With the population in Africa estimated to reach about 2.6 billion by 2050 it has become important that agriculture and food systems are reviewed in order to find innovative approaches at improving food production and utilisation to enhance food security.
Science and technology has been lauded as a means of achieving food security in Africa thereby achieving the second Sustainable Development Goal to end hunger. Artificial Intelligence stands out as one of the emerging technologies with great potential to transform the sector and provide sustainable solutions to food security in Africa.
As part of the program’s work with innovation, we launched the AI for Agriculture & Food Systems (AI4AFS) innovation research network, set up and managed by ATPS, Kumasi Hive and ICIPE. This network will consist of innovation research projects that will develop, deploy, test, and seek to scale responsible and African-led AI innovations that will deepen our understanding of how to deploy sustainable agriculture and food systems in Africa.
The network now invites eligible applicants to submit their Expression of Interest (EOI) for the Artificial Intelligence for Agriculture and Food Systems Innovation Research Network in Africa project. This research fund will support research projects and innovations for up to 18 months duration in the following four priority focus areas in Agriculture and Food Systems:
- Availability: the thematic areas may include:
- Prediction of crop yields (tools to help farmers make ideal decisions in crop yield forecasting and improve smart farming practices that lead to higher yields);
- Prediction of soil management properties (tools for understanding soil conditions and how to boost its performance to support productivity);
- Farm management systems (tools for precision agriculture to detect and perform farm management operations such as planting, irrigation, pollination, weeding, fertilizer application, harvesting, etc.);
- Pest and disease detection (early detection of pests and diseases in the farm and eventual prevention or control);
- Smart mechanization (tools to reduce drudgery in agriculture and minimize inputs, high autonomous and intelligent machines and agribots); and
- Livestock surveillance (for monitoring illnesses, injuries, and even pregnancies).
- Access, priority will be given to:
- Food demand monitoring (tools for real-time monitoring and control of changes in food demand);
- Supply chain management (tools for monitoring food origin, quality, and safety that affords transparency, trust, certification, and traceability of food product supply chain from farm to fork);
- Food retailing (tools for predicting consumer demands, perceptions, and buying behaviour);
- Transportation and storage (preservation of food product quality, to ensure safe food products and to minimize the product damage);
- Inventory management (prediction of daily food demand and to ensure that there are no inventory-related problems).
- Utilization, thematic areas include:
- Modern processing techniques (software algorithms for enhancing heating, cooling, milling, smoking, cooking and drying to ensure high quality and quantity of agrifood products and, at the same time, avoiding overutilization of resources and wastages);
- Minimizing postharvest losses (tools for preservation, processing, safe storage of foods);
- Societal impacts (ecology, infrastructure, livelihoods, nutrition, social systems, crisis and cultural practices of the food systems, understanding implications for inclusion and gender equity);
- Stability, some of the thematic priority areas will include:
- Climate and weather prediction (to help farmers increase yields and profits without risking the crops or livestock from climate vagaries);
- Decision support (support systems to enhance farmers’ choices in crop cultivation, consumer preferences, fashion and trends);
- Yield prediction (prediction of gaps between food production, supply and consumption to inform national agricultural policies, tracking and tracing agricultural commodities along transportation routes);
- Disaster prediction (able to identify impending disasters such as pests and diseases invasions, locust invasion, etc. and enable farmers mitigate them);
- Collective decisions (modelling social interactions, informing policy, and designing markets);
- Training, education and knowledge exchange (enhancing extension service delivery and information sharing); and
- Access to production factors (enhancing access to factors of production such as land, inputs, capital, labour etc. especially for marginalized groups like women, youth and persons with disabilities [PWDs]).
Eligible projects will include the development and/or testing of experimental-stage pilots and/or prototypes, as applicable. The funded projects are required to apply Responsible Artificial Intelligence (Machine Learning, Data Science, etc.), be multidisciplinary, adhere to the highest standards of research excellence, and strive to have direct and lasting benefits to communities in their home countries.
Who can apply?
Eligible research teams with demonstrated experience that are multi-disciplinary, gender-sensitive, inclusive, and equitable in the development, deployment and scaling of responsible AI for agriculture and food systems. Please note there must be a lead organization who will take on the grant as individuals cannot receive funding. Funds will be disbursed through the lead organization.
The Lead applicants must come from any of the sub-Saharan African (SSA) countries.
Grant Amount and Duration
Each project will be required to have a budget ranging between US$40,000 and US$60,000 depending on the scope and scale of the proposed project which must be well justified.
Deadline: May 10, 2022
How to apply
Further details about this opportunity and the application process are well detailed in this call document. Make sure to go through it before applying. Register for a webinar about this call on April 26, 2022.