkaloids in the roots, stems and leaves of tetraploid were 7.6%, 34.5%, 17.2%, 0.01%, 0.024% and 0.035% higher than those of diploid D. huoshanense, respectively. The contents of active components in different tissues were significantly different. There were 3 687 differentially expressed genes in diploid and tetraploid D. huoshanense, of which 2 346 genes were up-regulated and 1 341 down regulated. Go functional analysis showed that these genes were mainly involved in growth and development, stress resistance and other related functions. KEGG pathway analysis showed that most of the differential genes were concentrated in the processes of carbon metabolism, signal transduction, carbohydrate metabolism, amino acid metabolism and energy metabolism. The differential expression of key genes involved in the metabolism of polysaccharides, terpenes and polyketones, amino acid metabolism, hormone synthesis and signal transduction in diploid and tetraploid plants may be the main reason for the high energy content, the increase of active components and the growth potential of tetraploid plants.Unmanned aerial vehicle(UAV) remote sensing and vegetation index have great potential in the field of Chinese herbal medicine planting. In this study, the visible light image of Polygonatum odoratum planting area in Changyi district of Jilin province were acquired by UAV, and the real-time monitoring of P. odoratum planting area was realized. The green leaf index(GLI) was established, and GLI values of P. odoratum were collected used the spatial sampling points. To compare the GLI values in different periods, it was found that the GLI values of P. odoratum have three stages changing rule of rising-gentle-falling related to the germination, vigorous growth and withered of P. odoratum growth. Meanwhile, the GLI values were compared with four biomass data of P. odoratum, including plant height, leaf area, chlorophyll a and chlorophyll b content in leaves, and it was found that the GLI value was related to the growth potential of P. odoratum. The GLI value with a rapid increase in rising stage or at a high level in the gentle stage means the P. odoratum was in a better growth potential. GLI value has a same change trend with plant height, and has certain correlation with plant height and leaf area. However, there is no obvious relationship between chlorophyll a and chlorophyll b contents in leaves and GLI value. The study clarified the change rule of GLI value of P. odoratum, explained the reason for the change of GLI value, and expanded the application range of GLI. The research shows that UAV and vegetation index can be applied to monitoring the Chinese herbal medicines planting, and provides a new idea for exploring more effective information extraction methods of Chinese herbal medicines.Identification of Chinese medicinal materials is a fundamental part and an important premise of the modern Chinese medicinal materials industry. As for the traditional Chinese medicinal materials that imitate wild cultivation, due to their scattered, irregular, and fine-grained planting characteristics, the fine classification using traditional classification methods is not accurate. Therefore, a deep convolution neural network model is used for imitating wild planting. Identification of Chinese herbal medicines. This study takes Lonicera japonica remote sensing recognition as an example, and proposes a method for fine classification of L. japonica based on a deep convolutional neural network model. The GoogLeNet network model is used to learn a large number of training samples to extract L. japonica characteristics from drone remote sensing images. Parameters, further optimize the network structure, and obtain a L. japonica recognition model. The research results show that the deep convolutional neural network based on GoogLeNet can effectively extract the L. japonica information that is relatively fragmented in the image, and realize the fine classification of L. japonica. After training and optimization, the overall classification accuracy of L. japonica can reach 97.5%, and total area accuracy is 94.6%, which can provide a reference for the application of deep convolutional neural network method in remote sensing classification of Chinese medicinal materials.