Submitted to: HortScience
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/28/2024
Publication Date: 9/5/2024
Citation: Hilsop, L.M., Luby, C.H., Loarca, J., Humann, J., Hummer, K.E., Bassil, N.V., Zhao, D., Sheehan, M., Casa, A.M., Billings, G.T., Echeverria, D., Ashrafi, H., Babiker, E.M., Edger, P., Ehlenfeldt, M.K., Hancock, J., Finn, C.E., Iorizzo, M., Mackey, T.A., Munoz, P.R., Olmstead, J., Rowland, L.J., Sandefur, P., Spencer, J., Stringer, S.J., Vorsa, N., Wagner, A., Hulse-Kemp, A.M. 2024. A blueberry (Vaccinium spp.) crop ontology to enable standardized phenotyping for blueberry breeding and research. Journal of the American Pomological Society. 59:1433-1442. https://doi.org/10.21273/HORTSCI17676-23.
DOI: https://doi.org/10.21273/HORTSCI17676-23

Interpretive Summary: The amounts of data collected on our crop systems by plant breeders is continually increasing as digital collection tools increase. To synergize the use of these efforts a standardized system must be developed to enable comparing data points collected in the United States to data points collected in Europe, Africa, Asia or anywhere else in the world. A large group of blueberry breeders in the United States have come together to develop the first crop ontology for blueberry, that is a standardized way of describing their data collection. This monumental effort is the first step towards being able to operate collaboratively on a more global scale and transition to supportive data management systems like databases. The results of this effort, the crop ontology, has been made available through multiple public repositories which are all collaborating to support blueberry breeding around the globe.

Technical Abstract: Breeding programs around the world continually collect data on large numbers of individuals. To be able to combine distantly collected datasets, communities have been coming together to develop standard operating procedures for data collection and measurement. One such method is a crop ontology, or a standardized vocabulary for collecting data on commonly measured traits. The ontology is also computer-readable to facilitate utilization of data management systems like databases. Blueberry breeders and researchers across the United States have come together to develop the first standardized crop ontology in blueberry (Vaccinium spp.). Herein, we provide a review and report on the construction of the first blueberry crop ontology and the 183 traits and methods included within. This is a formal invitation to scientists across Vaccinium species – such as other blueberry species, cranberry, lingonberry, and bilberry – to utilize the described crop ontology to collect phenotypic data of greater quality and consistency, interoperability, and computer readability. Crop ontologies as a shared data language, benefits the entire worldwide research community by enabling collaborative meta-analyses which can be utilized with genomic data for genome-wide association studies (GWAS) and genomic selection (GS).