SmartNitro Project Tests AI Models to Improve Soil and Crop Nitrogen Management

Researchers at the DIPPER Lab working on the British Council-funded SmartNitro project under the Going Global Partnerships initiative have conducted field trials to test Artificial Intelligence models using paired multispectral images of crops and soil profiles.

 The field activity was aimed at validating the developed models while collecting continuous datasets to build a structured database linking soil nutrient levels with crop nitrogen status.

 The data will support further model improvement and future deployment.

 SmartNitro uses multispectral drones to capture farmland images and applies artificial intelligence to generate nitrogen maps.

 These maps are converted into practical recommendations to guide farmers on nitrogen application.

The system is expected to help farmers improve yields, reduce input costs, and limit excessive fertilizer use that can affect soil quality and the environment.

SmartNitro is one of seven research-led innovations developed by the DIPPER Lab and funded by the British Council through the Going Global Partnerships Grant under the IAU Funded Projects.

 The initiative supports the translation of research into practical solutions for farmers in Ghana and across Africa.