Digital platform for quality seed production data of pulses

Read full text
Authors: DEVRAJ, P. K. Katiyar, Amrit Lamichaney, Uma Sah, GIRISH PRASAD DIXIT
Cited by: 0
References: 20

Abstract

Quality seed is a key determinant of productivity and sustainability in pulse cultivation. Farmers frequently encounter challenges in accessing timely and accurate information on improved varieties, seed availability, and centre-wise or crop-wise production, which affects planning and adoption of quality seeds. This study aimed to develop a digital platform that enables systematic retrieval and dissemination of quality seed production data for pulses to support better decision-making across the seed value chain. The platform was conceptualised to consolidate seed production data from different seed hub centres and present it through an intuitive and searchable interface. Its structure includes three main functional modules: database design, data management, and report generation. Seed production data covering foundation, certified, and truthfully labelled classes were compiled and organised to facilitate efficient access. Users can retrieve information using flexible filters such as crop, variety, centre, and production quantity. A dashboard provides real-time summaries of total seed production, participating centres, and seed availability, allowing stakeholders including farmers, researchers, and policymakers—to quickly assess the current status of seed resources. The platform contributes to improved transparency, enhanced accessibility, and more efficient management of quality seed production data for pulses. By centralising information that was previously dispersed, it serves as a valuable decision-support tool for planning and monitoring seed-related activities. A key limitation is that the system relies on timely data updates from participating seed hub centres, which may influence the accuracy of data-driven insights. Future enhancements may include automatic data integration and mobile-based access to increase usability and scalability.

Fields of Study & Subjects

Smart Agriculture and AI Agricultural Productivity and Crop Improvement Engineering and Information Technology

Publication details

Journal / source
The Indian Journal of Agricultural Sciences
Volume
96
Issue
01
Pages
84–89
Publication date
20 January 2026
Language
EN