Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Kartēšana pēc nezāļu blīvuma× | Augu augšanas simulācija× | |
|---|---|---|
| Nozare | Agronomija | Agronomija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads | 2003 | 2003 |
| Autors≠ | Roland Gerhards, Søren Christensen | John W. Jones, Gerrit Hoogenboom et al. |
| Tips≠ | Spatial survey pipeline | Computational pipeline |
| Pirmavots≠ | Gerhards, R., & Christensen, S. (2003). Real-time weed detection, decision making and patch spraying in maize, sugarbeet, winter wheat and winter barley. Weed Research, 43(6), 385-392. DOI ↗ | 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≠ | Weed mapping, Spatial weed survey, Weed sampling | Crop phenological model, Growth stage simulation |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | Weed Density Mapping is a spatial survey pipeline for measuring and mapping weed distributions across fields to support targeted herbicide application and management decisions. Developed by Gerhards, Christensen, and others in precision agriculture (2000s), this method combines field sampling or remote sensing with geostatistics to create weed pressure maps, enabling variable-rate control strategies. | 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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