The European cattle milk sector has rapidly intensified in recent decades. This trend has received widespread disapproval from the public, which highlights the many problems linked to intensification. To address these concerns, agricultural policies commonly impose an agroecological transition. In order to evaluate and monitor the degree of sustainability of dairy cattle farms over time, many sets of indicators have been proposed in recent years. However, these indicators have often referred only to specific aspects of sustainability or have been generically proposed for the entire agricultural sector, and therefore, they are not capable of capturing the peculiarities and the complexity of the dairy cattle sector. A systematic review of the scientific literature was carried out to obtain a complete picture of the indicators proposed for the European context. A total of 325 out of over 6700 papers were selected, and three pillars—environmental, economic, and social pillars—were explored. A total of 70 indicators were identified, which could help build a complete and less sectoral picture of sustainability than that proposed so far. A total of 22 indicators were associated with the environmental pillar, 18 indicators were associated with the economic pillar, and 17 indicators were associated with the social pillar, while 12 indicators were associated with two different pillars. With reference to the measurement methods, considerable variability was highlighted, which did not allow us to identify or propose unique methods for measuring each indicator.

The study investigated differences in ruminal and fecal microbiota composition, fermentation traits, and volatile organic compounds (VOC) in Simmental dairy cows classified as high (HME) or low (LME) methane emitters. Methane emissions from 48 cows were quantified using the Laser Methane Smart portable gas detector. The 12 animals with the highest and lowest emissions were selected and assigned to the HME and LME groups, respectively, balanced for body weight, days in milk, and body condition score. Rumen fluid and fecal samples were analyzed for pH, ammonia, volatile fatty acids (VFA), VOC, and microbiota composition. As expected, CH₄ emissions were significantly higher in HME than in LME cows (22.5 vs. 13.2 g/kg DMI; 16.9 vs. 8.4 g/kg FCM). The neutral detergent fiber digestibility was higher in HME cows (51.4% vs. 47.9%). The valeric acid concentration and the acetate-to-propionate ratio were significantly higher in HME cows (3.53 vs. 3.31). The VOC profiles significantly differed between groups in both feces and rumen fluid. The microbiota analysis revealed a significant difference between groups at the order and genus levels (Bray–Curtis dissimilarity). The Shannon index was higher in LME cows (2.08 vs. 1.95). HME cows exhibited a higher abundance of Methanosphaera and Methanobacteriales. Overall, the results indicate that re-shaping the rumen microbial community can play a key role in reducing methane emissions, strengthening the case for microbiome-driven approaches and offering insights that can support mitigation strategies across dairy production systems.

This study investigated how the lactation stage and the main behavioral activities of dairy cows influence enteric methane emissions. The research trial was conducted on 39 Italian Simmental dairy cows reared in a commercial dairy farm. Each animal was monitored during early, mid, and late lactation. Methane emissions were measured using LaserMethaneSmart (LMS® - Tokyo Gas Engineering Solutions Ltd.) device. Simultaneously, eating, rumination, and resting times were continuously recorded using activity monitoring collars. Furthermore, milk yield and composition and feed samples were collected throughout the experiment. Methane emissions were significantly affected by both behavioral activity and its interaction with the lactation stage. The highest methane intensity values were observed during rumination in late lactation, while resting consistently showed the lowest emissions. Emissions estimated by considering only eating activity tended to overestimate total daily methane output compared with estimates weighted across all behaviors. These findings underscore that behavioral patterns, particularly rumination and resting, contribute substantially to daily methane emissions and should be included in emission models to improve the accuracy of environmental assessments and mitigation strategies in dairy production systems.