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Space applications offer a sign of hope for finding solution to food security challenge, threatened by the lethal disease wheat rust

NEWS: Project with SAWIE, funded by SPRINT, in collaboration with the University of Leicester

Developing a new solution that will better identify the early spread of rust disease in wheat fields

SAWIE, an agritech company based in Leicestershire, has completed a major project to develop an innovation solution for early detection of the lethal disease, wheat rust. The disease detection model was developed through engaging farming communities to share their crop imagery in combination with space data. It will help farmers, regional governments and crop protection agencies to take control of, measure and constrain the spread of fungal spores to a wider area.

The disease comes in three types as leaf, stem and strip rust. It affects wheat production worldwide with losses estimated to be 15 million tons valued at US$2.9 billion (1). Wheat rust diseases are among the airborne rust diseases and respect no boundaries. They can spread over borders and cause significant yield losses over large areas.

The project is supported by the national SPRINT (Space Research and Innovation Network for Technology) business development programme. SPRINT funding has enabled SAWIE to collaborate with the University of Leicester academics using machine learning (ML) and artificial intelligence (AI) to develop a new solution that will better identify the early spread of rust disease in wheat fields

SAWIE’s farm advisory digital platform provides advice to smallholder farmers in developing countries throughout the plant lifecycle, from seed-to-seed stage by sharing hyperlocal advisory alerts using standard mobile phone SMS messaging, a smart phone app and social media platform for farmers.

SAWIE has worked with data scientists from the University Leicester to apply MLand AI techniques to the development project. The project involved taking high resolution pictures through Earth observation satellites and ground-based imaging of farmlands.

This project is also supported by a team from Bloc Digital, specialists in digital solutions, who are developing visualisation tools.

This project with the University of Leicester was funded from the £7.5 million SPRINT programme. SPRINT provides unprecedented access to university space expertise and facilities, and helps businesses through the commercial exploitation of space data and technologies.

Fritz Boehmler, Strategy Director at SAWIE said: “We are excited to be working with world-class researchers from University of Leicester, to develop a tool to better identify the early spread of rust disease in wheat crops. This will enable farmers to apply corrective management measures to prevent a significant loss in crop yield.

“As we make the transition to more sustainable food systems, along with adopting more sustainable land and water management practices, protecting the environment and mitigating the impacts of climate change continue to be major challenges. Innovations like our new tool will help to find the right balance between food and nutritional security.”

Ashiq Anjum, Professor of Distributed Systems at the University of Leicester added: “Applying state of the art machine learning algorithms on vast amounts of satellite data and identifying new features for crop health is quite exciting because this will lead to many interesting applications and systems.”

(1) Huerta-Espino J, Singh R, Crespo-Herrera LA, Villaseñor-Mir HE, Rodriguez-Garcia MF, Dreisigacker S, Barcenas-Santana D and Lagudah E (2020) Adult Plant Slow Rusting Genes Confer High Levels of Resistance to Rusts in Bread Wheat Cultivars From Mexico. Front. Plant Sci. 11:824. doi: 10.3389/fpls.2020.00824

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