Chinese Bulletin of Botany ›› 2025, Vol. 60 ›› Issue (1): 74-80.DOI: 10.11983/CBB24027  cstr: 32102.14.CBB24027

• TECHNIQUES AND METHODS • Previous Articles     Next Articles

An Artificial Intelligence Model for Identifying Grassland Plants in Northern China

Jing Xuan1,2,, Qidi Fu1,, Gan Xie1,2,, Kai Xue1, Hairui Luo1,2, Ze Wei1, Mingyue Zhao1, Liang Zhi1, Huawei Wan3, Jixi Gao3, Min Li1,2,*()   

  1. 1Big Data and AI Biodiversity Conservation Research Center, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
    2China National Botanical Garden, Beijing 100093, China
    3Satellite Application Center for Ecology and Environment, Ministry of Ecology and Environment, Beijing 100094, China
  • Received:2024-02-23 Accepted:2024-06-21 Online:2025-01-10 Published:2024-06-24
  • Contact: * E-mail: iplant@ibcas.ac.cn
  • About author:These authors contributed equally to this paper

Abstract: A large number of software applications for plant identification based on plant images have been developed in recent years. However, those applications are mostly used for identifying the common species countrywide, and thus cannot meet the needs of identifying region-specific vegetation types. In this study, we developed an artificial intelligence model for identifying the dominant plants in Hulunbeier and Xilinhot grassland in Inner Mongolia, based on the image datasets in the Plant Photo Bank of China. The Top5 accuracy of this model reaches 94.6% in the actual field identification tests. Our model provides a new method for the intelligent identification of the major plant species in a specific area.

Key words: grassland plants, artificial intelligence, image recognition, Hulunbeier, Xilinhot