Xinggang Tang

Bio: Xinggang Tang is an academic researcher from Nanjing Forestry University. The author has contributed to research in topics: Dendrobium & Ecological niche. The author has an hindex of 5, co-authored 9 publications receiving 55 citations.

Maximum Entropy Modeling to Predict the Impact of Climate Change on Pine Wilt Disease in China.

Abstract: Pine wilt disease is a devastating forest disease caused by the pinewood nematode Bursaphelenchus xylophilus, which has been listed as the object of quarantine in China. Climate change influences species and may exacerbate the risk of forest diseases, such as the pine wilt disease. The maximum entropy (MaxEnt) model was used in this study to identify the current and potential distribution and habitat suitability of three pine species and B. xylophilus in China. Further, the potential distribution was modeled using the current (1970-2000) and the projected (2050 and 2070) climate data based on two representative concentration pathways (RCP 2.6 and RCP 8.5), and fairly robust prediction results were obtained. Our model identified that the area south of the Yangtze River in China was the most severely affected place by pine wilt disease, and the eastern foothills of the Tibetan Plateau acted as a geographical barrier to pest distribution. Bioclimatic variables related to temperature influenced pine trees' distribution, while those related to precipitation affected B. xylophilus's distribution. In the future, the suitable area of B. xylophilus will continue to increase; the shifts in the center of gravity of the suitable habitats of the three pine species and B. xylophilus will be different under climate change. The area ideal for pine trees will migrate slightly northward under RCP 8.5. The pine species will continue to face B. xylophilus threat in 2050 and 2070 under the two distinct climate change scenarios. Therefore, we should plan appropriate measures to prevent its expansion. Predicting the distribution of pine species and the impact of climate change on forest diseases is critical for controlling the pests according to local conditions. Thus, the MaxEnt model proposed in this study can be potentially used to forecast the species distribution and disease risks and provide guidance for the timely prevention and management of B. xylophilus.

The Effects of Ecological Factors on the Main Medicinal Components of Dendrobium officinale under Different Cultivation Modes

Abstract: Dendrobium officinale is an important traditional Chinese medicinal plant and crop, which contains many kinds of medicinal components. The quality of medicinal plants is closely related to the ecological factors in a growing environment. The main components of D. officinale determined in this study were polysaccharides, total alkaloids and total flavonoids. In addition, this study dealt with the correlation of these components to 16 ecological factors under three different cultivation modes (Greenhouse, Bionic, Wild; Lu’an, Anhui Province, China). The relationship between ecological factors and quality factors was analyzed step by step using correlation analysis, principal component analysis and stepwise multiple linear regression. Eight ecological factors: maximum relative humidity, minimum relative humidity, maximum temperature, sunshine duration, soil pH, soil total nitrogen, soil total phosphorus and soil available phosphorus were considered as key factors that influenced the main medicinal qualities of cultivated D. officinale. This study provides an insight for exploring the complex relationship between ecological factors and D. officinale medicinal value in artificial cultivation.

How Climate Change Will Alter the Distribution of Suitable Dendrobium Habitats

Abstract: To protect endangered species and restore their habitats, it is important to be able to predict their potential geographic distributions. The Dendrobium plant is important in traditional Chinese medicine, but urban expansion and over-exploitation have led to a decrease of Dendrobium resources. To achieve sustainable development of Dendrobium resources, here we systematically analyze the spatial and temporal distribution of two Dendrobium species, D. moniliforme and D. nobile. Maximum entropy modeling (MaxEnt) and the ArcGIS geographic information system were used to predict the distribution of suitable habitats for these Dendrobium species, both presently and in the future, under various greenhouse gas emission models. We found that D. moniliforme and D. nobile are widely distributed in the south of China (Anhui, Guangdong, Jiangxi, and Hunan provinces). Worldwide, Japan and North Korea were identified as major distribution areas for D. moniliforme and D. nobile. Based on the MaxEnt model, the mean diurnal range and the minimum temperature of the coldest month were identified as the most significant bioclimatic variables controlling the distribution of D. moniliforme and D. nobile. Future climate change will likely result in an increase of suitable habitat area for D. moniliforme (by around 16%), and decrease for D. nobile (by around 1-10%), but climate change is unlikely to have much impact on the distribution of suitable habitats for D. moniliforme and D. nobile in Japan and North Korea. Based on our findings, measures should be taken to protect these precious medicinal plant resources, and the sites used for the artificial cultivation of Dendrobium will need to shift as the climate changes.

Potential range expansion and niche shift of the invasive Hyphantria cunea between native and invasive countries

Abstract: 1. Hyphantria cunea is a problematic invasive species that has caused considerable damage to agricultural and forestry ecosystems in China.

Comparative Transcriptome Analysis of Different Dendrobium Species Reveals Active Ingredients-Related Genes and Pathways.

Abstract: Dendrobium is widely used in traditional Chinese medicine, which contains many kinds of active ingredients. In recent years, many Dendrobium transcriptomes have been sequenced. Hence, weighted gene co-expression network analysis (WGCNA) was used with the gene expression profiles of active ingredients to identify the modules and genes that may associate with particular species and tissues. Three kinds of Dendrobium species and three tissues were sampled for RNA-seq to generate a high-quality, full-length transcriptome database. Based on significant changes in gene expression, we constructed co-expression networks and revealed 19 gene modules. Among them, four modules with properties correlating to active ingredients regulation and biosynthesis, and several hub genes were selected for further functional investigation. This is the first time the WGCNA method has been used to analyze Dendrobium transcriptome data. Further excavation of the gene module information will help us to further study the role and significance of key genes, key signaling pathways, and regulatory mechanisms between genes on the occurrence and development of medicinal components of Dendrobium.

Hybrid threshold adaptable quantum secret sharing scheme with reverse Huffman-Fibonacci-tree coding

Abstract: With prevalent attacks in communication, sharing a secret between communicating parties is an ongoing challenge. Moreover, it is important to integrate quantum solutions with classical secret sharing schemes with low computational cost for the real world use. This paper proposes a novel hybrid threshold adaptable quantum secret sharing scheme, using an m-bonacci orbital angular momentum (OAM) pump, Lagrange interpolation polynomials, and reverse Huffman-Fibonacci-tree coding. To be exact, we employ entangled states prepared by m -bonacci sequences to detect eavesdropping. Meanwhile, we encode m -bonacci sequences in Lagrange interpolation polynomials to generate the shares of a secret with reverse Huffman-Fibonacci-tree coding. The advantages of the proposed scheme is that it can detect eavesdropping without joint quantum operations, and permits secret sharing for an arbitrary but no less than threshold-value number of classical participants with much lower bandwidth. Also, in comparison with existing quantum secret sharing schemes, it still works when there are dynamic changes, such as the unavailability of some quantum channel, the arrival of new participants and the departure of participants. Finally, we provide security analysis of the new hybrid quantum secret sharing scheme and discuss its useful features for modern applications.

Arbuscular mycorrhizal fungi

Abstract: The potential disease suppressiveness of arbuscular mycorrhizal (AM) fungi of various origins on Bipolaris sorokiniana in barley has been investigated. Firstly, a survey considering the occurrence of AM fungi in arable fields in Sweden were conducted with the aim to exploit site specific genetic resources in relation to disease suppressiveness. Arbuscular mycorrhizal fungi were present at all 45 sampling sites surveyed all over Sweden at densities ranging from 3 up to 44 spores per gram air dried soil. The highest spore density was found in a semi-natural grassland and the lowest were found in a cereal monoculture. The AM fungi were then multiplied in trap cultures in the greenhouse with the aim to use these for studying potential disease suppressiveness. Thus, the effects of the AM fungi trap cultures on the transmission of seed-borne B. sorokiniana in barley were investigated, using the trap culture inocula, but also including inocula consisting on spore mixtures. The arbuscular mycorrhizal fungi were able to suppress the transmission of B. sorokiniana in aerial parts of barley plants. The degree of suppression varied with the origin of the AM fungal trap cultures. The trap culture inoculum with the highest suppression of the B. sorokiniana transmission originated from an organically managed barley field with undersown ley. The two spore-inocula with the best suppression of the pathogen originated from fields with winter wheat and spring barley, respectively. Eventually, an in vitro method was developed for studying the effect of AM fungal colonisation of roots on the development of foliar diseases and the reaction of the actual host plant of the disease causing organism. Using the developed method, it was indicated that AM fungal colonisation of barley plant suppressed the development of leaf necroses due to B. sorokiniana. Further in vitro studies on the interaction between B. sorokiniana and arbuscular mycorrhizal fungi showed that B. sorokiniana decrease the germination of the AM fungal spores. In conclusion, AM fungi suppress the development of B. sorokiniana in barley. My data suggest that for biocontrol of B. sorokiniana AM fungi should be considered.

The Influence of Environmental Conditions on Secondary Metabolites in Medicinal Plants: A Literature Review.

Abstract: Medicinal plants, a source of different phytochemical compounds, are now subjected to a variety of environmental stresses during their growth and development. Different ecologically limiting factors including temperature, carbon dioxide, lighting, ozone, soil water, soil salinity and soil fertility has significant impact on medicinal plants' physiological and biochemical responses, as well as the secondary metabolic process. Secondary metabolites (SMs) are useful for assessing the quality of therapeutic ingredients and nowadays, these are used as important natural derived drugs such as immune suppressant, antibiotics, anti-diabetic, and anti-cancer. Plants have the ability to synthesize a variety of secondary metabolites to cope with the negative effects of stress. Here, we focus on how individual environmental variables influence the accumulation of plant secondary metabolites. A total of 48 articles were found to be relevant to the review topic during our systematic review. The review showed the influence of different environmental variables on SMs production and accumulation is complex suggesting the relationship are not only species-specific but also related to increases and decline in SMs by up to 50 %. Therefore, this review improves our understanding of plant SMs ability to adapt to key environmental factors. This can aid in the efficient and long-term optimization of cultivation techniques under ambient environmental conditions in order to maximize the quality and quantity of SMs in plants.

Comparative Metabolomic Analysis of Dendrobium officinale under Different Cultivation Substrates

Abstract: Dendrobium officinale, a precious herbal medicine, has been used for a long time in Chinese history. The metabolites of D. officinale, regarded as its effective components to fight diseases, are significantly affected by cultivation substrates. In this study, ultra-performance liquid chromatography mass spectrometry (UPLC-MS/MS) was conducted to analyze D. officinale stems cultured in three different substrates: pine bark (PB), coconut coir (CC), and a pine bark: coconut coir 1:1 mix (PC). A total of 529 metabolites were identified. Multivariate statistical analysis methods were employed to analyze the difference in the content of metabolites extracted from different groups. By the criteria of variable importance in projection (VIP) value ≥1 and absolute log2 (fold change) ≥1, there were a total of 68, 51, and 57 metabolites, with significant differences in content across groups being filtrated out between PB and PC, PB and CC, and PC and CC, respectively. The comparisons among the three groups revealed that flavonoids were the metabolites that fluctuated most. The results suggested the D. officinale stems from the PB group possessed a higher flavonoid content. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that the significantly regulated metabolites were mainly connected with flavonoid biosynthesis. A comprehensive profile of the metabolic differentiation of D. officinale planted in different substrates was provided, which supports the selection of an optimum cultivation substrate for a higher biomass yield of D. officinale.