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Chatbot for Promoting Best Crop Management Practices to Rice Farmers in Odisha, India

Author

Listed:
  • Bharti, Preeti
  • Cabrera, Ellanie
  • Miro, Berta
  • Sharma, Sheetal
  • Florey, Carolyn
  • Sahoo, Manas Ranjan
  • Rout, Kshitikanta

Abstract

The increasing penetration of mobile phones has made it easier to reach remote farmers and bridge the knowledge gap between them and researchers/extension workers and agricultural stakeholders. Farmers need concise, context-specific, information to address the challenges which arise due to lack of near-real time updates. Scaling up innovative agricultural technologies is essential to ensure these advancements reach the farmers for their benefit. Chatbots represent an informative tool for delivering the latest agricultural developments to farmers in a user-friendly and interactive format. Chatbots can deliver information on best agronomic practices, weather forecast, market information thereby improving the decision-making capacity of farmers. This paper discusses the development of a rule-based chatbot under a pilot-study and presents findings from a user study conducted with 102 farmers in Odisha, India in 2021. The content topics were decided using a participatory approach wherein farmers selected the topic of interests and information required. The content was developed using the digital tools Rice Crop Manager (RCM), Seed Cast and Rice Knowledge Bank (RKB), developed and deployed by International Rice Research Institute (IRRI). The chatbot is hosted on Facebook messenger platform and needs the internet support to operate. Farmers having this app can use the chatbot without any additional expense. The results indicate that farmers acknowledged and appreciated interactive features of chatbot and the content but expressed a desire for more comprehensive information on insect-pest management and other crop management practices. The findings highlight the potential of chatbot as a complementary channel to disseminate agro advisories, complementing the existing agricultural extension services. The study has its limitations in terms of small sample size which may or may not represent the variability of the entire population of the area.

Suggested Citation

  • Bharti, Preeti & Cabrera, Ellanie & Miro, Berta & Sharma, Sheetal & Florey, Carolyn & Sahoo, Manas Ranjan & Rout, Kshitikanta, 2024. "Chatbot for Promoting Best Crop Management Practices to Rice Farmers in Odisha, India," Asian Journal of Agricultural Extension, Economics & Sociology, Asian Journal of Agricultural Extension, Economics & Sociology, vol. 42(10), pages 1-7.
    • Handle: RePEc:ags:ajaees:368103
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