Search Results (7)

Agricultural activities are a significant contributor to global greenhouse gas emissions, accounting for 14.5% of total anthropogenic emissions. Specifically, greenhouse gas emissions from beef cattle and dairy cattle constitute 35% and 30% of total global livestock emissions, respectively. This study focuses on dairy cattle, exploring the complex relationships between rumen microbiota and methane emission. The methane emissions of 968 lactating Holstein cows were measured using a laser methane detector (LMD, Shanghai Hesai Technology Co., Ltd., Shanghai, China). Among the measured cows, 107 individuals were further selected into high (HME) and low methane-emitting (LME) groups, including 50 cows in the HME group and 57 in the LME group. This study analyzed differences in rumen microbiota and microbial functions between cows with varying levels of methane emissions. The results showed significant differences in the Simpson and Pielou indices of rumen bacterial communities between the HME and LME groups. Beta diversity analysis revealed significant differences in microbial community structure between the two groups. It was found that the abundance of Bacteroidales and Prevotellaceae in the rumen of cows in the HME group cows was significantly higher than that of cows in the LME group (LDA > 3, p < 0.05). Additionally, bacterial functions related to biosynthesis and carbohydrate metabolism were more active in the HME group. This study revealed distinct differences in the rumen bacterial communities between HME and LME cow in Chinese Holstein cattle, and identified specific bacteria and their functional differences in the HME group. The microbial characteristics and metabolic pathways provide new insights for developing strategies to reduce methane emissions, supporting the sustainable development of the dairy industry. Full article

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. Full article

A direct assessment of the methane (CH₄) emission level and its variability factors is needed in each animal species in order to target the best mitigation strategy for the livestock sector. Therefore, the present study aimed to (1) test a laser methane detector (LMD) for the first time in Italian Mediterranean buffaloes (IMB), a non-invasive tool to quantify CH₄ emissions; (2) test the effect of season on the emissions; and (3) compare the results measured directly with the ones estimated with the existing equations. CH₄ emissions of twenty non-productive IMB, under the same feeding regimen, were monitored for 12 days in summer and winter. Significantly higher THI (74.46 ± 1.88 vs. 49.62 ± 4.87; p < 0.001), lower DMI (2.24 ± 0.04 vs. 2.51 ± 0.03% DMI/kg live weight; p < 0.001) and lower emission intensities (0.61 ± 0.15 vs. 0.75 ± 0.13; p < 0.001) were found during the summer period when compared with winter. LMD was found to be a versatile tool to be used in buffaloes, and it was clear that a summer increase in THI could act as a stressor for the animals, influencing their emissions. In addition, measured emissions were significantly higher than when estimated with the existing equations (p < 0.001), suggesting the need for further research in this area. Full article

The laser methane detector (LMD), is a proprietary hand-held open path laser measuring device. Its measurements are based on infrared absorption spectroscopy using a semiconductor laser as a collimated excitation source. In the current study, LMD measurements were carried out in two experiments using 20 and 71 lactating dairy cows in Spain and Scotland, respectively. The study aimed at testing four assumptions that may impact on the reliability and repeatability of the LMD measurements of ruminants. The study has verified that there is no difference in enteric methane measurements taken from a distance of 3 m than from those taken at a distance of 2 m; there was no effect to the measurements when the measurement angle was adjusted from 90° to 45°; that the presence of an adjacent animal had no effect on the methane measurements; and that measurements lasting up to 240 s are more precise than those taken for a shorter duration. The results indicate that angle, proximity to other animals, and distance had no effects and that measurements need to last a minimum of 240 s to maintain precision. Full article

The handheld, portable laser methane detector (LMD) was developed to detect gas leaks in industry from a safe distance. Since 2009, it has also been used to measure the methane (CH₄) concentration in the breath of cattle, sheep, and goats to quantify their CH₄ emissions. As there is no consensus on a uniform measurement and data-analysis protocol with the LMD, this article discusses important aspects of the measurement, the data analysis, and the applications of the LMD based on the literature. These aspects, such as the distance to the animal or the activity of the animals, should be fixed for all measurements of an experiment, and if this is not possible, they should at least be documented and considered as fixed effects in the statistical analysis. Important steps in data processing are thorough quality control and reduction in records to a single point measurement or “phenotype” for later analysis. The LMD can be used to rank animals according to their CH₄ breath concentration and to compare average CH₄ production at the group level. This makes it suitable for genetic and nutritional studies and for characterising different breeds and husbandry systems. The limitations are the lower accuracy compared to other methods, as only CH₄ concentration and not flux can be measured, and the high amount of work required for the measurement. However, due to its flexibility and non-invasiveness, the LMD can be an alternative in environments where other methods are not suitable or a complement to other methods. It would improve the applicability of the LMD method if there were a common protocol for measurement and data analysis developed jointly by a group of researchers. Full article

Greenhouse gas emissions from livestock farming and in particular enteric methane (CH₄) from ruminants are criticized for being one of the main contributors to climate change. Different breeding, feeding and management strategies are tested to decrease these emissions, but a status quo analysis is also relevant to implement such measures. The present study aimed to analyze the concentration of CH₄ in air exhaled by dairy cows along a rural-urban gradient of Bangalore, India. Urban, mixed and rural areas were defined based on a survey stratification index (SSI) comprising build-up density and distance to the city center. Using a laser methane detector (LMD), CH₄ concentration was determined in 2-min spot measurements of exhaled air of 448 cows at three equally spaced visits between June 2017 and April 2018. Mean, maximum and CH₄ concentration per duration of the overall measurement, eructation and respiration bouts were calculated. For the overall mean and respiration bouts, CH₄ concentration was higher in cows from urban areas, which had also higher milk yield than cows from mixed and rural areas. Although no differences were found in terms of the intake level of fibrous diet components, the type of measurement location (indoor, half-outdoor or outdoor) and pasture access had an impact on CH₄ concentration. To our knowledge, this is the first study using the LMD on-farm and in an urbanizing environment. The LMD measurements show variations in enteric CH₄ emissions along the rural-urban gradient of Bangalore that reflect differences in dairy husbandry systems governed by the social-ecological context. Full article

The aim of this trial was to study the agreement between the non-dispersive infrared methane analyzer (NDIR) method and the hand held laser methane detector (LMD). Methane (CH₄) was measured simultaneously with the two devices totaling 164 paired measurements. The repeatability of the CH₄ concentration was greater with the NDIR (0.42) than for the LMD (0.23). However, for the number of peaks, repeatability of the LMD was greater (0.20 vs. 0.14, respectively). Correlation was moderately high and positive for CH₄ concentration (0.73 and 0.74, respectively) and number of peaks (0.72 and 0.72, respectively), and the repeated measures correlation and the individual-level correlation were high (0.98 and 0.94, respectively). A moderate concordance correlation coefficient was observed for the CH₄ concentration (0.62) and for the number of peaks (0.66). A moderate-high coefficient of individual agreement for the CH₄ concentration (0.83) and the number of peaks (0.77) were observed. However, CH₄ concentrations population means and all variance components differed between instruments. In conclusion, methane concentration measurements obtained by means of NDIR and LMD cannot be used interchangeably. The joint use of both methods could be considered for genetic selection purposes or for mitigation strategies only if sources of disagreement, which result in different between-subject and within-subject variabilities, are identified and corrected for. Full article