Rupavatharam, S and Komneic, A and Jat, M L (2025) Artificial Intelligence for Monitoring Pest and Disease in Groundnuts. In: Advances in Arachis through Genomics and Biotechnology (AAGB-2025), 23-25 March 2025, Novotel, Goa, India.
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Groundnut (Arachis hypogaea L.), also known as peanut, is a vital legume crop grown globally for its high oil (40-50%) and protein (25-30%) content. Groundnut crop improve soil fertility through nitrogen fixation, making them ideal for crop rotation in rainfed and semi-arid regions. However, pests and diseases significantly impact groundnut production, causing 25-50% yield losses globally. Novel digital tools that use Artificial intelligence (AI) and machine learning for disease diagnosis in groundnut are available to farmers. Digital apps like ‘Plantix’ provide valuable diagnoses of pests and diseases by processing images of plant damage symptoms sourced from a smartphone. These images provide time and geolocation data, delivering insights into the spatial and temporal spread of pests and diseases. This study presents results from the years 2023 to 2024 on a range of groundnut pests, diseases, and nutrient deficiencies. Over 96 % of notifications were sourced from India out of 548,854 received globally through Plantix app in groundnut. Indian states of Gujarat, Rajasthan, Andhra Pradesh, Maharashtra and Uttar Pradesh accounted to 66 % of these notifications. Results show that there was significantly higher reported incidence of foot and collar rot (53,461), tobacco caterpillar (41,576) bud necrosis (39,006), Helicoverpa (31,165) and leaf miners (28,653) when compared to other pests and diseases from the farmer fields. Real-time push notifications based on the user location were useful to alert the farmers on the prevalence of pest and disease. AI-based applications are useful in monitoring groundnut pests and diseases, leading to improved extension services.
| Item Type: | Conference or Workshop Item (Speech) |
|---|---|
| Divisions: | Global Research Program - Resilient Farm and Food Systems |
| CRP: | UNSPECIFIED |
| Uncontrolled Keywords: | Diagnosis, Farmer fields, Real-time, Advisories, Pest and Disease management, Alerts |
| Subjects: | Mandate crops > Groundnut Others > Plant Disease Others > Digital Agriculture |
| Depositing User: | Mr Nagaraju T |
| Date Deposited: | 03 Jul 2025 05:30 |
| Last Modified: | 03 Jul 2025 05:30 |
| URI: | http://oar.icrisat.org/id/eprint/13197 |
| Acknowledgement: | UNSPECIFIED |
| Links: | |
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