Artificial Intelligence for Monitoring Pest and Disease in Groundnuts

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.

Publication Details

Journal
Open Access Repository of ICRISAT (International Crops Research Institute for the Semi-Arid Tropics)
Published
2025-03-01
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial Intelligence for Monitoring Pest and Disease in Groundnuts

Open Access Repository of ICRISAT (International Crops Research Institute for the Semi-Arid Tropics)
Smart Agriculture and AI
article

Artificial Intelligence for Monitoring Pest and Disease in Groundnuts

article en

Abstract

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.

Open Access Repository of ICRISAT (International Crops Research Institute for the Semi-Arid Tropics)
Zero hunger
Openalex Percentile: Top 35%
Smart Agriculture and AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.