Article(id=1325193335379461041, tenantId=1146029695717560320, journalId=1319690209941618849, issueId=1325193166743282319, articleNumber=null, orderNo=null, doi=10.12398/j.issn.2096-7217.2025.04.006, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1722355200000, receivedDateStr=2024-07-31, revisedDate=1729094400000, revisedDateStr=2024-10-17, acceptedDate=null, acceptedDateStr=null, onlineDate=1793880312055, onlineDateStr=2026-11-05, pubDate=1763136000000, pubDateStr=2025-11-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793880312055, onlineIssueDateStr=2026-11-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793880312055, creator=13701087609, updateTime=1793880312055, updator=13701087609, issue=Issue{id=1325193166743282319, tenantId=1146029695717560320, journalId=1319690209941618849, year='2025', volume='6', issue='4', pageStart='1', pageEnd='110', issueExtLink='null', onlineDate='null', pubDate='1763136000000', pubDateStr='2025-11-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793880271850, creator='13701087609', updateTime=1793943421371, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1325458035077952468, tenantId=1146029695717560320, journalId=1319690209941618849, issueId=1325193166743282319, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1325458035077952469, tenantId=1146029695717560320, journalId=1319690209941618849, issueId=1325193166743282319, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=64, endPage=72, ext={EN=ArticleExt(id=1325193337485001650, articleId=1325193335379461041, tenantId=1146029695717560320, journalId=1319690209941618849, language=EN, title=Research on the development of electric agricultural machinery technology based on patent information, columnId=0, journalTitle=Journal of Intelligent Agricultural Mechanization, columnName=, runingTitle=null, highlight=null, articleAbstract=
This study takes the patent information of China's electric agricultural machinery technology as the research object, and uses patent measurement analysis method and visual analysis tools to carry out statistical analysis and comparative research on the relevant patent information from the perspectives of annual patent applications, patent structure, technological key, main applicants, patent layout, technology lifecycle and so on. The research results show that China's electric agricultural machinery technology innovation is developing rapidly, and the patent categories are mainly utility model and invention patents, and the proportion of invention patents is lower than utility model patents. Universities are the most important innovation subjects in this field, and technology research and development focuses on IPC (international patent classification) subcategories such as A01C (seeding, fertilization), B60K (power, transmission), and A01D (harvesting, mowing). Jiangsu Province and Shandong Province rank the top 2 in the number of domestic patent applications, and the United States and Japan are the two countries with the most layout in China. At present, the growth of electric agricultural machinery technology is weak, but the new technology has strong features, there is no sign of maturity, and it does not have signs of technological aging and still has greater development potential. The results of the study can provide information reference for clarifying the status quo, characteristics and development trend of China’s electric agricultural machinery technology innovation.
, authors=Qin LIU, Lianglong HU, Ya GAO, authorsList=Qin LIU, Lianglong HU, Ya GAO, authorCompany=null, correspAuthors=null, authorNote=
LIU Qin, Postgraduate, Researcher, research interests: Intellectual Property and Agricultural Mechanization. E-mail: 631144312@qq.com
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以中国电动农机技术专利信息为研究对象，利用专利计量分析方法和可视化分析工具，从专利年度申请量、专利结构、技术关键、主要申请人、专利布局、技术生命周期等角度对相关专利信息进行统计分析和比较研究。研究结果表明，中国电动农机技术创新发展迅速，专利类别以实用新型和发明专利为主，发明专利占比低于实用新型专利。高校是该领域最重要的创新主体，技术研发重点集中于A01C、B60K、A01D等IPC小类，江苏省和山东省是国内申请专利量前2位的省份，美国、日本是在中国布局最多的两个国家。目前电动农机技术生长性偏弱，但新技术特征较强，还没有出现成熟的迹象，尚不具备技术衰老的特征，仍具有较大的发展潜力。研究结果可为明晰中国电动农机技术创新现状、特点及发展趋势提供信息参考。
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