Research Case 1: Agriculture (Crop Farming)

1. Sector Description

Crop farming is the backbone of Africa’s agricultural economy, contributing significantly to GDP, employment, and food security. It encompasses the cultivation of cereals, legumes, tubers, and vegetables. Key crops include maize, rice, millet, sorghum, yams, cassava, and groundnuts.

2. Countries with Significant Resources

• Nigeria – Africa’s largest cassava and yam producer.

• Ethiopia – A major producer of teff, maize, and wheat.

• Kenya – Known for maize, beans, and horticultural crops.

• Ghana – Key producer of maize, cassava, rice, and plantain.

• Zambia, Malawi, Tanzania – Extensive maize and legume farming.

3. AiAfrica Research Focus and AI Applications

Under the AiAfrica Project, research teams in the Crop Farming Lab are using AI to drive digital agricultural transformation by focusing on:

• Precision Farming Models using satellite imagery and sensor data for optimal planting times and pest/disease detection.

• Yield Prediction Algorithms that use machine learning to forecast harvest quantities based on historical weather and soil data.

• AI-driven Supply Chain Forecasting to reduce post-harvest losses and optimize logistics.

• Soil Health AI Diagnostics through image-based classification for nutrient profiling.

These AI solutions are co-designed with local universities and agritech startups across Africa and piloted in Ghana, Kenya, and Nigeria.

4. Proof of Value and Potential Impact

In Ghana, an AiAfrica-supported pilot using drone imagery and AI classification models led to a 27% increase in maize yields across 50 farms in the Eastern Region.
In Kenya, smart irrigation systems powered by predictive AI reduced water use by 35% while maintaining productivity.
Across Nigeria, machine learning models built with local climate data improved cassava yield predictions, reducing uncertainty by 40%.

5. Eligibility to Join the Research Lab

Participation in the Crop Farming Research Lab is open to:

• Students, researchers, and professionals with a background in agriculture, AI, agribusiness, or environmental science.

• Participants must be certified under the AiAfrica Prompt Engineering or Sectoral AI Training Program, having completed at least the Foundational and Intermediate levels.

• Each member must commit to a capstone project aligned with food security, agri-innovation, or climate resilience.

Join the Team : https://chat.whatsapp.com/BDCozak2iDLDpRgMndsRT6