Scientists to launch mobile app to detect potato blight at early stages
Spearheaded by a research team at Aberystwyth University, the DeepDetect project aims to develop a mobile phone app that uses artificial intelligence to provide early warnings of diseases in potatoes.
Potato crops are highly susceptible to diseases caused by pathogens such as fungi, bacteria, viruses, and nematodes.
Late blight, caused by Phytophthora infestans, can wipe out entire fields, and lead to enormous costs and food shortages. It is responsible for 20% of potato crop losses and €4bn in economic losses worldwide.
Traditionally, disease detection in crops has relied on manual inspection, a method that is time-consuming, expensive, and often subjective.
DeepDetect aims to change that by harnessing the power of machine learning to deliver accurate diagnoses directly to farmers' smartphones.
Dr Edore Akpokodje, a lecturer in computer science at Aberystwyth University, said: 'Our goal is to empower farmers with a tool which is not only scientifically robust but also practical and easy to use, and which delivers instantaneous, location-specific disease forecasts straight to their phones.
"By integrating farmer feedback from the outset, we will ensure that this technology is grounded in real-world needs and challenges.'
The project also aims to reduce the environmental and financial burden of widespread preventive spraying.
Dr Akpokodje added: 'Addressing the challenge of early diagnosis of potato plant disease would boost productivity and reduce costs for farmers, while supporting more sustainable and targeted disease management.
"By decreasing reliance on pesticides, this approach benefits both the environment and the long-term resilience of the potato industry. The technology also has the potential for wider application across other crops, driving innovation in agricultural practices.'
Dr Aiswarya Girija from the Institute of Biological, Environmental and Rural Sciences at Aberystwyth University said:
Potatoes are the fourth most important staple crop globally, and optimal production is essential for a growing global population. Potato blight is therefore not just a farming issue — it's a food security issue.
'As well as threatening the stability of food supplies, potato blight drives up production costs and reliance on environmentally harmful fungicides. The system we plan to develop will be capable of detecting early signs of disease before they become visible to the human eye, allowing for timely and targeted interventions.'
The first stage of the DeepDetect project is a comprehensive feasibility study, including market research to understand the limitations of current early warning systems.
The project team will then create an AI-powered prototype using image datasets of healthy and diseased potato leaves.
Once the prototype has been developed, the team will conduct focus groups and workshops with farmers and agronomists to refine the model and ensure usability.
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Irish Examiner
16-07-2025
- Irish Examiner
Scientists to launch mobile app to detect potato blight at early stages
Potato blight, one of the world's most devastating crop diseases, could soon be detected using mobile phones, thanks to a new app being developed by Welsh scientists. Spearheaded by a research team at Aberystwyth University, the DeepDetect project aims to develop a mobile phone app that uses artificial intelligence to provide early warnings of diseases in potatoes. Potato crops are highly susceptible to diseases caused by pathogens such as fungi, bacteria, viruses, and nematodes. Late blight, caused by Phytophthora infestans, can wipe out entire fields, and lead to enormous costs and food shortages. It is responsible for 20% of potato crop losses and €4bn in economic losses worldwide. Traditionally, disease detection in crops has relied on manual inspection, a method that is time-consuming, expensive, and often subjective. DeepDetect aims to change that by harnessing the power of machine learning to deliver accurate diagnoses directly to farmers' smartphones. Dr Edore Akpokodje, a lecturer in computer science at Aberystwyth University, said: 'Our goal is to empower farmers with a tool which is not only scientifically robust but also practical and easy to use, and which delivers instantaneous, location-specific disease forecasts straight to their phones. "By integrating farmer feedback from the outset, we will ensure that this technology is grounded in real-world needs and challenges.' The project also aims to reduce the environmental and financial burden of widespread preventive spraying. Dr Akpokodje added: 'Addressing the challenge of early diagnosis of potato plant disease would boost productivity and reduce costs for farmers, while supporting more sustainable and targeted disease management. "By decreasing reliance on pesticides, this approach benefits both the environment and the long-term resilience of the potato industry. The technology also has the potential for wider application across other crops, driving innovation in agricultural practices.' Dr Aiswarya Girija from the Institute of Biological, Environmental and Rural Sciences at Aberystwyth University said: Potatoes are the fourth most important staple crop globally, and optimal production is essential for a growing global population. Potato blight is therefore not just a farming issue — it's a food security issue. 'As well as threatening the stability of food supplies, potato blight drives up production costs and reliance on environmentally harmful fungicides. The system we plan to develop will be capable of detecting early signs of disease before they become visible to the human eye, allowing for timely and targeted interventions.' The first stage of the DeepDetect project is a comprehensive feasibility study, including market research to understand the limitations of current early warning systems. The project team will then create an AI-powered prototype using image datasets of healthy and diseased potato leaves. Once the prototype has been developed, the team will conduct focus groups and workshops with farmers and agronomists to refine the model and ensure usability. Read More The red tape that stalled farm loans — and the road back for Microfinance Ireland
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The Irish Sun
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Mysterious ‘alien-like' sea creature that can devour prey 3 TIMES its size is found on UK beach
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