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Updated: Jun 3, 2026

The Use of an Automated System (GreenFeed) to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals
Published on: September 7, 2015
Breed-specific enteric methane emission factor assessment in Italian dairy cattle leveraging DHI and primary ration
Giulia Ferronato1, Mesfin Mekonnen Moliso2, Raphael Mrode3
1Department of Civil, Environmental, Architectural, Engineering and Mathematics (DICATAM), Università degli Studi di Brescia, 25121, Brescia, Italy.
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Enteric methane (CH4) emissions from dairy cattle are a major contributor to greenhouse gas footprint in the livestock sector. This study applied Intergovernmental Panel on Climate Change (IPCC) Tier 2 equations to estimate enteric methane emissions in Italian Holstein, Brown Swiss, and Red Pied herds using either default dietary assumptions or farm-specific diet information. By combining individual Dairy Herd Improvement (DHI) test-day records with primary ration data, the analysis examined how improved input data resolution affected methane estimates across breeds and animal categories under commercial farming conditions. Data were collected from 138 Italian dairy farms participating in the national Dairy Herd Improvement (DHI) program between January 2021 and December 2022, with farm rations recorded concurrently during DHI test days by trained technicians using a standardized questionnaire. Breed, emission estimation approach, and their interaction were analyzed using aligned rank transform (ART) procedures with permutation-based P-values. Holstein cows exhibited greater daily methane production (MeP = 443.60 ± 5.68 g/d; P < 0.001), whereas Red Pied herds showed the greatest methane intensity (MeI = 29.99 ± 0.70 g/kg fat- and protein-corrected milk; P < 0.001). Breed and CH4 estimation approaches affected emission estimates, however, their interaction was not significant, indicating consistent breed rankings across methods. Post hoc analyses revealed no significant differences in methane indices among breeds. Incorporation of farm-specific ration data impacted emission estimates, particularly for nonproductive groups such as dry cows and heifers, highlighting the importance of context-specific dietary inputs for improving the accuracy and representativeness of CH4 inventories.

