2024年3月28日 星期四
基于植物大数据遴选中国地理标志资源植物
Selecting geographical indication resource plants in China based on botanical big data
2022年 第31卷 第4期 页码[11-19]    下载全文[1MB]  
摘要

 为了充分挖掘和利用中国野生植物资源,并将资源植物利用与乡村振兴紧密结合,本文基于植物大数据,兼顾资源植物的经济价值和地域分布,提出利用地标系数遴选各地级行政区的“地理标志资源植物”(简称“地标植物”)。在全国375个地级行政区(即省级行政区管辖的行政单位,包含地级市、盟、自治州、地区、省直辖县级行政区)共遴选出1 181种地标植物候选物种,每个地级行政区至少1种;并且,从这些候选物种中遴选出661种地标植物,这些地标植物或具有独特的自然生态环境和人文历史,或已具备产业基础及当地栽培历史,或易规模化生产。从省级行政区看,广东遴选出的地标植物最多(102种),接下来依次为四川、云南和海南,遴选出的地标植物分别有96、86和83种。从地级行政区看,云南省文山壮族苗族自治州、安徽省芜湖市、江苏省淮安市、西藏自治区林芝市遴选出的地标植物最多(8种)。值得注意的是,有17种植物仅为1个地级行政区的地标植物,建议将这类植物开发成“地理标志植物产品”(简称“地标产品”)。另外,还存在1种植物被遴选为多个地级行政区地标植物的情况。对于地理空间上连续的多个地级行政区的地标植物,建议协同当地有关部门打造地标产品,塑造产业集群优势;而对于地理空间上不连续的多个地级行政区的地标植物,则需要突破地域壁垒,创新营销模式,构建营销网络,注重品牌打造,以形成拳头产品。研究结果显示:基于植物大数据可遴选出各地独特的优良植物资源,后续可将地标植物开发成地标产品,避免区域资源植物产业发展同质化,服务地方经济建设,助力乡村振兴。

Abstract

To fully explore and utilize the wild plant resources in China and closely integrate utilization of resource plants with rural revitalization, it is proposed to select “geographical indication resource plant” (“landmark plant” for short) in each prefectural administrative region using landmark coefficient based on botanical big data as well as considering the economic value and geographical distribution of resource plants. A total of 1 181 candidate species of landmark plants are selected from 375 prefectural administrative regions (namely administrative units governed by provincial administrative regions, containing prefecturelevel city, league, autonomous prefecture, prefecture, and countylevel administrative regions directly governed by provincial government) in China, and each prefectural administrative region has one species at least. Moreover, 661 species of landmark plants are selected from these candidate species, and these landmark plants possess unique natural ecological environment and humanistic history, or have industrial foundation and local cultivation history, or are easy to scale up for production. From the view of provincial administrative regions, the landmark plants selected from Guangdong are the most (102 species), followed by Sichuan, Yunnan, and Hainan, with 96, 86, and 83 species of landmark plants selected respectively. From the view of prefectural administrative regions, the landmark plants selected from Wenshan Zhuang and Miao Autonomous Prefecture of Yunnan Province, Wuhu City of Anhui Province, Huai’an City of Jiangsu Province, and Nyingchi City of Tibet Autonomous Region are the most (8 species). Notably, there are 17 species of plants, which are only landmark plants of one prefectural administrative region, and it is suggested to develop these plants into “geographical indication plant product” (“landmark product” for short). In addition, there is also a case that one species of plant selected as a landmark plant of multiple prefectural administrative regions. For the landmark plants of multiple continuous prefectural administrative regions in geographical space, it is suggested to cooperate with relevant local departments to create landmark products and shape industrial cluster advantage; while for the landmark plants of multiple discontinuous prefectural administrative regions in geographical space, it is necessary to break through regional barriers, innovate marketing models, build marketing networks, and pay attention to brand building in order to form. key products. It is suggested that unique excellent plant resources in different regions can be selected based on botanical big data, and landmark plants can be subsequently developed into landmark products to avoid the homogenization of regional resource plant industry development, serve local economic construction, and help rural revitalization.

关键词植物大数据; 地标系数; 地理标志资源植物; 地理标志植物产品; 乡村振兴
Key wordsbotanical big data; landmark coefficient; geographical indication resource plant; geographical indication plant product; rural revitalization
作者赵莉娜1,2, 单章建1,2, 刘冰1, 鲁丽敏1, 陈之端1, 路安民1
所在单位1. 中国科学院植物研究所 系统与进化植物学国家重点实验室, 北京 100093; 2. 中国科学院大学, 北京 100049
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基金项目国家自然科学基金资助项目(31900191; 32122009); 中国科学院B类战略先导项目(XDB31000000)