Keywords: decoding modules, effector deployment, computer vision

Latest 5 Papers

Universal modules for decoding amplitude and frequency of Ca2+ signals in plants

Authors: Vergara-Valladares, F., Rubio-Melendez, M. E., Charpentier, M., Michard, E., Dreyer, I.

Date: 2025-12-16 · Version: 1

DOI: 10.64898/2025.12.13.694100

Model Organism: General

calcium signaling EF‑hand Ca2+ binding protein decoding modules plant calcium sensors signal amplitude and frequency

Automated detection and quantification of two-spotted spider mite life stages using computer vision for high-throughput in vitro assays

Authors: Wiseman, M. S., Woods, J. L., Hartgrave, C. R., Richardson, B. J., Gent, D. H.

Date: 2025-12-10 · Version: 2

DOI: 10.1101/2025.09.14.676116

Model Organism: Tetranychus urticae

Tetranychus urticae high‑throughput phenotyping computer vision YOLO11 object detection resistance breeding

The host range paradox of Meloidogyne incognita: a physiological and transcriptomic analysis of nine susceptible interactions across six plant orders

Authors: Moura de Souza, V. H., Pellegrin, C., Hanlon, V. C. T., Xia, C., Kranse, O. P., Sonawala, U., Desikan, P., Senatori, B., Danchin, E. G. J., Derevnina, L., Eves-van den Akker, S.

Date: 2025-09-29 · Version: 1

DOI: 10.1101/2025.09.26.678250

Model Organism: Multi-species

Meloidogyne incognita host range cross‑kingdom transcriptome effector deployment host specificity

Evaporative cooling signals for wound healing in plants

Authors: Balem, J. M., Tan, C., Dias, N. C. F., Arnold, M. L., Tran, S., Severns, P. M., Teixeira, P. J. P. L., Li, C., Yang, L.

Date: 2025-05-28 · Version: 1

DOI: 10.1101/2025.05.23.655667

Model Organism: Arabidopsis thaliana

wound healing Arabidopsis thaliana cold-responsive genes CBF transcription factors computer vision

The Global Wheat Full Semantic Organ Segmentation (GWFSS) dataset

Authors: Wang, Z., Zenkl, R., Greche, L., De Solan, B., Bernigaud Samatan, L., Ouahid, S., Visioni, A., Robles-Zazueta, C. A., Pinto, F., Perez-Olivera, I., Reynolds, M. P., Zhu, C., Liu, S., D'argaignon, M.-P., Lopez-Lozano, R., Weiss, M., Marzougui, A., Roth, L., Dandrifosse, S., Carlier, A., Dumont, B., Mercatoris, B., Fernandez, J., Chapman, S., Najafian, K., Stavness, I., Wang, H., Guo, W., Virlet, N., Hawkesford, M., Chen, Z., David, E., Gillet, J., Irfan, K., Comar, A., Hund, A.

Date: 2025-03-19 · Version: 1

DOI: 10.1101/2025.03.18.642594

Model Organism: Triticum aestivum

wheat semantic segmentation computer vision deep learning phenotyping