<p>This special issue titled “Advances in precision irrigation management in the twenty-first century” explored novel research in precision irrigation management, with a focus on enhancing water use efficiency and environmental sustainability. Thirteen papers were accepted following a peer review process. Invited contributions developed new approaches for scheduling precision irrigation, leveraging artificial intelligence for water stress management and irrigation application support, optimizing irrigation efficiency through machine learning tools, and developing evidence-based tools for monitoring water stress, water use, and soil water status. Research on the environmental benefits of precision irrigation, contributing to the advancement of sustainable agricultural practices was part of this special issue. This special issue provided a platform for sharing the latest findings, methodologies, and insights on precision irrigation management. Notably, the research in this special issue extended the methodological and technological foundations of the field by addressing several critical challenges, such as irrigation in water-scarce conditions, scalability of monitoring tools, and the environmental implications of irrigation practices. The knowledge and tools presented in this special issue contributed to more robust, evidence-based, resilient, efficient, and environmentally sound irrigation systems, with close relevance to research, practice, and policy in sustainable agriculture.</p>

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Advances in precision irrigation management in the twenty-first century

  • Davie M. Kadyampakeni,
  • Elia Scudiero,
  • Rajan Shrestha

摘要

This special issue titled “Advances in precision irrigation management in the twenty-first century” explored novel research in precision irrigation management, with a focus on enhancing water use efficiency and environmental sustainability. Thirteen papers were accepted following a peer review process. Invited contributions developed new approaches for scheduling precision irrigation, leveraging artificial intelligence for water stress management and irrigation application support, optimizing irrigation efficiency through machine learning tools, and developing evidence-based tools for monitoring water stress, water use, and soil water status. Research on the environmental benefits of precision irrigation, contributing to the advancement of sustainable agricultural practices was part of this special issue. This special issue provided a platform for sharing the latest findings, methodologies, and insights on precision irrigation management. Notably, the research in this special issue extended the methodological and technological foundations of the field by addressing several critical challenges, such as irrigation in water-scarce conditions, scalability of monitoring tools, and the environmental implications of irrigation practices. The knowledge and tools presented in this special issue contributed to more robust, evidence-based, resilient, efficient, and environmentally sound irrigation systems, with close relevance to research, practice, and policy in sustainable agriculture.