Comparative Performance of Aerial RGB vs. Ground Hyperspectral Indices for Evaluating Water and Nitrogen Status in Sweet Maize

• Published in: Agronomy (Basel) Vol. 14; no. 3; p. 562
• Main Authors: Colovic, Milica, Stellacci, Anna Maria, Mzid, Nada, Di Venosa, Martina, Todorovic, Mladen, Cantore, Vito, Albrizio, Rossella
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.03.2024
• Subjects: Agricultural production; Agriculture; Chlorophyll; Climatic conditions; Color imagery; Corn; Crop diseases; Crops; Data analysis; Gas exchange; hyperspectral sensors; Irrigation; Leaf area; Leaf area index; Leaves; Moisture content; Multivariate analysis; Nitrogen; Parameters; Physiology; Plant diseases; Principal components analysis; Radiation; red-edge region; red-green-blue indices; Remote sensors; Stomata; Stomatal conductance; Transpiration; UAV; Unmanned aerial vehicles; Vegetation; Vegetation index; Water; water and nitrogen stresses; Water content; Wheat; Zea mays L

This study analyzed the capability of aerial RGB (red-green-blue) and hyperspectral-derived vegetation indices to assess the response of sweet maize (Zea mays var. saccharata L.) to different water and nitrogen inputs. A field experiment was carried out during 2020 by using both remote RGB images an...