Lacuna Fund has awarded the Ghanaian-led Artificial Intelligence (AI) firm, KaraAgro AI and its consortium partners a grant towards the creation of a machine learning dataset for crop disease and pest diagnosis based on crop imagery and spectrometry.

The consortium partners include the Makerere University (Uganda), the Nelson Mandela African Institution of Science and Technology (Tanzania) and Namibia University of Science and Technology (Namibia). Lacuna Fund covers as much as $500,000 budget per project.

KaraAgro AI Foundation and its partners’ project will produce quality open and accessible image and spectrometry datasets from Uganda, Tanzania, Namibia, and Ghana for several crops that contribute to food security in Sub-Saharan Africa, including cassava, maize, beans, bananas, pearl millet, and cocoa. Data scientists and researchers of the team will then use the image and spectral datasets for early disease identification, disease diagnosis, and modelling disease spread, which will ultimately help in breeding resistant crop varieties.

“This project is a unique collaboration across four countries in sub-Saharan Africa with the aim of delivering crop imagery and spectrometry datasets for six important food security crops. The datasets are necessary for building machine learning models for early disease diagnosis and will be relevant for not only the AI and machine learning communities but also for the smallholder farmers and agricultural experts.”
Joyce Nakatumba-Nabende, Makerere University

According to the Founder and Executive Director of KaraAgro AI, Mr Darlington Akogo, his outfit would be supported by the Department of Crop Science of the University of Ghana, and the Cocoa Research Institute of Ghana (CRIG) towards the collection, annotation and baseline modelling of crop disease and pests in Ghana. He added that KaraAgro AI is well-positioned for the creation of machine learning datasets for crop pest and disease diagnosis based on crop imagery and spectrometry data and hope to lead the charge in crop disease and pest management.

“With this funding, we can collect largely localised crop disease and pest data, which can be used towards improving African Artificial Intelligence-for-Agriculture solutions like the KaraAgro AI Android app.

“African farmers, who currently lose up to 40 percent of crop yield due to diseases and pests, would then be able to affordably detect diseases and pests, and boost their yields, using these AI-powered automated tools on mobile devices.”
Mr Darlington Akogo

Lacuna Fund is the world’s first collaborative effort to provide data scientists, researchers, and social entrepreneurs in low- and middle-income contexts globally with the resources they need to produce labeled datasets that address urgent problems in their communities. It aims to disburse funds to institutions to create, expand, and/or maintain datasets that fill gaps and reduce bias in training data used for machine learning; and also make it possible for underserved populations to take advantage of advances offered by AI.

According to Lacuna Fund, the recipients of its first-round funding are unlocking the power of machine learning to alleviate food security challenges. Besides, these recipients will spur economic opportunities and give researchers, farmers, communities and policymakers access to superior agriculture datasets.