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Palabras clave – provistas por la editorial

nitrogen nutrition index; n/a; soil organic carbon; yield estimation; hyperspectral sensor; crop modeling; crop residue management; land use change; flat-fan atomizer; vegetation index; septoria tritici blotch; crop simulation model; temporal variability; spectral-weight variations in fused images; plant; EPIC model; large cardamom; crop inventory; proximal sensing; sorghum biomass; soil; UAV; Integrated Administration and Control System; canopy temperature depression; fractional cover; Cropsim-CERES Wheat; hyperspectral data; yield; wheat; precision farming; SPAD; AquaCrop; prediction modeling; spectral simulation; leaf nitrogen concentration; machine learning; crop production; protein content; Á Trous algorithm; spatial variability; variable rate technology; crop type mapping; Tarim Basin; leaf area index; management zone; irrigation; multi-spectral; agricultural land-cover; crop modelling; dynamic model; satellite images; climate change; control variables; generalized model; Sentinel-2 satellite imagery; vegetation indices; vegetable monitoring; Sentinel-2; remote sensing; cultivars; crop growth model; yield monitoring; big data technology; conservation agriculture; GIS; fAPAR; droplet drift; simulation analysis; durum wheat; hydroponic; grain yield; Leaf Area Index; NDVI; precision agriculture; relative frequencies; soil stoichiometry; habitat assessment; data assimilation; satellite; species modelling; ?13C; disease; nitrogen; yield mapping; UAV chemical application; RGB images; decision support system for agrotechnology transfer (DSSAT)