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ZHANG Xing, HOU Meifang, TIAN Daike, YU Yueshu. Evaluation of the application effectiveness of seven commonly used plant identification software at home and abroad[J]. Journal of Technology, 2025, 25(3): 364-370. DOI: 10.3969/j.issn.2096-3424.2025.004
Citation: ZHANG Xing, HOU Meifang, TIAN Daike, YU Yueshu. Evaluation of the application effectiveness of seven commonly used plant identification software at home and abroad[J]. Journal of Technology, 2025, 25(3): 364-370. DOI: 10.3969/j.issn.2096-3424.2025.004

Evaluation of the application effectiveness of seven commonly used plant identification software at home and abroad

  • The application of plant identification softwares in professional investigation, science popularization, and teaching of plant resources is increasingly valued, and it has also become a powerful tool for people to flexibly and conveniently identify the surrounding plants in their daily lives. Based on the characteristics of plant edibility, medicinal use and ornamental value, the representative plants of 163 families, 379 genera, and 618 species were selected through field photography combined with Chinese plant image database resources, and a test image database was established. Seven commonly used plant identification softwares, including PictureThis, FlowerMate, FlowerMate2.0, PlantNet, LeafSnap, etc. at home and abroad, were selected for application effect evaluation. The results showed that FlowerMate2.0 had the highest identification score and LeafSnap had the lowest identification score. However, no significant difference was found among the selected software for plant identification accuracy. From the aspect of different plant organs, the identification of FlowerMate2.0 showed the best performance, while LeafSnap had the lowest performance. The identification accuracy of six softwares for angiosperms was higher than that of gymnosperms and ferns, and the identification accuracy for cultivated plants was higher than that for wild plants. PlantNet had the best output stability in plant identification, followed by PictureThis. Overall, PictureThis as the commonly used plant identification software for identifying flowers, fruits, and vegetables, shape and color can be used in daily life and routine plant teaching and science popularization. Combining professional field surveys with FlowerMate2.0 or expert identification can improve identification accuracy. With the development of artificial intelligence, the characteristics and identification effects of various plant identification softwares will be further improved, which will be conducive to promoting the development of plant resource investigation and protection, plant teaching and popular science education.
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