ArticleG3 (Bethesda, Md.)2022
Breedbase: a digital ecosystem for modern plant breeding.
Article in G3 (Bethesda, Md.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- Identification of germplasm and genomic markers associated with reduced T-2 and HT-2 mycotoxin accumulation in oat.The plant genome · 2026Article
- Advances in root phenotyping: high-throughput imaging, computational tools, and integrative approaches for crop improvement.Journal of experimental botany · 2026Review
- Harnessing artificial intelligence in plant breeding: innovations in digital phenotyping and breeding methodologies.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Beyond Data: Artificial intelligence, knowledge graphs, and the next revolution in wheat breeding.Plant communications · 2026Review
- Association of sugarcane cold tolerance with stem borer resistance.Scientific reports · 2026Article
- G2P datasets: a hub for genomic datasets for predictive modeling in plants and animals.G3 (Bethesda, Md.) · 2026Article
- Adoption of Standard Reference SNP Identifiers in Agricultural Genomics for Interoperability and Data Reuse.Scientific data · 2026Article
- CottonGen 2025: a knowledgebase for cotton genomics, genetics, and breeding research.Genetics · 2026Article
- Spatial coordination between leaf gradient and temperature response in barley.The Plant journal : for cell and molecular biology · 2026Article
- QTL mapping of oat crown rust resistance in Australian fields and identification of a seedling resistance locus in oat line GS7.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Improving annotation, access, and comparison of nutritional composition data for underutilized crops.Database : the journal of biological databases and curation · 2026Article
- Advances and prospects of genomic-assisted breeding in roots, tubers, and banana crops.Frontiers in plant science · 2026Review
- Article
- AI-integrated digital breeding for crop improvement.Frontiers in plant science · 2026Review
- Post-composing ontology terms for efficient phenotyping in plant breeding.Database : the journal of biological databases and curation · 2025Article
- Agricultural landscape genomics to increase crop resilience.Plant communications · 2025Review
- Genomic Predicted cross performance: a tool for optimizing parental combinations in breeding programs.Database : the journal of biological databases and curation · 2025Article
- BrAPI v2: real-world applications for data integration and collaboration in the breeding and genetics community.Database : the journal of biological databases and curation · 2025Article
- Pan-phylum genomes of hornworts reveal conserved autosomes but dynamic accessory and sex chromosomes.Nature plants · 2025Article
- Article
Corrections and comments
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Authors and funding
57 authors.
Funding
Abstract
Modern breeding methods integrate next-generation sequencing and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This data-driven approach hinges on strong foundations in data management, quality control, and analytics. Of crucial importance is a central database able to (1) track breeding materials, (2) store experimental evaluations, (3) record phenotypic measurements using consistent ontologies, (4) store genotypic information, and (5) implement algorithms for analysis, prediction, and selection decisions. Because of the complexity of the breeding process, breeding databases also tend to be complex, difficult, and expensive to implement and maintain. Here, we present a breeding database system, Breedbase (https://breedbase.org/, last accessed 4/18/2022). Originally initiated as Cassavabase (https://cassavabase.org/, last accessed 4/18/2022) with the NextGen Cassava project (https://www.nextgencassava.org/, last accessed 4/18/2022), and later developed into a crop-agnostic system, it is presently used by dozens of different crops and projects. The system is web based and is available as open source software. It is available on GitHub (https://github.com/solgenomics/, last accessed 4/18/2022) and packaged in a Docker image for deployment (https://hub.docker.com/u/breedbase, last accessed 4/18/2022). The Breedbase system enables breeding programs to better manage and leverage their data for decision making within a fully integrated digital ecosystem.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.