Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Оценка урожайности сельскохозяйственных культур× | Моделирование роста сельскохозяйственных культур× | |
|---|---|---|
| Область | Агрономия | Агрономия |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2015 | 2003 |
| Автор метода≠ | Agronomic research institutions (CIMMYT, ICRISAT, IRRI) | John W. Jones, Gerrit Hoogenboom et al. |
| Тип≠ | Analytical and predictive pipeline | Computational pipeline |
| Основополагающий источник≠ | 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 ↗ | 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 ↗ |
| Другие названия≠ | Yield forecasting, Harvest prediction, Yield monitoring | Crop phenological model, Growth stage simulation |
| Связанные | 5 | 5 |
| Сводка≠ | 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. | 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. |
| ScholarGateНабор данных ↗ |
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