Inheritance, Innovation and Development, Intellectual Property Protection of Traditional Chinese Medicine in Hubei Province.

  • Published In: Asian Agricultural Research, 2026, v. 18, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: SUN, Yuanpeng; QU, Fei; SUN, Jianda; ZHANG, Yanping; SUN, Pei; YUAN, Zhiyang; SUN, Zhiguo 3 of 3

Abstract

Chinese medicinal materials are the material basis for the inheritance and development of traditional Chinese medicine. Intellectual property protection for the entire industrial chain of traditional Chinese medicinal materials promotes the inheritance and innovation of traditional Chinese medicine, and contributes to rural revitalization and the building of an agricultural power. This article provides an overview of the traditional Chinese medicinal materials in Hubei Province. It conducts a detailed investigation into the intellectual property resources of the province's traditional Chinese medicinal materials from aspects such as traditional knowledge, genetic resources, new plant varieties, patents, geographical indications, and trademarks. It analyzes the eight main problems in the protection, inheritance, and innovative development of intellectual property rights, and puts forward corresponding suggestions, such as establishing an intellectual property rights rule system for specific fields of traditional Chinese medicinal materials, promoting the "Famous Brand Action in Rural Areas", and building a "Hubei's Sixteen Superior Herbs" cluster of traditional Chinese medicinal materials. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Asian Agricultural Research. 2026/01, Vol. 18, Issue 1, p1
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2026
  • ISSN:1943-9903
  • DOI:10.19601/j.cnki.issn1943-9903.2026.01.001
  • Accession Number:191669483
  • Copyright Statement:Copyright of Asian Agricultural Research is the property of WuChu (USA - China) Science & Culture Media Corporation and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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