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PODCAST · government

Rural On AIr

Rural on AIr AI-LAB is a digital communication tool that supports information and knowledge transfer of all outputs of the Italian CAP Network to the Italian agricultural sector and rural development.

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    Looking for equity: The Effects of Compensatory Allowances on Mountain Farming in Piedmont

    Rural On AIr AI-LAB is a digital communication tool that supports information and knowledge transfer of all outputs of Italian CAP Network to the Italian agricultural sector and rural development.In this podcast, Mario Cariello (CREA PB) reviewed the scientific article "Bridging the Gap: The Impact of Compensatory Measures on Mountain Farming in Piedmont" originally published on Bio-Based and Applied Economics, Special Issue 13th AIEAA Conference and, through the use of artificial intelligence, produced a podcast that describes its contents in an informative way.This  study examines  the  impact of  the  Rural Development  Program  (RDP) on reducing  income disparities  between farms  in  mountainous and  non-mountainous  areas in  Piedmont.  Using Farm Accounting  Data  Network data  from  2012–2022, the  analysis  focuses on  cattle,  sheep and goats, and fruit farms. The findings  indicate  that significant  income  disparities are  primarily  observed in  small  farms specialized in cattle and sheep and goats, with mountain farms facing a net shortfall. While compensatory allowance support helps reduce this gap a substantial  disparity  remains. Bridging the gap entirely would require doubling compensatory payments, though alternative strategies are discussed.DOI: https://doi.org/10.36253/bae-16852Authors of the scientific article:Moino, F. (CREA PB), Giacardi, A. (Università di Roma La Sapienza), Califano, G. (Università degli Studi di Napoli Federico II), & Cagliero, R. (CREA PB)

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    AKISinCNA – From 2024 CNA to 2025 Agenda: What’s Changing Across Europe’s AKIS

    ModernAKIS – Modernisation of Agriculture through more efficient and effective Agricultural Knowledge and Innovation Systems is a Horizon Europe project that aims to strengthen the systemic capacities of AKIS (Agricultural Knowledge and Innovation Systems) actors at the individual, organizational, and system levels. The goal is to contribute to the transformation of AKIS by making them more coherent, effective, and efficient, in order to support the transition towards sustainable management of natural resources in agriculture and forestry.This podcast was created with the help of artificial intelligence.The concept, script, and content were developed by Simona Cristiano and Mario Cariello, with AI tools used to support the production process.

  3. 2

    AKISinCNA – Inside the Needs of Key Change Agents of AKIS in the EU

    ModernAKIS – Modernisation of Agriculture through more efficient and effective Agricultural Knowledge and Innovation Systems is a Horizon Europe project that aims to strengthen the systemic capacities of AKIS (Agricultural Knowledge and Innovation Systems) actors at the individual, organizational, and system levels. The goal is to contribute to the transformation of AKIS by making them more coherent, effective, and efficient, in order to support the transition towards sustainable management of natural resources in agriculture and forestry.This podcast was created with the help of artificial intelligence.The concept, script, and content were developed by Simona Cristiano and Mario Cariello, with AI tools used to support the production process.

  4. 1

    Lessons learned from existing carbon removal methodologies for agricultural soils to drive European Union policies

    Rural On AIr AI-LAB is a digital communication tool that supports information and knowledge transfer of all outputs of the National Rural Network to the Italian agricultural sector and rural development.In this podcast, Mario Cariello (CREA PB) reviewed the scientific article "Lessons learned from existing carbon removal methodologies for agricultural soils to drive European Union policies" originally published on Volume 75, Issue 5 of the European Journal of Soil Science by CREA and Teagasc researchers and, through the use of artificial intelligence, produced a podcast that describes its contents in an informative way.The article focuses on carbon sequestration in agricultural soils and presents a detailed and critical analysis of carbon credits methodologies and regulations. In particular, the European Commission’s proposal for a regulation on carbon removals is compared with certification schemes developed in some extra-EU countries (such as Australia, Alberta in Canada and USA) to provide recommendations to policy makers to strengthen the European legislation under development.DOI: https://doi.org/10.1111/ejss.13577Authors of the scientific article:Irene Criscuoli, Andrea Martelli, Ilaria Falconi, Francesco Galioto, Maria Valentina Lasorella, Stefania Maurino, Avion Phillips, Guido Bonati, Giovanni Dara Guccione.

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ABOUT THIS SHOW

Rural on AIr AI-LAB is a digital communication tool that supports information and knowledge transfer of all outputs of the Italian CAP Network to the Italian agricultural sector and rural development.

HOSTED BY

retepacAI

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Frequently Asked Questions

How many episodes does Rural On AIr have?

Rural On AIr currently has 4 episodes available on PodParley. New episodes are automatically indexed when they're published to the podcast feed.

What is Rural On AIr about?

Rural on AIr AI-LAB is a digital communication tool that supports information and knowledge transfer of all outputs of the Italian CAP Network to the Italian agricultural sector and rural development.

How often does Rural On AIr release new episodes?

Rural On AIr has 4 episodes. Check the episode list to see recent publication dates and frequency.

Where can I listen to Rural On AIr?

You can listen to Rural On AIr on PodParley by clicking any episode. We provide an embedded audio player for direct listening, and you can also subscribe via your preferred podcast app using the RSS feed.

Who hosts Rural On AIr?

Rural On AIr is created and hosted by retepacAI.
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