About the Crop Ontology

The quality and consistency of agricultural data has greatly improved since the use of digital technologies applies to all steps of the research data lifecycle, particularly at the collection and management stages that integrate standardized ontology terms, such as lists of defined crop traits and variables. Created in 2008 by the CGIAR, the Crop Ontology (CO; http://www.cropontology.org) is an essential source of traits and variables to support the standardization of the breeding databases such as the Integrated Breeding Platform’s BMS (IBP; https://www.integratedbreeding.net/) and the Boyce Thompson Institute’s Breedbase (https://breedbase.org/) (Arnaud et al., 2020). By providing descriptions of agronomic, morphological, physiological, quality, and stress traits along with their definitions and relationships, also including a standard nomenclature for composing the variables, the CO enables digital capture and aggregation of crop trait data, as well as comparison across projects and locations (Shrestha et al, 2012). The crop ontologies follow a conceptual model that defines a phenotypic variable as a combination of a trait, a method and a scale. This model aims at supporting the creation and management of breeders’ field books and the generation of annotated trial data. Annotated data are interpretable, interoperable and reusable.

The development of a crop-specific ontology is a community-driven effort which is usually coordinated by a curator (or curators) nominated from within the community itself. The curator(s) are responsible for coordinating discussions with domain experts and developing a quality Trait Dictionary (TD) using the template. The TD is a structured format which can be used to compile, curate and harmonize the phenotypic variables for the crop. Once the TD is finalised and is considered to be stable, it can be uploaded and published on cropontology.org (http://www.cropontology.org/add-ontology). We strongly recommend reading and applying the Guidelines to develop a high quality Trait Dictionary containing all necessary information for a variable. This is the condition to enable the reuse of Crop ontology by a wide community, including industries, and robust mapping with other ontologies.

The CO was included in the Planteome’s ontology project funded by the National Science Foundation, US (IOS:1340112 award; http://planteome.org). CO’s Traits that are properly described following the guidelines are progressively mapped to the Planteome species-neutral Trait Ontology (TO) maintained by Oregon State University, thus enabling users to search for a trait without consideration of the species (Arnaud et al., 2012; Laporte et al., 2016). This is useful for studies in comparative genomics or for grouping traits for a family or a clade (e.g. legumes) (Cooper et al., 2018). The CO is listed among the most popular ontologies used in agriculture (Leonelli et al., 2017; Harper et al., 2018). To further support the standardization of the breeding data sets, the CO format was adopted by the metadata schema called the Minimum Information About a Plant Phenotype Experiment (MIAPPE https://www.miappe.org/; Ćwiek-Kupczyńska et al., 2016; Papoutsoglou, et al., 2020) and also by the Breeding Application Programming Interface (BrAPI; https://brapi.org/; Selby et al., 2019) that enables the extraction of genotype and phenotype data across databases (Arnaud et al., 2020).

The CO provides the crop ontologies under a CC BY 4.0 license and is regularly synchronized with the Ontology Lookup Service of the European Bioinformatics Institute (EBI, https://www.ebi.ac.uk/ols/search?q=Crop+ontology) and Agroportal, the registry of ontologies in agriculture and related domains (http://agroportal.lirmm.fr/).


The Crop Ontology has existed for 12 years thanks to the dedication of the CGIAR curators for maintaining the quality of the ontologies specific to their Center’s mandate crops. We also acknowledge the crucial contribution of research partners from public and private sectors that comply with the guidelines and submit traits and variables used in their multi-partner projects to expand the ontology content. The Crop Ontology was created with the financial support of Bioversity International and the Integrated Breeding Platform, and is maintained thanks to the CGIAR Research Programmes, the CGIAR Platform for Big Data in Agriculture, all funded by the CGIAR Fund Council and, from 2014 to 2019, with the award of the US National Science Foundation (NSF) to the cROP-Planteome Project (IOS:1340112 award).


Arnaud, E., Laporte, M.A., Kim, S., Aubert, C., Leonelli, S., Miro, B., Cooper, L., Jaiswal, P., Kruseman, G., Shrestha, R., et al. (2020). The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems. Patterns 1(7), 100105.DOI: 10.1016/j.patter.2020.100105. DOI: 10.1016/j.patter.2020.100105

Arnaud, E., Cooper, L., Shrestha, R., Menda, N., Nelson, R.T., Matteis, L., Skofic, M., Bastow, R., Jaiswal, P., Mueller, L, et al., (2012). Towards a reference Plant Trait Ontology for modeling knowledge of plant traits and phenotypes. Proceedings of the International Conference on Knowledge Engineering and Ontology Development. SciTePress, Barcelona, Spain, pp 220–225. DOI: 10.5220/0004138302200225

Cooper, L., Meier, A., Laporte, M.-A., Elser J.L., Mungall, C.J., Sinn, B.T., Cavaliere, D., Carbon, S., Dunn, N.A., Smith, B., et al., (2018). The Planteome database: an integrated resource for reference ontologies, plant genomics and phenomics. Nucleic Acids Research 46: D1168–D1180. doi.org/10.1093/nar/gkx1152

Ćwiek-Kupczyńska, H., Altmann, T., Arend, D., Arnaud, E., Chen, D., Cornut, G., Fiorani, F., Frohmberg, W., Junker, A., Klukas, C., et al., (2016). Measures for interoperability of phenotypic data: minimum information requirements and formatting. Plant Methods. 2016 Nov 9;12:44. doi: 10.1186/s13007-016-0144-4. PMID: 27843484; PMCID: PMC5103589.

Jonquet, C., Toulet, A., Arnaud, E., Aubin, S., Dzalé Yeumo, E., Emonet, V., Graybeal, J., Laporte, M.-A., Musen, M.A., Pesce, P., Larmande, P. (2018). AgroPortal: A vocabulary and ontology repository for agronomy, Computers and Electronics in Agriculture, Volume 144, 2018, p. 126-143, doi: 10.1016/j.compag.2017.10.012.

Laporte, M.-A., Valette, L., Cooper, L., Mungall, C., Meier, A., Jaiswal, P., Arnaud, E., (2016). Comparison of ontology mapping techniques to map plant trait ontologies. Proceedings of the Joint International Conference on Biological Ontology and BioCreative, Oregon State University, Oregon, 2016

Papoutsoglou, E.A., Faria, D., Arend, D., Arnaud, E., Athanasiadis, I.N., Chaves, I., Coppens, F., Cornut, G., Costa, B.V., ĆwiekKupczyńska, et al., (2020). Enabling reusability of plant phenomic datasets with MIAPPE 1.1. New Phytol. doi:10.1111/nph.16544

Selby, P., Abbeloos, R., Backlund, J.E., Basterrechea Salido, M., Bauchet, G., Benites-Alfaro, O.E., Birkett, C., Calaminos, V.C., Carceller, P., Cornut, et al., (2019). BrAPI consortium. BrAPI-an application programming interface for plant breeding applications. Bioinformatics. 2019 Oct 15;35(20):4147-4155. doi: 10.1093/bioinformatics/btz190. PMID: 30903186; PMCID: PMC6792114.

Shrestha, R., Matteis, L., Skofic, M., Portugal, A., McLaren, G., Hyman, G., Arnaud, E., (2012). Bridging the phenotypic and genetic data useful for integrated breeding through a data annotation using the Crop Ontology developed by the crop communities of practice. Frontiers in Plant Physiology v. 3 Article 326: doi: 10.3389/fphys.2012.00326, ISSN: 1664-042X


Book chapter

2011 - Shrestha Rosemary, Guy F Davenport, Richard Bruskiewich and Elizabeth Arnaud in : Monneveux Philippe and Ribaut Jean-Marcel, eds (2011). Drought phenotyping in crops: from theory to practice CGIAR Generation Challenge Programme, Texcoco, Mexico. ISBN: 978-970-648-178-8. 475pp. Chapter is: Development of crop ontology for sharing crop phenotypic information.