Integrating and sharing accession-level and omics-size genotype, phenotype and environmental data: Experiences at the International Potato Center (CIP).

Plant breeding consists in the creation and selection of new genotypes. This involves not only keeping records across generations and environments but also accommodating data of increasing resolution on genotypes, phenotypes, and growth environments. Some such high-resolution characterization methods are Near-Infrared spectroscopy, metabolomics, next-generation sequencing and high resolution spatial-temporal-spectral photos. A first need is the integration and retrieval of this information. Such an integrated and complete set can be described in breeder’s terms in six dimensions: a plant phenotype (P) is the result of a genotypes (G) interaction with its environment (E) given certain field management (M) practices. In addition, data on the administrative (A) context should be kept including staff involved, objectives and, if applicable, projects and donors; as well as on data documentation standards (S) like ontologies. The latter play an important part in exchanging and aggregating information. Here we describe the adoption of the ‘Biomart’ database for this purpose. While Biomart was developed originally to accommodate gene and sequencing data at a genomic scale we describe here how it can be used for breeding program data. This is being illustrated by current data warehousing in the potato breeding program at the International Potato Center (CIP). Particularly, genotype and phenotype can be transparently combined for further analysis in the decision process for the selection of new genotypes

THE MUST MODEL EVALUATION EXERCISE: PATTERNS IN MODEL PERFORMANCE

As part of the COST 732 action more than a dozen different research groups have modelled the MUST experiment, as simulated in a wind tunnel. The model evaluation guidance developed within COST 732 recommends \u27exploratory data analysis\u27 as one of the elements in model validation. Experience has shown that such exploratory analysis is crucial to reveal shortcomings of models that might otherwise pass unnoticed. Conditions are best for detecting common patterns and anomalies if you have a situation where several models are put into a common framework – like the case at hand. The available material provides a unique opportunity to identify and explore patterns within model performance

THE MUST MODEL EVALUATION EXERCISE: STATISTICAL ANALYSIS OF MODELLING RESULTS

The first validation exercise of the COST action 732 lead to a substantial number of simulation results for comparison with the MUST wind tunnel experiments. Validation metrics for selected simulation results of the flow field and the concentrations are presented and compared to the state of the art. In addition mean metrics and corresponding scatter limits are computed from the individual results

An episodic event of pollen transport of European beech

The meteorological impacts on pollen emission and spread in a typical Central European forest of mixed deciduous and coniferous trees are investigated. Pollen samples as well as meteorological measurements have been conducted during the flowering period of spring flowering tree species in 2009. An episodic event of pollen transport to the study area is analyzed in detail with the aid of hourly backwards trajectories. The results indicate that the experimental set-up was well designed for a thorough meteorological analysis of the pollen counts

The must model evaluation exercise: statistical analysis of modelling results

The first validation exercise of the COST action 732 lead to a substantial number of simulation results for comparison with the MUST wind tunnel experiments. Validation metrics for selected simulation results of the flow field and the concentrations are presented and compared to the state of the art. In addition mean metrics and corresponding scatter limits are computed from the individual results

ENSEMBLE Dispersion Modelling. Part II. Application and Evaluation.

Abstract not availableJRC.H-Institute for environment and sustainability (Ispra

The MUST model evaluation exercise: Patterns in model performance

As part of the COST 732 action more than a dozen different research groups have modelled the MUST experiment, as simulated in a wind tunnel. The model evaluation guidance developed within COST 732 recommends 'exploratory data analysis'as one of the elements in model validation. Experience has shown that such exploratory analysis is crucial to reveal shortcomings of models that might otherwise pass unnoticed. Conditions are best for detecting common patterns and anomalies if you have a situation where several models are put into a common framework - like the case at hand. The available material provides a unique opportunity to identify and explore patterns within model performance

The must model evaluation exercise: statistical analysis of modelling results

The first validation exercise of the COST action 732 lead to a substantial number of simulation results for comparison with the MUST wind tunnel experiments. Validation metrics for selected simulation results of the flow field and the concentrations are presented and compared to the state of the art. In addition mean metrics and corresponding scatter limits are computed from the individual results