Crop of interest
| Selected crop per country along with key words for PhDs and MSc subjects | |||
|---|---|---|---|
| Countries | Crops | Key words for PhD candidates | Key words for MSc candidates |
| Benin | Pineapple | Artificial intelligence + Crop biophysical models+ Precision farming + Satellite | Artificial intelligence + Crop biophysical models OR Precision farming + Satellite |
| Maize | Machine learning + Image processing, Internet of things + Pest management + Precision farming | Pest Management + Precision farming | |
| Groundnut | Precision nutrients, precision pest management and high throughput phenotyping + artificial intelligence | Precision nutrient and water management + remote sensing | |
| African eggplants | - | Genomics and Precision Agriculture | |
| Ghana | Pineapple | Artificial intelligence + Crop biophysical models+ Precision farming + Satellite | Artificial intelligence + Crop biophysical models OR Precision farming + Satellite |
| Sorghum | Artificial intelligence + Crop biophysical models+ Precision farming + Satellite + Remote Sensing of Soils | Geospatial Data and mapping + precision farming OR Remote Sensing of Soils + Precision farming | |
| Cassava | Artificial intelligence + Crop biophysical models+ Precision farming + Satellite + Remote Sensing of Soils | Geospatial Data and mapping+ Precision agriculture OR Remote Sensing of Soils and Crops (including Phenotyping) + Precision Agriculture | |
| Maize | - | Climate-smart pest protection strategies for selected Maize varieties in Ghana +Artificial intelligence | |
| Eswatini | Maize | Application of models to predict crop growth and yield (Artificial intelligence + Decision support + Precision nutrient) | Machine learning models + pest management + yield OR Detection of pest infestation and spot application of pesticides |
| Sweet Potatoes | Screening of planting material through use of biotechnology techniques (On farm experimentation + Genomics and Precision agriculture) | Screening of planting material through use of biotechnology techniques (On farm experimentation + Precision agriculture) OR Pest and disease management + Precision farming | |
| Potato | Screening of planting material through use of biotechnology techniques (On farm experimentation + Genomics and Precision agriculture) | Screening of planting material through use of biotechnology techniques (On farm experimentation + Precision agriculture) OR Pest and disease management + Precision farming | |
| Tomato | - | Machine learning models + disease + prediction of tomatoes | |
| Rwanda | Potato | Site specific nutrient + modeling + artificial intelligence +climate smart agriculture OR Field Pest Management and remote sensing + Artificial intelligence +climate smart agriculture | Site specific nutrient + modeling + artificial intelligence +climate smart agriculture OR Field Pest Management and remote sensing + Artificial intelligence +climate smart agricultureagriculture |
| Beans | Site specific nutrient + modeling + artificial intelligence +climate smart agriculture | Site specific nutrient + modeling + artificial intelligence +climate smart agriculture OR Bacterial blight, anthracnose and rust diseases management + Precision farming | |
| Cassava | Artificial intelligence + Crop biophysical models+ Precision farming + Satellite + Remote Sensing of Soils + Internet of Things + Site specific nutrients | Detection, identification and mapping of cassava brown streak and cassava mosaic virus diseases in Rwanda using different remote sensing technologies OR Artificial intelligence and climate smart agriculture practices for cassava growth and yield parameters | |
| Sorghum | - | Geospatial Data and mapping + precision farming OR Remote Sensing of Soils + Site specific nutrients | |