Work

Predicting Distribution of Fallarmy Worm Pest Using Climate Changes With Machine Learning on Indian Crops

Year: 2025

Type: article

Abstract: This project aims to develop an AI-powered web application to assist farmers in making informed crop cultivationdecisions. By analyzing factors like crop type, cultivation time, and location, the application predicts crop success,assesses pest infestation risks (especially fall armyworms), and suggests alternative crops and optimal plantingtimes. With a user-friendly interface, it provides data-driven insights to enhance productivity and sustainability,empowering farmers while supporting India's agricultural sector and food security.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15088388

Authors: Dr. V. Venkat Krishna, T. Vinutna, B. Adithya, K. Manikanta, S. Nagaraju

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDGs: Zero hunger, Industry, innovation and infrastructure, Life on land

Open Access status: green

OpenAlex ID: W6949195100

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