PlantID: A Flexible Unique Identifier Framework for Plant Phenotyping

Plant phenotyping experiments increasingly integrate diverse data types, including physical samples, image-derived traits, environmental measurements, and multi-omics datasets. As experimental complexity grows, maintaining traceability between individual plants, collected samples, and downstream analytical outputs has become a major challenge. Although community standards such as MIAPPE (Minimum Information About Plant Phenotyping Experiments) and FAIR principles (Findable, Accessible, Interoperable, Reusable) provide guidance for metadata reporting and interoperability, practical recommendations for implementing sample-level identifiers during active experimentation remain limited. Here, we present PlantID, a flexible unique identifier (UID) framework designed specifically for plant science research. PlantID provides a set of principles and practical guidelines for developing consistent, scalable, and interoperable plant identifiers that remain linked to structured metadata throughout the experimental lifecycle. Following a review of common UID strategies, PlantID recommends a condensed semantic UID structure that balances human readability, scalability, and compatibility with automated workflows while remaining adaptable to diverse experimental designs. To facilitate adoption, we developed an open-source PlantID label designer that supports generation of human-readable labels alongside machine-readable QR codes and barcodes. By promoting consistent UID and metadata practices, PlantID complements MIAPPE and FAIR standards to improve sample traceability, enhance data interoperability, and increase the long-term value and reusability of plant phenotyping datasets.