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Sustainability & efficiency

Towards Sustainable Dairy: Establishing an Italian Consortium for Methane Mitigation Through Breeding

Authors
  • Lorenzo Benzoni (African Network of Agricultural Policy Research Institutes (ANAFIBJ))
  • Greta Bonacina (Tecnosens)
  • Alessandro Bracchi (Tecnosens)
  • Martino Cassandro (African Network of Agricultural Policy Research Institutes (ANAFIBJ))
  • Martina Dorigo (Nutristar spa)
  • Raffaella Finocchiaro (Associazione Nazionale Allevatori della Razza Frisona, Bruna e Jersey)
  • Francesca Fumagalli (African Network of Agricultural Policy Research Institutes (ANAFIBJ))
  • Giulia Gislon (University of Milan)
  • Silvia Graziani (University of Florence)
  • Giampiero Grossi (University of Tuscia)
  • Nicola Lacetera (University of Tuscia)
  • Jonathan Layton (African Network of Agricultural Policy Research Institutes (ANAFIBJ))
  • Vincenzo Lopreiato (University of Messina)
  • Chiara Rossi (University of Tuscia)
  • Francesco Tiezzi (University of Florence)
  • Marco Tolone (University of Messina)
  • Giulio Visentin (University of Bologna)
  • Andrea Vitali (University of Tuscia)
  • Maddalena Zucali (University of Milan)

Abstract

Rising greenhouse gas (GHG) emissions, particularly methane (CH₄) from livestock, pose a significant challenge for climate change mitigation worldwide. In recent years, the dairy sector has been recognized as a major contributor to agricultural emissions, prompting growing international attention on strategies to monitor, quantify, and reduce methane output from cattle. In response to this global concern, an Italian consortium on environmental impact has been established, led by ANAFIBJ, bringing together researchers, breeding associations, and dairy farmers to develop coordinated approaches for reducing the environmental footprint of dairy herds. For this reason, a three-year project has been launched to consolidate existing methane phenotypes and collect new data from a broad range of Holstein cows in commercial farms across Italy. The project aims to establish a robust reference population for breeding value estimation (EBV), enabling selective breeding for lower CH₄ emissions while maintaining herd productivity and resilience. To achieve this, 14 Moologger sniffer units are deployed across commercial farms, targeting the phenotyping of approximately 7,500 cows over three years. All phenotyped animals will be genotyped if not already done. Selected farms will be monitored continuously to assess trait repeatability and individual emission behavior. The collected data will feed into statistical models to estimate EBVs for methane emissions, while Life Cycle Assessment (LCA) analyses will evaluate the potential impact of selection on dairy production and the environment. ANAFIBJ's environmental impact estimator, integrated into the HerdUp management tool, will be refined and expanded using farmer surveys and LCA data, providing practical decision support for breeders. Since 2015, ANAFIBJ has implemented a holistic approach to environmental sustainability, establishing pipelines to integrate new traits into routine databases and creating a consortium of stakeholders for systematic recording of environmental traits. Key phenotypes-including methane emissions, milk spectral profiles, ruminal content, and microbiota composition-are integrated into a central data system and summarized in a 'Green Passport' for each animal. This project leverages these foundations to provide a comprehensive framework for Italian farmers to reduce CH₄ emissions, promote sustainable herd management, and contribute to broader efforts in mitigating climate change.

Keywords: 2026

How to Cite:

Benzoni, L., Bonacina, G., Bracchi, A., Cassandro, M., Dorigo, M., Finocchiaro, R., Fumagalli, F., Gislon, G., Graziani, S., Grossi, G., Lacetera, N., Layton, J., Lopreiato, V., Rossi, C., Tiezzi, F., Tolone, M., Visentin, G., Vitali, A. & Zucali, M., (2026) “Towards Sustainable Dairy: Establishing an Italian Consortium for Methane Mitigation Through Breeding”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2286338. doi: https://doi.org/10.31274/wcgalp.23937

Rights: 1

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Published on
2026-02-26

Peer Reviewed