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<p>Current food systems present several shortcomings that hinder their long-term sustainability leading to depletion of natural resources, land degradation and biodiversity loss. Circular Economy (CE) promises to mitigate these problems, by regenerating the ecosystems, enhancing production efficiency, and alleviating ecological pressures. Farms implement circularity in agriculture through renewable resources use, food waste prevention, biomasses valorization and regenerative practices. In particular, food waste prevention alleviates ecological pressures from production by enhancing output efficiency per unit of input. Farm level data are essential for understanding the mechanisms guiding CE diffusion, yet data availability is limited. This study tries to fill the knowledge gap by providing a new representative dataset on Italian farms. Data were collected through a structured survey administered to 1,200 farms. The dataset comprises 443 variables covering farm characteristics, surplus and waste generation and valorization, regenerative practices, use of circular inputs, and food waste performance providing the first granular overview of CE and food waste management practices in agriculture.</p>

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Survey data on Circular Economy practices in Italian farms with a focus on surplus food and food waste

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月28日

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  • Niso Randellini,
  • Giovanni Scotti,
  • Giulia Valentini,
  • Paola Garrone

摘要

Current food systems present several shortcomings that hinder their long-term sustainability leading to depletion of natural resources, land degradation and biodiversity loss. Circular Economy (CE) promises to mitigate these problems, by regenerating the ecosystems, enhancing production efficiency, and alleviating ecological pressures. Farms implement circularity in agriculture through renewable resources use, food waste prevention, biomasses valorization and regenerative practices. In particular, food waste prevention alleviates ecological pressures from production by enhancing output efficiency per unit of input. Farm level data are essential for understanding the mechanisms guiding CE diffusion, yet data availability is limited. This study tries to fill the knowledge gap by providing a new representative dataset on Italian farms. Data were collected through a structured survey administered to 1,200 farms. The dataset comprises 443 variables covering farm characteristics, surplus and waste generation and valorization, regenerative practices, use of circular inputs, and food waste performance providing the first granular overview of CE and food waste management practices in agriculture.