Results of using machine learning and a proximal canopy reflectance sensor to predict biomass and nutritional quality in tropical forages (Urochloa humidicola) in three different locations in Colombia
Attributes such as biomass and nutritional quality are characteristics that allow for the selection of better pastures and, therefore, for obtaining greater quantities of meat and milk from livestock feed. However, the laboratory analytical method used to calculate these attributes is inefficient fo...
| Main Authors: | , , , |
|---|---|
| Format: | Informe técnico |
| Language: | Inglés |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/179954 |
Similar Items: Results of using machine learning and a proximal canopy reflectance sensor to predict biomass and nutritional quality in tropical forages (Urochloa humidicola) in three different locations in Colombia
- Near-infrared spectroscopy and wet chemistry dataset for forage nutritional quality assessment in Urochloa humidicola
- Predictive modeling of nutritional quality in Urochloa pastures from multispectral sensors and images using machine learning approaches
- Dataset: Multi-view video sequences of Megathyrsus maximus and Urochloa spp. in field conditions for 3D reconstruction and temporal phenotyping
- La teledetección como herramienta para la prevención, seguimiento y evaluación de incendios e inundaciones
- Predicción de la condición corporal de bovinos en base al análisis espectral NIRS de muestras de heces. Comunicación
- High-resolution image dataset for the automatic classification of phenological stage and identification of racemes in Urochloa spp. hybrids