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The agriculture sector is essential for driving economic growth and ensuring food and nutritional security. As the global population continues to rise, the demand for sustainable practices becomes ever more critical. Embracing technological innovations is pivotal to developing forward-thinking solutions that will shape the future of agriculture. Artificial intelligence (AI) and other advanced technologies offer significant potential to transform agriculture research and development sector. ICAR-Indian Agricultural Statistics Research Institute (IASRI) is a premier institution of ICAR conducting cutting-edge research in the area of AI. We shall present case studies of AI applications taken up at ICAR-IASRI, demonstrating high precision in crop improvement through techniques such as SpikeSegNet, SlypNet, and PanicleDet for plant phenotyping and AI-DISC and AI-DISA for disease diagnosis. SpikeSegNet, SlypNet deep learning-based networks, identifies wheat panicles with more than 95% accuracy, while PanicleDet, based on YOLOv5, accurately detects rice panicle development stages. AI-DISC and AI-DISA, mobile applications, diagnose crop and livestock diseases using AI, achieving testing accuracy between 92% and 96%. Dairy SHRIA is an advanced educational platform that provides real-time, multilingual support on dairy farming, enhancing livestock health and profitability through expert guidance in breeding, feeding, and healthcare. These case studies highlight AI’s transformative impact on agriculture, enhancing productivity, minimizing environmental impact, and promoting sustainable agricultural practices. By integrating AI, farmers can make data-driven decisions, optimize resources, and significantly contribute to global food and nutrition security, paving the way for a sustainable and resilient agricultural ecosystem.

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Advancing Toward Sustainable Agriculture Through Artificial Intelligence: Case Studies in Indian Agriculture

  • 章节

  • 发表日期：

    2025年

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  • Alka Arora,
  • Chandan Kumar Deb,
  • Tanuj Misra,
  • Himanshushekhar Chaurasia,
  • Sudeep Marwaha,
  • Rajender Parsad

摘要

The agriculture sector is essential for driving economic growth and ensuring food and nutritional security. As the global population continues to rise, the demand for sustainable practices becomes ever more critical. Embracing technological innovations is pivotal to developing forward-thinking solutions that will shape the future of agriculture. Artificial intelligence (AI) and other advanced technologies offer significant potential to transform agriculture research and development sector. ICAR-Indian Agricultural Statistics Research Institute (IASRI) is a premier institution of ICAR conducting cutting-edge research in the area of AI. We shall present case studies of AI applications taken up at ICAR-IASRI, demonstrating high precision in crop improvement through techniques such as SpikeSegNet, SlypNet, and PanicleDet for plant phenotyping and AI-DISC and AI-DISA for disease diagnosis. SpikeSegNet, SlypNet deep learning-based networks, identifies wheat panicles with more than 95% accuracy, while PanicleDet, based on YOLOv5, accurately detects rice panicle development stages. AI-DISC and AI-DISA, mobile applications, diagnose crop and livestock diseases using AI, achieving testing accuracy between 92% and 96%. Dairy SHRIA is an advanced educational platform that provides real-time, multilingual support on dairy farming, enhancing livestock health and profitability through expert guidance in breeding, feeding, and healthcare. These case studies highlight AI’s transformative impact on agriculture, enhancing productivity, minimizing environmental impact, and promoting sustainable agricultural practices. By integrating AI, farmers can make data-driven decisions, optimize resources, and significantly contribute to global food and nutrition security, paving the way for a sustainable and resilient agricultural ecosystem.