Post-composing ontology terms for efficient phenotyping in plant breeding
Menda, Naama | Ellerbrock, Bryan J. | Simoes, Christiano C. | Karaikal, Srikanth Kumar | Nyaga, Christine | Flores-Gonzalez, Mirella | Tecle, Isaak Y. | Lyon, David | Agbona, Afolabi | Agre, Paterne A. | Peteti, Prasad | Akech, Violet | Asiimwe, Amos | Fauvelle, Eglantine | Meghar, Karima | Tran, Thierry | Dufour, Dominique | Cooper, Laurel | Laporte, Marie-Angelique | Arnaud, Elizabeth | Mueller, Lukas A
Ontologies are widely used in databases to standardize data, improving data quality, integration, and ease of comparison. Within ontologies tailored to diverse use cases, post-composing user-defined terms reconciles the demands for standardization on the one hand and flexibility on the other. In many instances of Breedbase, a digital ecosystem for plant breeding designed for genomic selection, the goal is to capture phenotypic data using highly curated and rigorous crop ontologies, while adapting to the specific requirements of plant breeders to record data quickly and efficiently. For example, post-composing enables users to tailor ontology terms to suit specific and granular use cases such as repeated measurements on different plant parts and special sample preparation techniques. To achieve this, we have implemented a post-composing tool based on orthogonal ontologies providing users with the ability to introduce additional levels of phenotyping granularity tailored to unique experimental designs. Post-composed terms are designed to be reused by all breeding programs within a Breedbase instance but are not exported to the crop reference ontologies. Breedbase users can post-compose terms across various categories, such as plant anatomy, treatments, temporal events, and breeding cycles, and, as a result, generate highly specific terms for more accurate phenotyping.
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Эту запись предоставил International Livestock Research Institute