Arabidopsis Thaliana Data for A Conversational Multi-Agent AI System for Automated Plant Phenotyping

This dataset contains images of 24 Arabidopsis thaliana plants from five different ecotypes. Each plant was grown for 26 days, with images captured every 12 hours, resulting in a total of 1,248 images. This dataset is released in support of the following publication: [1] Chen, F. et al. A conversational multi-agent AI system for automated plant phenotyping. Nature Communications (2026). If you use this dataset, please cite the above paper. In addition, please also cite the following related works: [2] Minervini, M., Fischbach, A., Scharr, H. & Tsaftaris, S. A. Finely-grained annotated datasets for image-based plant phenotyping. Pattern Recognition Letters 81, 80–89 (2016). [3] Minervini, M., Giuffrida, M. V., Perata, P. & Tsaftaris, S. A. Phenotiki: an open software and hardware platform for affordable and easy image-based phenotyping of rosette-shaped plants. The Plant Journal 90, 204–216 (2017). Acknowledgement: We thank Dr Massimo Minervini for his contribution to this dataset.