Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Optimizācija attiecībā uz sējas datumu× | Augu augšanas simulācija× | |
|---|---|---|
| Nozare | Agronomija | Agronomija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 2006 | 2003 |
| Autors≠ | P. K. Aggarwal, N. Kalra, IARI India | John W. Jones, Gerrit Hoogenboom et al. |
| Tips≠ | Decision support pipeline | Computational pipeline |
| Pirmavots≠ | Aggarwal, P. K., Kalra, N., Chander, S., & Pathak, H. (2006). InfoCrop: A decision support system for crop planning and resource management at farm level. Agricultural Systems, 88(1), 56-77. link ↗ | Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Basso, B., Hunt, L. A., ... & Winter, S. R. (2003). The DSSAT cropping system model. European journal of agronomy, 18(3-4), 235-265. DOI ↗ |
| Citi nosaukumi≠ | Planting date optimization, Sowing time selection, Phenological timing | Crop phenological model, Growth stage simulation |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | Sowing Date Optimization is a decision support pipeline for determining optimal crop planting dates that align phenological development with favorable environmental windows, maximizing yield and reducing climate risk. Developed by crop modelers (Aggarwal, Semenov) in the 2000s, this method combines crop simulation, climate data, and risk analysis to identify safe, profitable sowing windows. | Crop Growth Simulation is a computational pipeline for predicting daily or seasonal crop development, biomass accumulation, and yield under varying environmental conditions. Developed by Jones and colleagues in the DSSAT framework, this method integrates agronomic knowledge with process-based modeling to enable decision support in field management. |
| ScholarGateDatu kopa ↗ |
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