Abstract
Besides phenotypic data from field trials and molecular data from lab
experiments, modern plant breeding programs generate a wide variety of
data, for instance pedigree, randomization, geostatistical or climate
data. Due to the lack of an integrated database system, breeders
generally exploit only part of these data for selection decisions or
retrieve only part of the information present in the data. Most
approaches in genomics, however, develop their full power only when
they are based on analyses of large numbers of genotypes from multiple
crosses and current as well as past generations. We have developed a
flexible data management and -analyses system for storage and quality
control of plant breeding data. It is implemented using the PostgreSQL
database management system and linked to the R software environment for
integrated statistical analyses of phenotypic and genomic data. The
database structure is capable of managing the following types of data
observed in breeding programs of all major crops: (a) germplasm data of
any species including pedigree data, (b) phenotypic data of any trait
and trait complexity, (c) trial management data for any field and trial
design, (d) molecular marker data for all common types of markers, as
well as (e) project and study management data.
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