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Leveraging Artificial Intelligence for Sustainable Irrigated Rice Production: A case of Smart Alternate Wetting and Drying in Nigeria

Author

Listed:
  • Ume, Chukwuma
  • Ume, Sunny

Abstract

This study, conducted in Southeast Nigeria, investigates the impact of Smart Alternate Wetting and Drying (SAID) on sustainable rice farming, using a randomised controlled trial and focusing on water use efficiency and greenhouse gas emissions. The research involved a pilot project with 15 rice farms, categorized into three groups employing SAID, manual Alternate Wetting and Drying (AWD), and continuous irrigation methods. The results revealed that SAID led to a 30% reduction in water usage compared to continuous irrigation and significantly lowered methane emissions. These findings corroborate global research advocating for sustainable agricultural practices. The integration of digital technology in SAID resolved the limitations associated with manual AWD, potentially making agriculture more appealing to younger generations. This study not only confirms SAID's effectiveness in enhancing water conservation and reducing environmental impact but also suggests its applicability as a scalable solution for rice cultivation. The research supports the advancement of climate-smart agricultural technologies, which are crucial for addressing global challenges of water scarcity and environmental sustainability in farming.

Suggested Citation

  • Ume, Chukwuma & Ume, Sunny, 2024. "Leveraging Artificial Intelligence for Sustainable Irrigated Rice Production: A case of Smart Alternate Wetting and Drying in Nigeria," IAAE 2024 Conference, August 2-7, 2024, New Delhi, India 344260, International Association of Agricultural Economists (IAAE).
    • Handle: RePEc:ags:cfcp15:344260
    DOI: 10.22004/ag.econ.344260
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