Intelligent Machines and Plant Disease Forecasting Systems: Digital Solution for Managing Crop-Stressors Toward Food Security in Africa

Abstract

Agriculture in sub-Saharan Africa is facing increasing threats from climate change, pest and disease outbreaks, water stress, and diminishing labor availability. Traditional methods of managing these issues, such as manual pest control and field surveillance, are no longer viable for large-scale farming operations. The integration of intelligent technologies, including artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT), and drones, offers innovative solutions. These technologies, alongside plant disease forecasting platforms like PLANTPlus, WISDOM, FAST, and EPIDEM, can accurately predict pest and disease risks based on environmental and edaphic data. By enabling timely and precise interventions, such systems enhance crop productivity, reduce reliance on agrochemicals, and contribute to a more sustainable and food secure future for Africa. This review explores the potential of these digital tools in mitigating agricultural losses and stresses the importance of their adoption in the region.