Research advance in phenotype detection robots for agriculture and forestry
Yuanqiao Wang, Jiangchuan Fan, S.K. Yu, Shuangze Cai, Xinyu Guo, Chunjiang Zhao
- Year
- 2023
- Citations
- 12
- Access
- Open access
Abstract
The continuous development of robot technology has made phenotype detection robots a key for extracting and analyzing phenotyping data in agriculture and forestry. The different applications of agricultural robots and phenotype detection robots were discussed in this article. Further, the structural characteristics and information interaction modes of the current phenotype detection robots were summarized from the viewpoint of agriculture and forestry. The publications with keywords related to clustering distribution were analyzed and the currently available phenotype robots were classified. Additionally, a conclusion on the design criteria and evaluation system of plant phenotype detection robots was summarized and obtained, and the challenges and future development direction were proposed, which can provide a reference for the design and applications of agriculture and forestry robots. Keywords: computer vision, plant phenotype detection robot, phenotyping analysis, sensor, evaluation system, device clustering DOI: 10.25165/j.ijabe.20231601.7945 Citation: Wang Y Q, Fan J C, Yu S, Cai S Z, Guo X Y, Zhao C J. Research advance in phenotype detection robots for agriculture and forestry. Int J Agric & Biol Eng, 2023; 16(1): 14–25.
Keywords
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