Daphne: a generic database to integrate multiscale agronomic and phenotypic information for crop modelling
Studies of genotype x environment x management (GXEXM) interactions commonly use Crop Simulation Models (CSM). The minimum datasets required for a successful model implementation are multi-scale, multi-species and multi-disciplinary. We observed that although they are organized differently, CSM input files and field experiment datasets shared the same measurements (yield, leaf area index, biomass, etc.) and a few similar tables corresponding to the minimum dataset (weather, soil, crop, and management data). Based on this analysis, we have designed the schema of DAPHNE. We used the relevant technology of metadata. Thus, in DAPHNE, all variable labels are stored in a metadata table including the units and methods of measurements and the observed and experimental units. The main advantage of this technology is that the addition of any variable does not imply to reconsider the structure of the database. Database query performance is also improved. DAPHNE already has a wide application in GXEXM experiments on sorghum and sugarcane. The genericness of the schema of DAPHNE can allow intercomparison of CSM that require the same datasets with no common data structure.
| Main Authors: | , , , |
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| Format: | conference_item biblioteca |
| Language: | eng |
| Published: |
AgMIP
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| Online Access: | http://agritrop.cirad.fr/587854/ http://agritrop.cirad.fr/587854/1/ID587854.pdf |
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| Summary: | Studies of genotype x environment x management (GXEXM) interactions commonly use Crop Simulation Models (CSM). The minimum datasets required for a successful model implementation are multi-scale, multi-species and multi-disciplinary. We observed that although they are organized differently, CSM input files and field experiment datasets shared the same measurements (yield, leaf area index, biomass, etc.) and a few similar tables corresponding to the minimum dataset (weather, soil, crop, and management data). Based on this analysis, we have designed the schema of DAPHNE. We used the relevant technology of metadata. Thus, in DAPHNE, all variable labels are stored in a metadata table including the units and methods of measurements and the observed and experimental units. The main advantage of this technology is that the addition of any variable does not imply to reconsider the structure of the database. Database query performance is also improved. DAPHNE already has a wide application in GXEXM experiments on sorghum and sugarcane. The genericness of the schema of DAPHNE can allow intercomparison of CSM that require the same datasets with no common data structure. |
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