A team of scientists has received a $100,000 grant to refine an app that uses artificial intelligence to diagnose crop diseases, and aims to help millions of Afrikan smallholders.

The CGIAR Research Program on Roots, Tubers and Bananas team won the grant during big data conference in Colombia on 21 September 2017 as part of the CGIAR Platform for Big Data in Agriculture Inspire Challenges.

The app to be used against cassava brown streak disease and the cassava mosaic disease, is expected to be rolled out in 2018.

โ€œWe think the most important value we will create will be through [agricultural] extension workers already helping farmers.โ€David Hughes, Penn State University

It accurately diagnoses diseases in the field and will combine mobile phone short message service (SMS) alerts to farmers in rural Afrika.

David Hughes, associate professor of entomology and biology at US-based Penn State University, who leads the project together with James Legg, a plant virologist with the International Institute of Tropical Agriculture, Tanzania, say the team needs to continue field-testing and improving its user-friendliness.

The appโ€™s conception was in 2012 but got developed in June-September 2017 through about US$300,000 funding from Penn State University, Hughes told SciDev.Net in an interview.

The app uses a Google programme called TensorFlow that allows machines to train and learn. โ€œWe trained it to recognise plant diseases. What the app does in real-time is to assign a score to a video being captured,โ€ said Hughes. โ€œThat score is the probability that the plant in the video shows symptoms of one of five diseases or pests.

โ€œWe think the most important value we will create will be through [agricultural] extension workers already helping farmers, and most of whom do already own smartphones. Itโ€™s realistic to anticipate that [most] farmers in Sub-Saharan Afrika will have smartphones capable of running the app within five to ten years.โ€

According to Hughes, the projectโ€™s expansion is aimed at collecting more images to train the machine to identify more diseases in more crops โ€” such as banana, sweet potato and yam โ€” as well as work with farmer groups to provide local language apps they want to use.

App for Cassava Disease Diagnosis.

Legg adds that so far it distinguishes five major types of damage to cassava plants: three diseases and two types of pest damage.

Cassava virus diseases alone, explains Legg, cause losses of more than $1 billion annually in Afrika, and threaten food and income security of over 30 million farmers in East and Central Afrika.

โ€œThe main target will be farmers in Sub-Saharan Africa. However, we will be working with the global network of CGIAR, and this means that the app could equally be of value in other parts of the developing world, such as Latin America and Asia.โ€

Peter Okoth, a consultant agronomist at the Kenya-based Newscape Agro Systems Ltd, tells SciDev.Net that smallholders in Africa cannot afford basic agricultural inputs, and thus well planned value chain arrangement with key players are needed to make its potential roll-out in Afrika feasible.

For this app to generate the desired impact, the developers must partner with service providers and plant-health specialists and financiers to solve the problems,โ€ explains Okoth. โ€œThe CGIAR needs to move a step further and constitute action consortia with membership drawn from an array of actors who are needed to address the practical aspects of solving the crop problems jointly with the farmers.โ€ โ€‹

Challenges in dissemination, according to Okoth, include information distribution and gaining potential usersโ€™ confidence that it will solve their problems as well as sustainability.

This piece was produced by SciDev.Netโ€™s Sub-Saharan Africa English desk.

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