The Archive

Every paper we've published

12 papers, 6 disciplines — indexed for readers, search engines, and AI answer engines alike.

Suresh Gawande· Researcher · ICAR-Directorate of Onion and Garlic Research (DOGR), Pune, Maharashtra

YOLO-ODD: An Improved YOLOv8s Model for Onion Foliar Disease Detection

A field-image dataset of 1,000 onion plants trained an upgraded YOLOv8 detector that spots Anthracnose, Stemphylium blight, Purple Blotch, and Twister disease at 77.3% accuracy and 123 frames per second — fast and light enough to run inside a farmer-facing smartphone app.

Agri Data SciencePlant PathologyIndiaMachine LearningComputer Vision
Abhilash Singh Maurya· Subject Matter Specialist, Agricultural Extension · Krishi Vigyan Kendra, Raebareli-II, Uttar Pradesh

Assessing the Role of Digital Platforms in Strengthening Agricultural Extension Services: Advisory to Empowerment

A survey of 400 Uttar Pradesh farmer households finds that regular users of digital advisory platforms — WhatsApp groups, YouTube, apps — score significantly higher on knowledge, empowerment, and yield than non-users, even after controlling for income and education.

Agri Data ScienceAgricultural ExtensionIndiaFarmer Empowerment
Victoria C. F. Westbrooke· Researcher, Department of Land Management and Systems · Lincoln University, Christchurch, New Zealand

Bridging Gaps: A Study of Trust and Information Flow in New Zealand Agriculture

A qualitative study of 37 New Zealand dairy and sheep/beef farmers finds they increasingly trust informal, digital, and peer-driven information — including AI — over formal institutions, and are struggling with real information overload as a result.

Agri Data ScienceAgricultural ExtensionNew ZealandFarmer Decision-Making
Vedant Balasubramaniam· Researcher · Indian Institute of Science, Bengaluru

Agri-SAGE: Simulation-Grounded Multi-Agent LLM for Context-Aware Agricultural Advisory Generation

A multi-agent AI system that generates season-long farming advice and checks it against a crop growth simulator before recommending it — in a decade-long test on maize in Karnataka, all three reasoning strategies beat static advisory guidelines, with the best approach lifting yields by over 1,150 kg/ha.

Agri Data ScienceMachine LearningAgronomyIndiaCrop Simulation