Why use the Guidelines?

The Guidelines version 2.0 supports the use of the Crop Ontology (CO) Trait Dictionary Template (TD) v.5.1 for developing a new species-specific ontology. The TD Template is a structured format that can be used to compile, curate, and harmonize the phenotypic variables for the crop and produce an ontology.

We strongly recommend reading and applying the Guidelines to develop a high-quality Trait Dictionary. This is the condition to enable the use of Crop Ontology by a wide community, including industries, and robust mapping with other ontologies. 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 for e.g. studies in comparative genomics or for grouping traits for a family or a clade. Once the TD is finalised and is considered stable, it can be uploaded and published on the Crop Ontology Curation Tool website with a CC BY 4.0 license. It will then be synchronized with the Ontology Lookup Service of the European Bioinformatics Institute (EMBL-EBI) and Agroportal, a registry of ontologies in agriculture and related domains.

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 (MIAPPE2020) and also by the Breeding Application Programming Interface (BrAPI).

What is new in Version 2?

The Crop Ontology evolves to address the feedback of curators and contributors, as well as the new types of trait measurement methods and modelling. Therefore, the Guidelines need regular revision. In Version 2, some sections and tables have been revised to improve their clarity. New sections were added, such as ‘The boundaries of the CO Model’ about the metadata that describes the trait but is not part of the CO model, like time series, timestamp, subsamples, and experiment factors. Frequently Asked Questions and a bibliography for further reading were added as well as guidance in defining the abiotic and biotic stress variables in Annex 1.

The list of method types has been augmented with the prediction type to include trait predictive tools like Near-Infrared Spectroscopy (NIRS) which are not calculations with a formula. A new method class was added to include trait classification methods using Machine Learning algorithms. According to Table 5, we have also added a Description class.

Crop Ontology is an open collaborative product

We acknowledge the valuable contribution of the curators (see list below) to the maintenance of quality content addressing the guidelines recommendations, and partners’ active collaboration. The development of a crop-specific ontology is a community-driven effort that is usually coordinated by a curator (or curators) nominated 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.

Guidelines Authors and Reviewers

The first version of the Guidelines was written by Julian Pietragalla, Integrated Breeding Platform, and Léo Valette, formerly Research assistant at Bioversity international. The revised version 2.0 was written by Julian Pietragalla (IBP), Rosemary Shrestha (CIMMYT), Marie-Angélique Laporte (Alliance Bioversity-CIAT) and Elizabeth Arnaud (Alliance Bioversity-CIAT) and Tom Hazekamp (Consultant for the Alliance), and submitted for feedback to Célia Michotey (INRAe, URGI),Cyril Pommier (INRAe, URGI), Françoise Potier (CIRAD) David Waring (Cornell University)

Citation

Pietragalla J., Valette L., Shrestha R., Laporte M.-A., Hazekamp T., Arnaud E. Guidelines for creating crop-specific ontologies to annotate phenotypic data, version 2.0, Alliance Bioversity International-CIAT, 2020

Grants

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’ support, 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).

Ontology principal curators in 2020 and 2021