Objective To predict the potential suitability distribution of Vitex negundo in China;To analyze the key environmental factors influencing its suitability distribution.Methods Based on the geographic distribution data of Vitex negundo from 196 sites across China and 55 environmental variables,the Maximum Entropy(MaxEnt)model and ArcGIS 10.2 were employed to predict the potential distribution of suitable habitats for Vitex negundo in China.Results The constructed MaxEnt prediction model demonstrated high reliability.The primary environmental factors influencing the suitable distribution of Vitex negundo included the average temperature from June to October,precipitation in April and November,the mean temperature of the warmest season,soil type,and vegetation type.The predicted suitable habitats for Vitex negundo would be widely distributed,primarily concentrated in Jiangxi,central and southern Anhui,northwestern Zhejiang,eastern and northeastern Hunan,as well as eastern and southeastern Hubei.Conclusion The predicted potential distribution of Vitex negundo in China can provide a valuable reference for the conservation and sustainable utilization of this medicinal resource.

Background: Salvia miltiorrhiza Bunge, commonly known as “Danshen” in China due to the distinctive red color of its roots, is one of the most widely used traditional Chinese medicines. It is cultivated in various regions across China, and environmental differences among these regions can affect the secondary metabolites of plants, thereby influencing the quality of S. miltiorrhiza. In recent years, increasing demand for S. miltiorrhiza has exacerbated the problem of origin fraud. Therefore, ensuring the authenticity of its geographical origin is crucial for the sustainable development of the industry. Objective: The red coloration of S. miltiorrhiza is closely associated with the content of its primary active compounds, particularly tanshinones. Therefore, both its internal chemical composition and external color characteristics serve as key indicators for quality assessment. This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S. miltiorrhiza. Methods: Spectral data reflecting the internal chemical properties of S. miltiorrhiza were integrated with color information representing its external features through 3 levels of data fusion. These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification. Results: The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72% by integrating image color and short-wave infrared spectral data. Conclusion: This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S. miltiorrhiza.

Background: Optimizing cultivation techniques for traditional Chinese medicine has become a crucial means to improve the quality of medicinal materials. Microbial agents, as environmentally friendly and efficient plant growth promoters and soil conditioners, have increasingly attracted attention in eco-agriculture research. Objective: Our understanding remains limited regarding how the application of microbial agents, alone or in combination, affects changes in the rhizosphere microbiome and its association with the bioactive components of medicinal materials. Methods: In this study, Epimedium pubescens Maxim. was employed as a model plant to examine the effects of 2 microbial agents(Paenibacillus mucilaginosus and Bacillus subtilis) applied individually and in combination on plant growth and the accumulation of bioactive components. Additionally, this study explored the relationship between the rhizosphere microbiome and plant development. Results: The application of microbial agents increased the yield of E. pubescens leaves by 20.30% to 33.66% and enhanced the total flavonol glycosides content by 11.40% to 29.94%. Meanwhile, microbial treatments reshaped the rhizosphere microbiome, promoted the enrichment of beneficial microorganisms (e.g., Frankia and Paenibacillus), suppressed phytopathogenic fungi such as Didymella and Scytalidium, and enhanced the stability of the soil microbial co-occurrence network. The partial least squares path model suggested that microbial agents not only directly impact the quality of medicinal herbs but also indirectly alter the accumulation of bioactive components by modulating the soil microbiome. Conclusion: These findings deepen our understanding of the relationship between medicinal plant quality and rhizosphere microbiomes as mediated by microbial agents. They also provide a basis for designing and manipulating synthetic microbial communities to promote sustainable development in eco-agriculture.

Background:Salvia miltiorrhiza Bunge,commonly known as"Danshen"in China due to the distinctive red color of its roots,is one of the most widely used traditional Chinese medicines.It is cultivated in various regions across China,and environmental differences among these regions can affect the secondary metabolites of plants,thereby influencing the quality of S.miltiorrhiza.In recent years,increasing demand for S.miltiorrhiza has exacerbated the problem of origin fraud.Therefore,ensuring the authenticity of its geo-graphical origin is crucial for the sustainable development of the industry.Objective:The red coloration of S.miltiorrhiza is closely associated with the content of its primary active compounds,particularly tanshinones.Therefore,both its internal chemical composition and external color characteristics serve as key indicators for quality assessment.This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S.miltiorrhiza.Methods:Spectral data reflecting the internal chemical properties of S.miltiorrhiza were integrated with color information represent-ing its external features through 3 levels of data fusion.These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification.Results:The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72％by integrating image color and short-wave infrared spectral data.Conclusion:This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S.miltiorrhiza.

Background:Optimizing cultivation techniques for traditional Chinese medicine has become a crucial means to improve the quality of medicinal materials.Microbial agents,as environmentally friendly and efficient plant growth promoters and soil conditioners,have increasingly attracted attention in eco-agriculture research.Objective:Our understanding remains limited regarding how the application of microbial agents,alone or in combination,affects changes in the rhizosphere microbiome and its association with the bioactive components of medicinal materials.Methods:In this study,Epimedium pubescens Maxim.was employed as a model plant to examine the effects of 2 microbial agents(Paenibacillus mucilaginosus and Bacillus subtilis)applied individually and in combination on plant growth and the accumulation of bioactive components.Additionally,this study explored the relationship between the rhizosphere microbiome and plant development.Results:The application of microbial agents increased the yield of E.pubescens leaves by 20.30％to 33.66％and enhanced the total flavonol glycosides content by 11.40％to 29.94％.Meanwhile,microbial treatments reshaped the rhizosphere microbiome,promoted the enrichment of beneficial microorganisms(e.g.,Frankia and Paenibacillus),suppressed phytopathogenic fungi such as Didymella and Scytalidium,and enhanced the stability of the soil microbial co-occurrence network.The partial least squares path model suggested that microbial agents not only directly impact the quality of medicinal herbs but also indirectly alter the accumula-tion of bioactive components by modulating the soil microbiome.Conclusion:These findings deepen our understanding of the relationship between medicinal plant quality and rhizosphere micro-biomes as mediated by microbial agents.They also provide a basis for designing and manipulating synthetic microbial communities to promote sustainable development in eco-agriculture.

Background:Salvia miltiorrhiza Bunge,commonly known as"Danshen"in China due to the distinctive red color of its roots,is one of the most widely used traditional Chinese medicines.It is cultivated in various regions across China,and environmental differences among these regions can affect the secondary metabolites of plants,thereby influencing the quality of S.miltiorrhiza.In recent years,increasing demand for S.miltiorrhiza has exacerbated the problem of origin fraud.Therefore,ensuring the authenticity of its geo-graphical origin is crucial for the sustainable development of the industry.Objective:The red coloration of S.miltiorrhiza is closely associated with the content of its primary active compounds,particularly tanshinones.Therefore,both its internal chemical composition and external color characteristics serve as key indicators for quality assessment.This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S.miltiorrhiza.Methods:Spectral data reflecting the internal chemical properties of S.miltiorrhiza were integrated with color information represent-ing its external features through 3 levels of data fusion.These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification.Results:The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72％by integrating image color and short-wave infrared spectral data.Conclusion:This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S.miltiorrhiza.

Background:Optimizing cultivation techniques for traditional Chinese medicine has become a crucial means to improve the quality of medicinal materials.Microbial agents,as environmentally friendly and efficient plant growth promoters and soil conditioners,have increasingly attracted attention in eco-agriculture research.Objective:Our understanding remains limited regarding how the application of microbial agents,alone or in combination,affects changes in the rhizosphere microbiome and its association with the bioactive components of medicinal materials.Methods:In this study,Epimedium pubescens Maxim.was employed as a model plant to examine the effects of 2 microbial agents(Paenibacillus mucilaginosus and Bacillus subtilis)applied individually and in combination on plant growth and the accumulation of bioactive components.Additionally,this study explored the relationship between the rhizosphere microbiome and plant development.Results:The application of microbial agents increased the yield of E.pubescens leaves by 20.30％to 33.66％and enhanced the total flavonol glycosides content by 11.40％to 29.94％.Meanwhile,microbial treatments reshaped the rhizosphere microbiome,promoted the enrichment of beneficial microorganisms(e.g.,Frankia and Paenibacillus),suppressed phytopathogenic fungi such as Didymella and Scytalidium,and enhanced the stability of the soil microbial co-occurrence network.The partial least squares path model suggested that microbial agents not only directly impact the quality of medicinal herbs but also indirectly alter the accumula-tion of bioactive components by modulating the soil microbiome.Conclusion:These findings deepen our understanding of the relationship between medicinal plant quality and rhizosphere micro-biomes as mediated by microbial agents.They also provide a basis for designing and manipulating synthetic microbial communities to promote sustainable development in eco-agriculture.

Objective To predict the potential suitability distribution of Vitex negundo in China;To analyze the key environmental factors influencing its suitability distribution.Methods Based on the geographic distribution data of Vitex negundo from 196 sites across China and 55 environmental variables,the Maximum Entropy(MaxEnt)model and ArcGIS 10.2 were employed to predict the potential distribution of suitable habitats for Vitex negundo in China.Results The constructed MaxEnt prediction model demonstrated high reliability.The primary environmental factors influencing the suitable distribution of Vitex negundo included the average temperature from June to October,precipitation in April and November,the mean temperature of the warmest season,soil type,and vegetation type.The predicted suitable habitats for Vitex negundo would be widely distributed,primarily concentrated in Jiangxi,central and southern Anhui,northwestern Zhejiang,eastern and northeastern Hunan,as well as eastern and southeastern Hubei.Conclusion The predicted potential distribution of Vitex negundo in China can provide a valuable reference for the conservation and sustainable utilization of this medicinal resource.

As a Chinese saying goes， "good Chinese medicinal material makes good medicine"， the quality of Chinese herbal medicines is related to the development prospect of Chinese medicine industry in China. With the rapid development of new technologies such as traceability methods and monitoring instruments， it is imperative to integrate and innovate traditional Chinese herbal medicines with new-generation information technology in view of the quality problems existing in the current production and circulation of Chinese herbal medicines， and it is of great significance for the construction of traceability system to ensure the quality and safety of Chinese herbal medicines and to promote the industry of Chinese herbal medicines to move towards high-quality development. This paper reviews the development history of the traceability system of Chinese herbal medicines in China， takes the influencing factors of the quality of Chinese herbal medicines as the entry point， and proposes that the construction of the traceability system should satisfy the traceability requirements of the characteristics of Chinese herbal medicines and their traditional medication experience. By analyzing the influencing factors of the quality of Chinese herbal medicines， it is pointed out that focusing on the influencing factors to build a traceability system is of great significance for targeting the problematic links at a later stage and exploring the interrelationship between environmental factors and the quality of Chinese herbal medicines. Based on the previous explorations， the author summarizes the system framework， functional modules and practical applications of the traceability system of Chinese herbal medicines， and looks forward to the development of a traceability system with risk early warning function and expert decision-making function in its functional development. Finally， based on the factors affecting the quality of Chinese herbal medicines， the author puts forward several thoughts on construction of the traceability system， and makes an in-depth analysis and puts forward a solution for the current situation that a unified， standardized and universal traceability system has not yet been built， with a view to providing ideas and references for the construction of traceability system of Chinese herbal medicines.

ObjectiveIn recent years， with the sharp decline of wild resources in Arisaematis Rhizoma and Pinelliae Rhizoma and the immaturity of medicinal cultivation technology， their adulterants have appeared frequently in the market， and the main identifying characteristics have mostly disappeared in the circulation of medicinal materials. Therefore， there is an urgent need to establish a molecular identification method that can quickly and effectively identify the specificity of Arisaematis Rhizoma and Pinelliae Rhizoma. MethodAfter comparison of the rbcL sequences of Arisaematis Rhizoma，Pinelliae Rhizoma， and their adulterants， the specific enzyme cleavage sites Hae Ⅲ and Dra Ⅰ of Arisaematis Rhizoma and Pinelliae Rhizoma， respectively， were selected and identified by polymerase chain reaction-restriction fragment length polymorphism（PCR-RFLP）. The main system conditions of PCR-RFLP reaction were established and optimized， and their durability and the ability to detect genuine， adulterants， and mixed counterfeits were investigated. ResultThe PCR-RFLP identification method of Arisaematis Rhizoma and Pinelliae Rhizoma was established. After specific primer amplification， Arisaematis Rhizoma and Pinelliae Rhizoma could be digested by Hae Ⅲ and Dra Ⅰ-restricted endonucleases respectively， at annealing temperature of 54 ℃， the number of cycles of 35， and the amount of DNA template of 3-30 ng， producing two fragments or small cut fragments with a single band between 100-250 bp， whereas the mixed counterfeits were not cleaved and both showed a band at 250 bp. The method is highly accurate in identifying adulterants and mixed counterfeits of Arisaematis Rhizoma or Pinelliae Rhizoma. ConclusionThe PCR-RFLP method developed in this study allows for the rapid identification of Arisaematis Rhizoma and Pinelliae Rhizoma.