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
Open Access logo

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