BOLLWM: A real-world dataset for bollworm pest monitoring from cotton fields in India
Jerome White, Chandan Agrawal, Anmol Ojha, Apoorv Agnihotri, Makkunda, Sharma, Jigar Doshi

TL;DR
This paper introduces BOLLWM, a comprehensive real-world dataset of pest images from Indian cotton fields, supporting AI-driven pest management tools and enabling diverse research opportunities.
Contribution
It provides a unique, real-world pest dataset collected over five years, combining organized and mobile app data, advancing pest detection research and applications.
Findings
Dataset includes thousands of pest images from Indian cotton fields.
Supports development of AI-based pest management mobile applications.
Enables diverse research beyond pest detection.
Abstract
This paper presents a dataset of agricultural pest images captured over five years by thousands of small holder farmers and farming extension workers across India. The dataset has been used to support a mobile application that relies on artificial intelligence to assist farmers with pest management decisions. Creation came from a mix of organized data collection, and from mobile application usage that was less controlled. This makes the dataset unique within the pest detection community, exhibiting a number of characteristics that place it closer to other non-agricultural objected detection datasets. This not only makes the dataset applicable to future pest management applications, it opens the door for a wide variety of other research agendas.
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Taxonomy
TopicsPlant Virus Research Studies · Smart Agriculture and AI · Insect Resistance and Genetics
