BerryPortraits: Phenotyping Of Ripening Traits in cranberry (Vaccinium macrocarpon Ait.) with YOLOv8

• Published in: Plant methods Vol. 20; no. 1; p. 172
• Main Authors: Loarca, Jenyne, Wiesner-Hanks, Tyr, Lopez-Moreno, Hector, Maule, Andrew F., Liou, Michael, Torres-Meraz, Maria Alejandra, Diaz-Garcia, Luis, Johnson-Cicalese, Jennifer, Neyhart, Jeffrey, Polashock, James, Sideli, Gina M., Strock, Christopher F., Beil, Craig T., Sheehan, Moira J., Iorizzo, Massimo, Atucha, Amaya, Zalapa, Juan
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 13.11.2024; BioMed Central; BMC
• Subjects: Analysis; blueberries; color; color vision; computer software; Computer vision; Cranberries; Digital phenotyping; fruit quality; Genetic aspects; grapes; Growth; horticulture; image analysis; Image processing; Image segmentation; Image-based phenotyping; Machine vision; morphometry; Phenotype; Plant breeding; Plant genetics; plant pathology; Plant physiology; Pomology; Python (Programming language); Software; Vaccinium macrocarpon; Vaccinium vitis-idaea; United States; Digital phenotyping; Computer vision; Image segmentation; Plant breeding; Pomology; Image-based phenotyping; Fruit quality
• DOI: 10.1186/s13007-024-01285-1
• ISSN: 1746-4811

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.