BerryPortraits: Phenotyping Of Ripening Traits in cranberry (Vaccinium macrocarpon Ait.) with YOLOv8
BerryPortraits (Phenotyping of Ripening Traits) is open source Python-based image-analysis software that rapidly detects and segments berries and extracts morphometric data on fruit quality traits such as berry color, size, shape, and uniformity. Utilizing the YOLOv8 framework and community-developed, actively-maintained Python libraries such as OpenCV, BerryPortraits software was trained on 512 postharvest images (taken under controlled lighting conditions) of phenotypically diverse cranberry populations (Vaccinium macrocarpon Ait.) from the two largest public cranberry breeding programs in the U.S. The implementation of CIELAB, an intuitive and perceptually uniform color space, enables differentiation between berry color and berry brightness, which are confounded in classic RGB color channel measurements. Furthermore, computer vision enables precise and quantifiable color phenotyping, thus facilitating inclusion of researchers and data analysts with color vision deficiency. BerryPortraits is a phenotyping tool for researchers in plant breeding, plant genetics, horticulture, food science, plant physiology, plant pathology, and related fields. BerryPortraits has strong potential applications for other specialty crops such as blueberry, lingonberry, caneberry, grape, and more. As an open source phenotyping tool based on widely-used python libraries, BerryPortraits allows anyone to use, fork, modify, optimize, and embed this software into other tools or pipelines.
Authors
- Luis Díaz‐García (ORCID: https://orcid.org/0000-0002-3984-5516)
- Maria Alejandra Torres-Meraz
- Tyr Wiesner‐Hanks (ORCID: https://orcid.org/0000-0002-3280-5749)
- Juan Zalapa (ORCID: https://orcid.org/0000-0001-8840-3565)
- Gina M. Sideli (ORCID: https://orcid.org/0000-0003-1056-1496)
- James J. Polashock (ORCID: https://orcid.org/0000-0002-7977-2921)
- Jenyne Loarca (ORCID: https://orcid.org/0000-0002-3661-3795)
- Jennifer Johnson‐Cicalese
- Massimo Iorizzo (ORCID: https://orcid.org/0000-0002-0032-8247)
- Amaya Atucha (ORCID: https://orcid.org/0000-0002-8921-5096)
- Jeffrey Neyhart (ORCID: https://orcid.org/0000-0002-1991-5310)
- Andrew Maule (ORCID: https://orcid.org/0000-0002-3187-1461)
- Michael Liou (ORCID: https://orcid.org/0000-0002-0035-957X)
- Christopher Strock (ORCID: https://orcid.org/0000-0003-1432-8130)
- Moira J. Sheehan (ORCID: https://orcid.org/0000-0002-3400-2165)
- Craig T. Beil (ORCID: https://orcid.org/0000-0002-1756-9987)
- Hector Lopez‐Moreno (ORCID: https://orcid.org/0009-0002-3223-447X)
Institutions
- Rutgers, The State University of New Jersey (US)
- NC Department of Health and Human Services (US)
- Agricultural Research Service (US)
- United States Department of Agriculture (US)
- University of Wisconsin–Madison (US)
- North Carolina State University (US)
- Cornell University (US)
- Carnegie Department of Plant Biology (US)
- Cranberry Institute (US)
- Beltsville Agricultural Research Center (US)
- University of California, Davis (US)
Publication Details
- Journal
- Plant Methods
- Published
- 2024-11-13
- DOI
- https://doi.org/10.1186/s13007-024-01285-1
- Citations
- 2
- Primary Topic
- Horticultural and Viticultural Research
- Type
- article
- Field-Weighted Citation Impact
- 1.20
Funders
- U.S. Department of Agriculture
- National Institute of Food and Agriculture