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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