A rich diversity of wild medicinal plant resources is distributed in China, but the breeding of new plant varieties of Chinese medicinal plants started late and the breeding level is relatively weak. Chinese medicinal plant resources are the foundation for new varieties breeding, and the plant variety rights(PVP) are of great significance for the protection and development of germplasm resources. However, most Chinese medicinal plants do not have a distinctness, uniformity, and stability(DUS) testing guideline. The Ministry of Agriculture and Rural Affairs has put 191 plant species(genera) on protection lists, of which only 30 are medicinal species(genera). At the same time, only 29 of 293 species(genera) plants in the Protection List of New Plant Varieties of the People\'s Republic of China(Forest and Grass) belong to Chinese medicinal plants. The number of PVP applications and authorization of Chinese medicinal plants is rare, and the composition of variety is unreasonable. Up to now, 29 species(genera) of DUS test guidelines for Chinese medicinal plants have been developed. Some basic problems in the breeding of new varieties of Chinese medicinal plants have appeared, such as the small number of new varieties and insufficient utilization of Chinese medicinal plant resources. This paper reviewed the current situation of breeding of new varieties of Chinese medicinal plants and the research progress of DUS test guidelines in China and discussed the application of biotechnology in the field of Chinese medicinal plant breeding and the existing problems in DUS testing. This paper guides the further application of DUS to protect and utilize the germplasm resources of Chinese medicinal plants.

The mycorrhizal traits of plants have been widely reported based on different scales or plant functional groups. To better utilize mycorrhizae to improve the cultivation yield and active ingredient accumulation of medicinal plants, a database of medicinal plant mycorrhizal characteristics is needed. A database on mycorrhizal traits including mycorrhizal type or status of Chinese medicinal plant species was assembled. In this study, the mycorrhizal type or status of a total of 3,230 medicinal plants was presented. Among them, the mycorrhizal traits of 1,321 species were ascertained. These medicinal plants had three mycorrhizal statuses, both single mycorrhiza (SM) and multi-mycorrhiza (MM) contained four mycorrhizal types. The majority of medicinal plants were obligatorily symbiotic with mycorrhizal fungi with 926 (70.10%) species. The most widespread mycorrhizal type is AM, which is associated with 842 medicinal plant species (90.93% of mycorrhiza has an obligatorily symbiotic relationship with Chinese medicinal plants). Another broadly studied mycorrhizal type is ECM, which is associated with 15 medicinal plant species. This study is the first exclusive database on mycorrhizal traits of medicinal plants, which provides both mycorrhizal type and status. This database provides valuable resources for identifying the mycorrhizal information of medicinal plants and enriching the theory of mycorrhizal traits, which will greatly benefit the production or management of medicinal plants.

Nitrogen is one of the most frequently used fertilizers in growth of Chinese medicinal plants(CMP). As in many other ecosystems, CMP ecosystem is also composed of plant-herbivore-natural enemy(tritrophic) interactions. Nitrogen fertilizer influences the growth and reproduction of CMP, and it is also able to heavily shape the ecosystem functions of CMP ecosystem through bottom-up forces. Understanding the specific effects of nitrogen fertilizer towards each trophic level will be beneficial to improve the resistance of CMP to herbivore and enhance the control efficiency of nature enemies to herbivore, and eventually, maximize the yield and quality of CMP. Most papers published on nitrogen use in plants focused mainly on the impact of nitrogen fertilization on CMP yield and quality. Influences of nitrogen application on CMP ecosystem get little attention at present. Therefore, this review summed up the potential effects of nitrogen fertilization on CMP ecosystem from perspectives of soil and tritrophic interactions. First of all, nitrogen fertilizer might decrease soil microbial biomass and altered the community structures of soil bacteria, fungi and protozoa. Negative effects of nitrogen fertilizer were found on biodiversity of soil bacteria and protozoa. Different fungi species respond differently to nitrogen fertili-zers. Nitrogen deposition can also decrease the soil pH. Decreases in soil microbial diversity and soil acidification can cause negative effects on CMP growth. In addition, nitrogen fertilizer could regulate the pest resistance of CMP including constitutive and inducible resistance. Both positive and negative effects of nitrogen application were found on pest resistance of CMP. Moreover, the development and predation of natural enemies were influenced by nitrogen deposition. Nitrogen influences natural enemies in many ways including plant volatiles, plant nutrient and structure and the supplementary food quality. Nectar and honeydew of plants and preys serve as important food source for natural enemies especially in early season when preys are still not available. Finally, the interactions between herbivores and their natural enemies were also shaped by nitrogen fertilizer in many aspects like increasing the nutritional content of prey and changing control efficiency of natural enemies. Some herbivores have evolved a strategy to sequester secondary metabolites which they absorbed from plant during their feeding. Studies showed that sequestration efficiency of secondary metabolites in prey could also be regulated by nitrogen. Parasitic, emergence, reproduction rate and longevity of parasites were found positively correlated with nitrogen deposition. Hopefully this study will shed light on practicable and economical application of nitrogen in cultivation of CMP.

Radix pseudostellariae L. is one of the most common and highly-prized Chinese medicinal plants with various pharmacological effects, and mainly produced in acid soils in the Guizhou and Fujian provinces of southwestern and southeastern China, respectively (Wu et al. 2020). However, consecutive monoculture of R. pseudostellariae results in severe root rot and decline in biomass and quality of underground tubers. Root tubers of R. pseudostellariae are typically planted in December and harvested in next June. Root rot commonly starts developing in May. The disease incidence of root rot was ranging from 37 to 46% in root portions and basal stem of R. pseudostellariae under the consecutive monoculture fields in Shibing County, Guizhou Province, China (108°12\'E, 27°03\'N) (Li et al. 2017). Severe root rot was observed in Shibing County in May 2018. Infected plants displayed curly, withered, and yellow leaves, blight, retarded growth, root rot, and yield losses. Abundant whitish mycelia were observed on roots and surrounding soil. Two fungal isolates, designated GZ20190123 and GZ20190124, were obtained from symptomatic roots cultured on potato dextrose agar (PDA). The optimum temperature range for growth of the two isolates was 25 to 30°C. The optimum pH range for the growth of GZ20190123 was 5 to 5.5, whereas GZ20190124 grew better between pH 5 to 8.5. The mean mycelial growth rates of GZ20190123 and GZ20190124 at 30°C were 2.1 and 1.5 cm/day, respectively. Conidia of the two isolates were ovoid or obclavate and were produced in single or branched chains. The internal transcribed spacer (ITS) region was amplified with primers ITS1 and ITS4 (White et al. 1990). The sequences were deposited in GenBank as accession No. MN726736 for GZ20190123 and MN726738 for GZ20190124. Sequence comparison revealed 99% (GZ20190123) and 97% (GZ20190124) identity with previously reported isolate xsd08071 of Mucor racemosus Bull. (accession No. FJ582639.1) and isolate BM3 of Mucor fragilis Bainier (accession No. MK910058.1), respectively, which was confirmed by phylogenetic analysis. The two isolates were tested for pathogenicity on R. pseudostellariae. Six roots of R. pseudostellariae were surface-sterilized with 75% ethanol and stab inoculated with mycelia using a sterile toothpick for each isolate. Sterile distilled water was stab inoculated to twelve roots to serve as the control. Treated roots were incubated in a greenhouse with 16 h day length [light intensity 146.5 μmol/(m2·s)] and day/night temperature 26°C/18°C. The inoculated roots showed the expected symptoms on roots and sprouts 7 days after inoculation, whereas the control roots with sprouts did not show any symptom. The fungi were re-isolated from the diseased roots and confirmed as expected M. racemosus or M. fragilis based on the ITS sequences, which satisfied Koch\'s postulates. Thus, isolate GZ20190123 was identified as M. racemosus and GZ20190124 as M. fragilis. Previously, M. racemosus and M. fragilis have been reported as a pathogen on tomato (Kwon and Hong 2005) and grape (Ghuffar et al. 2018), respectively. To our knowledge, this is the first report of M. racemosus and M. fragilis causing root rot of R. pseudostellariae in southwestern China, where the disease could cause a significant loss to production of this important medicinal plant.

The aim of this study was to develop quantitative structure-activity relationship (QSAR) models for predicting antioxidant activities of phenolic compounds. The bond dissociation energy of O-H bond (BDE) was calculated by semi-empirical quantum chemical methods. As a new parameter for QSAR models, sum of reciprocals of BDE of enol and phenol groups (X BDE ) was calculated. Significant correlations were observed between X BDE and antioxidant activities, and X BDE was introduced as a parameter for developing QSAR models. Linear regression-applied QSAR models and adaptive neuro-fuzzy inference system (ANFIS)-applied QSAR models were developed. QSAR models by both of linear regression and ANFIS achieved high prediction accuracies. Among the developed models, ANFIS-applied models achieved better prediction accuracies than linear regression-applied models. From these results, the proposed parameter of X BDE was confirmed as an appropriate variable for predicting and analysing antioxidant activities of phenolic compounds. Also, the ANFIS could be applied on QSAR models to improve prediction accuracy.