Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Augu augšanas simulācija× | Kultūraugu ražas prognozēšana× | |
|---|---|---|
| Nozare | Agronomija | Agronomija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 2003 | 2015 |
| Autors≠ | John W. Jones, Gerrit Hoogenboom et al. | Agronomic research institutions (CIMMYT, ICRISAT, IRRI) |
| Tips≠ | Computational pipeline | Analytical and predictive pipeline |
| Pirmavots≠ | 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 ↗ | Lobell, D. B., Thau, D., Seifert, C., Engle, E., & Shadow, B. (2015). A regional crop yield forecasting system for Sub-Saharan Africa. Global Food Security, 5, 6-15. link ↗ |
| Citi nosaukumi≠ | Crop phenological model, Growth stage simulation | Yield forecasting, Harvest prediction, Yield monitoring |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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. | Crop Yield Estimation is an analytical and predictive pipeline for forecasting final crop yield before harvest or monitoring yield accumulation during the growing season. Developed by agronomic research centers (CIMMYT, ICRISAT, IRRI), this method combines field observations, environmental data, and statistical models to predict grain or biomass output, informing harvest planning, market decisions, and performance evaluation. |
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