Comparative study of the bacterial community of organic and conventional cow's milk.

Agricultural practises such as conventional and organic farming can potentially affect the microbial communities in milk. In the present study, the bacterial diversity of milk was investigated using high-throughput sequencing on ten organic and ten conventional farms in the Azores, a region where milk production is largely based on year-round grazing systems. The microbiota of milk from both production systems was dominated by Bacillota, Pseudomonadota, Actinomycetota and Bacteroidota. The organic milk showed greater heterogeneity between farms, as reflected in the dispersion of diversity indices and the large variation in the relative abundances of the dominant genera. In contrast, conventionally produced milk showed a high degree of similarity within each season. In the conventional production system, the season also had a strong influence on the bacterial community, but this effect was not observed in the organic milk. The LEfSe analysis identified the genus Iamia as significantly (p < 0.05) more abundant in organic milk, but depending on the season, several other genera were identified that distinguished organic milk from conventionally produced milk. Of these, Bacillus, Iamia and Nocardioides were associated with the soil microbiota in organic farming.

A Longitudinal Study with a Laser Methane Detector (LMD) Highlighting Lactation Cycle-Related Differences in Methane Emissions from Dairy Cows.

Reversing climate change requires broad, cohesive, and strategic plans for the mitigation of greenhouse gas emissions from animal farming. The implementation and evaluation of such plans demand accurate and accessible methods for monitoring on-field CH4 concentration in eructating breath. Therefore, this paper describes a longitudinal study over six months, aiming to test a protocol using a laser methane detector (LMD) to monitor CH4 emissions in semi-extensive dairy farm systems. Over 10 time points, CH4 measurements were performed in dry (late gestation) and lactating cows at an Azorean dairy farm. Methane traits including CH4 concentration related to eructation (E_CH4) and respiration (R_CH4), and eructation events, were automatically computed from CH4 measured values using algorithms created for peak detection and analysis. Daily CH4 emission was estimated from each profile's mean CH4 concentration (MEAN_CH4). Data were analyzed using a linear mixed model, including breed, lactation stage, and parity as fixed effects, and cow (subject) and time point as random effects. The results showed that Holsteins had higher E_CH4 than Jersey cows (p < 0.001). Although a breed-related trend was found in daily CH4 emission (p = 0.060), it was not significant when normalized to daily milk yield (p > 0.05). Methane emissions were lower in dry than in lactation cows (p < 0.05) and increased with the advancement of the lactation, even when normalizing it to daily milk yield (p < 0.05). Primiparous cows had lower daily CH4 emissions related to R_ CH4 compared to multiparous (p < 0.001). This allowed the identification of periods of higher CH4 emissions within the milk production cycle of dairy cows, and thus, the opportunity to tailor mitigation strategies accordingly.