Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Kartēšana pēc nezāļu blīvuma× | Kultūraugu ražas prognozēšana× | |
|---|---|---|
| Nozare | Agronomija | Agronomija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 2003 | 2015 |
| Autors≠ | Roland Gerhards, Søren Christensen | Agronomic research institutions (CIMMYT, ICRISAT, IRRI) |
| Tips≠ | Spatial survey pipeline | Analytical and predictive 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 ↗ | 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 | Weed mapping, Spatial weed survey, Weed sampling | Yield forecasting, Harvest prediction, Yield monitoring |
| 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 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. |
| ScholarGateDatu kopa ↗ |
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