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

Simple Summary Within anthropogenic sources, agriculture contributes the most to greenhouse gas (GHG) emissions. The on-field assessment of methane emissions from livestock is crucial for testing and implementing mitigation strategies to reduce the deleterious effects of GHG on climate. Therefore, this article presents a longitudinal study in which measurements of enteric methane emissions from dairy cows (Jersey and Holstein-Freisian raised under a semi-extensive management system) were performed with a tool previously described as reliable, portable, and cost-effective: the laser methane detector (LMD). The results showed breed-related differences in methane emissions when milk yield was not considered, challenging us to rethink milk traits and breeding choices. Moreover, methane emissions were lower in cows in early lactation as well as in primiparous, likely reflecting concentrate supplementation and energy metabolism. The study pointed out the opportunity to design and test regional tailored mitigation strategies, including nutritional management, for higher methane emission periods within cows' lactation cycle, while ensuring the enhancement of productivity. 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.