PlantCV v4: Image analysis software for high-throughput plant phenotyping
Publication date
2026-12
Authors
Schuhl, Haley
Brown, Keely E.
Sheng, Hudanyun
Bhatt, Parag K.
Gutierrez, Jorge
Schneider, Dominik
Casto, Anna L.
Acosta-Gamboa, Lucia
Ballenger, Joe G.
Barbero, Fabio
Editors
Advisors
Supervisors
Document Type
Article
Metadata
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License
cc_by
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.
Keywords
Agronomy and Crop Science, Plant Science
Citation
Schuhl, H, Brown, K E, Sheng, H, Bhatt, P K, Gutierrez, J, Schneider, D, Casto, A L, Acosta-Gamboa, L, Ballenger, J G, Barbero, F, Braley, J, Brown, A M, Chavez, L, Cunningham, S, Dilhara, M, Dimech, A M, Duenwald, J G, Fischer, A, Gordon, J M, Hendrikse, C, Hernandez, G L, Hodge, J G, Huber, M, Hurr, B M, Jarolmasjed, S, Jimenez, K M, Kenney, S, Konkel, G, Kutschera, A, Lama, S, Lohbihler, M, Lorence, A, Luebbert, C, Ly, N, Manching, H K, Marrano, A, Meerdink, S, Miklave, N M, Mudrageda, P, Murphy, K M, Peery, J D, Pierik, R, Polydore, S, Robey, C, Rogers, T, Schultz, T J, Seigel, E, Srivastava, D, Summerer, S, Sumner, J, Teng, C, Thompson, A E, Tovar, J C, van Daalen, T, Watson, M, Wheeler, J J, Wilson, M C, Ying, K R, Zare, A, Zhou, Y, Gehan, M A & Fahlgren, N 2026, 'PlantCV v4 : Image analysis software for high-throughput plant phenotyping', Plant Phenome Journal, vol. 9, no. 1, e70065. https://doi.org/10.1002/ppj2.70065