Abstract:
PlantCV is an open-source Python project aimed at developing tools to address a range of image-based, plant phenotyping questions. PlantCV has been used for more than 10 years to automate trait collection from image data, and the newest release, PlantCV version 4, continues to lower the barrier to entry for users without substantial coding experience through extensive example use-case tutorials and simplified installation. In addition to usability, we document added functionality since the release of PlantCV v2, including support for more image types such as fluorescence, thermal, and hyperspectral data. Finally, we describe the development of a new subpackage focused on morphological trait measurements like leaf angle, and demonstrate its utility as compared to more manual methods of data collection.
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Citation:
H. Schuhl, K. E. Brown, H. Sheng, P. K. Bhatt, J. Gutierrez, D. Schneider, A. L. Casto, L. Acosta-Gamboa, J. G. Ballenger, F. Barbero, J. Braley, A. M. Brown, L. Chavez, S. Cunningham, M. Dilhara, A. M. Dimech, J. G. Duenwald, A. Fischer, J. M. Gordon, C. Hendrikse, G. L. Hernandez, J. G. Hodge, M. Huber, B. M. Hurr, S. Jarolmasjed, K. M. Jimenez, S. Kenney, G. Konkel, A. Kutschera, S. Lama, M. Lohbihler, A. Lorence, C. Luebbert, N. Ly, H. K. Manching, A. Marrano, S. Meerdink, N. M. Miklave, P. Mudrageda, K. M. Murphy, J. D. Peery, R. Pierik, S. Polydore, C. Robey, T. Rogers, T. J. Schultz, E. Seigel, D. Srivastava, S. Summerer, J. Sumner, C. Teng, A. E. Thompson, J. C. Tovar, T. van Daalen, M. Watson, J. J. Wheeler, M. C. Wilson, K. R. Ying, A. Zare, Y. Zhou, M. A. Gehan, and N. Fahlgren, “PlantCV v4: Image analysis software for high-throughput plant phenotyping,” The Plant Phenome Journal, vol. 9, no. 1, p. e70065, 2026, doi: 10.1002/ppj2.70065.@article{https://doi.org/10.1002/ppj2.70065,
author = {Schuhl, Haley and Brown, Keely E. and Sheng, Hudanyun and Bhatt, Parag K. and Gutierrez, Jorge and Schneider, Dominik and Casto, Anna L. and Acosta-Gamboa, Lucia and Ballenger, Joe G. and Barbero, Fabio and Braley, Jackson and Brown, Autumn M. and Chavez, Leonardo and Cunningham, Shannon and Dilhara, Malinda and Dimech, Adam M. and Duenwald, Joseph G. and Fischer, Annika and Gordon, Jared M. and Hendrikse, Chloe and Hernandez, Gabriela L. and Hodge, John G. and Huber, Martina and Hurr, Brandon M. and Jarolmasjed, Sanaz and Jimenez, Karina Medina and Kenney, Samuel and Konkel, Grant and Kutschera, Alexander and Lama, Sunita and Lohbihler, Matthew and Lorence, Argelia and Luebbert, Collin and Ly, Nathaniel and Manching, Heather K. and Marrano, Annarita and Meerdink, Susan and Miklave, Nicholas M. and Mudrageda, Pavan and Murphy, Katherine M. and Peery, J. David and Pierik, Ronald and Polydore, Seth and Robey, Caleb and Rogers, Tess and Schultz, Tyler J. and Seigel, Eliza and Srivastava, Dhiraj and Summerer, Stephan and Sumner, Josh and Teng, Chong and Thompson, Adriane E. and Tovar, Jose C. and van Daalen, Tim and Watson, Mark and Wheeler, John J. and Wilson, Mark C. and Ying, Kaitlyn R. and Zare, Alina and Zhou, Yutai and Gehan, Malia A. and Fahlgren, Noah},
title = {PlantCV v4: Image analysis software for high-throughput plant phenotyping},
journal = {The Plant Phenome Journal},
volume = {9},
number = {1},
pages = {e70065},
doi = {https://doi.org/10.1002/ppj2.70065},
url = {https://acsess.onlinelibrary.wiley.com/doi/abs/10.1002/ppj2.70065},
eprint = {https://acsess.onlinelibrary.wiley.com/doi/pdf/10.1002/ppj2.70065},
year = {2026}
}