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## Abstract {.page_break_before} | ||
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Population growth and climate change require extraordinary efforts to increase efficiency in breeding programs around the world. In the last few years, new phenotyping techniques, genomics technologies, and genomic prediction approaches have provided a boost in genetic gain in breeding, but have also created a flood of data that needs careful management to be fully harnessed. Data integration is a significant challenge with multiple types of data being collected and stored by a variety of disparate systems. | ||
The Breeding API (BrAPI) project is an international, grass-roots effort to enable more efficient data management by enabling interoperability among research databases and tools, using a standardized RESTful web service API specification for communicating breeding related data. | ||
This community driven standard is software agnostic and free to be used by anyone interested in breeding data management, including trial, germplasm, phenotypic, and genotyping data management. | ||
This manuscript presents the current version of BrAPI, the substantial growth of the project, and a wide variety of open source breeding research tools with active BrAPI implementations. | ||
Population growth and climate change require extraordinary efforts to increase efficiency in breeding programs around the world. In the last few years, new phenotyping techniques, genomics technologies, and genetic approaches such as genomic prediction have provided a boost in genetic gain in breeding, but have also created a flood of data that needs careful management to be fully harnessed. In particular, data integration is a challenge due to the multiple types of data being handled by a variety of disparate and dispersed systems. | ||
The Breeding API (BrAPI) project is an international, grass-roots effort to enable more efficient data management by enabling interoperability among research databases and tools, using a standardized RESTful web service API specification for exchanging breeding related data. | ||
This community driven standard is software agnostic and free to be used by anyone interested in plant breeding, genetics and agronomy data management, including trial, germplasm, phenotyping, and genotyping data management. | ||
This manuscript presents the current version of BrAPI, the substantial growth of the project, and a wide variety of open source plant genetics research tools with active BrAPI implementations. |
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### Phenotyping | ||
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Phenotyping is fundamental to plant breeding, providing the accurate, high-quality data needed for downstream analyses and decisions. It goes beyond simple data collection, requiring a thorough understanding of research questions and strategic data gathering to ensure successful outcomes. Effective phenotyping can make or break a research project, underscoring the importance of mastering its techniques. The BrAPI specification supports phenotypic data throughout the entire breeding pipeline, from initial collection and standardization to publication and archiving. The community has developed BrAPI-compatible tools to facilitate early data standardization, efficient storage, and curation of phenotypic data and trait metadata. Additionally, there are ongoing efforts to create tools for managing images and other high-throughput phenotyping techniques, further enhancing the precision and efficiency of plant breeding research. | ||
Phenotyping is fundamental to plant breeding, providing the accurate, high-quality data needed for downstream analyses and decisions. It goes beyond simple data collection, requiring a thorough understanding of research questions and strategic data gathering to ensure successful outcomes. Effective phenotyping can make or break a research project, underscoring the importance of mastering its techniques. The BrAPI specification supports phenotypic data throughout the entire phenomics and breeding pipeline, from initial collection and standardization to analysis, publication and archiving. The community has developed BrAPI-compatible tools to facilitate early data standardization, efficient storage, and curation of phenotypic data and trait metadata. Additionally, there are ongoing efforts to create tools for managing images and other high-throughput phenotyping techniques, further enhancing the precision and efficiency of plant breeding research. |
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