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Artificial intelligence helps banana growers protect the world’s favourite fruit

The detection tool is built in a mobile app called Tumaini – which means 'hope' in Swahili – and is designed to help smallholder banana growers quickly detect a disease or pest and prevent a wide outbreak from happening. Credit: CIAT
The detection tool is built in a mobile app called Tumaini – which means 'hope' in Swahili – and is designed to help smallholder banana growers quickly detect a disease or pest and prevent a wide outbreak from happening. Credit: CIAT

Using artificial intelligence, scientists created an easy-to-use tool to detect banana pests and diseases. With an average 90% success rate in detecting a pest or a disease, the tool can help farmers avoid millions of dollars in losses.

Bananas are a crucial source of nutrition and income in many countries. However, pests and diseases – Xanthomanas wilt, Fusarium wilt, black leaf streak (or Black sigatoka), to name a few – threaten to damage the fruit. And when a disease outbreak hits, the effects to smallholder livelihoods can be detrimental.

A new smartphone tool developed for banana farmers scans plants for signs of five major diseases and one common pest. In testing in Colombia, the Democratic Republic of the Congo, India, Benin, China, and Uganda, the tool provided a 90% successful detection rate. This work is a step towards creating a satellite-powered, globally connected network to control disease and pest outbreaks, say the researchers who developed the technology. The findings were published this week in the journal Plant Methods.

“Farmers around the world struggle to defend their crops from pests and diseases,” said Michael Selvaraj, CIAT scientist and lead author, who developed the tool with colleagues from Bioversity International in Africa. “There is very little data on banana pests and diseases for low-income countries, but an AI tool such as this one offers an opportunity to improve crop surveillance, fast-track control and mitigation efforts, and help farmers to prevent production losses.” Co-authors included researchers from India’s Imayam Institute of Agriculture and Technology (IIAT), and Texas A&M University.

The tool is built into an app called Tumaini – which means 'hope' in Swahili – and is designed to help smallholder banana growers quickly detect a disease or pest and prevent a wide outbreak from happening. The app aims to link them to extension workers to quickly stem the outbreak. It can also upload data to a global system for large-scale monitoring and control. The app’s goal is to facilitate a robust and easily deployable response to support banana farmers in need of crop disease control.

“The overall high accuracy rates obtained while testing the beta version of the app show that Tumaini has what it takes to become a very useful early disease and pest detection tool,” said Guy Blomme, from Bioversity International. “It has great potential for eventual integration into a fully automated mobile app that integrates drone and satellite imagery to help millions of banana farmers in low-income countries have just-in-time access to information on crop diseases.”

 

This article is an excerpt from an original CIAT blog

Read the full blog on CIAT's website

 


Bioversity International and the CIAT Agrobiodiversity Research Area supported this project with funding and research expertise for field image collection and processing within the framework of the CGIAR Research Program on Roots, Tubers and Bananas (RTB) and is supported by contributors to the CGIAR Trust Fund

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