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Maize is considered globally as the most important agricultural grain which is staple food for many humans and feed to livestock. There is need to enhance productivity through management tools to meet the demand for growing populations. Farmers are likely to be interested in technologies that are beneficial to their operations. A technology that could assist farmers to produce staple foods e.g. maize more efficiently is remote sensing. The paper focuses on reviewing published research that deals with application of remote sensing in maize farming particularly the spectral characteristics of maize leaves, classification and mapping. It further surveys the application of remote sensing in detecting foliar nitrogen deficiency, water stress and disease infestations in maize. Remote sensing can be considered as a fast, non-destructive and relatively cost-effective method to study biophysical and biochemical parameters of vegetation across vast spatial areas. However, selection of appropriate sensors with special attention on their spatial and spectral resolutions as well as processing techniques will validate a success story for remote sensing application in maize production.
Keywords: Maize; Nutrient monitoring; Remote sensing; Spectral reflectance; Yield predictions
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