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Relationship between daily milk yield and methane emission index measured during milking (MEIm) on farm in experiment 1. The MEIm was calculated from methane peaks (eructations) as the product of peak frequency and peak area, without correction for dilution with ambient air. Data points are individual means for 82 cows sampled during 1 to 6 milkings. The line shows the relationship (R2=0.50, P<0.001)
Source publication
The objective of this study was to investigate whether measurement of methane emissions by individual dairy cows during milking could provide a useful technique for monitoring on-farm methane emissions. To quantify methane emissions from individual cows on farm, we developed a novel technique based on sampling air released by eructation during milk...
Citations
... The enteric CH 4 was collected across the experiment using a hooded infrared CH 4 analyser (Guardian NG gas card, Edinburgh Instruments Ltd., Livingston, UK) attached to the feed bins ( Figure 1) [18]. The sensors were calibrated each morning with 1% CH 4 and 0% CH 4 gas (Noventis Australia Pty Ltd., Melbourne, VIC, Australia). ...
... The enteric CH4 was collected across the experiment using a hooded infrare analyser (Guardian NG gas card, Edinburgh Instruments Ltd., Livingston, UK) att to the feed bins ( Figure 1) [18]. The sensors were calibrated each morning with 1% and 0% CH4 gas (Noventis Australia Pty Ltd., Melbourne, VIC, Australia). ...
Simple Summary
Enteric methane emission reduction from livestock is one of the most discussed topics of the 21st century. Plant-based polyphenols are found to be one of the effective solutions to reduce methane emissions from ruminant animals. Hence, this study evaluates the effect of sugarcane-based polyphenolic supplements on enteric methane emission and its effect on microbiota and body weight changes in sheep. The results from this study indicate that both dosages of Polygain reduced methane emission from sheep and increased average daily gain compared to the control group animals with notable changes in rumen microbiota.
Abstract
The objective of this study was to evaluate the effects of feeding sugarcane-derived polyphenolic supplement (Polygain, The Product Makers Australia, Keysborough, VIC, Australia) on enteric methane (CH4) emission, rumen microbiota, and performance of second-cross lambs. For this purpose, 24 Poll Dorset × (Border Leicester × Merino) lambs were allocated to 3 different treatments: Control (C), 0.25% Polygain (0.25 PG), and 1% Polygain (1 PG) diets with a uniform basal feed (25% cracked wheat grain, 25% cracked barley grain, 25% oaten chaff, 25% lucerne chaff). Both doses of Polygain reduced the total CH4 production (g/day; p = 0.006), CH4 yield (CH4, g/kg of dry matter intake; p = 0.003) and CH4 intensity (CH4, g/kg of BW; p = 0.003). Dry matter intake tended to be greater (p = 0.08) in sheep fed 1 PG compared to the C group, with the 0.25 PG group being intermediate. The average daily gain of the lambs was improved (p = 0.03) with 1% Polygain supplementation. The relative abundance of genera Methanobrevibacter_unidentified, Methanomethylophilaceae_uncultured, Methanogenic archaeon mixed culture ISO4-G1, Methanosphaera uncultured rumen methanogen, Methanogenic archaeon ISO4-H5, and Methanobrevibacter boviskoreani JH1 were reduced with Polygain supplementation. In conclusion, feeding Polygain reduced lambs’ enteric CH4 emissions, altered the rumen microbiome, and improved the growth performance of lambs.
... Measurements from infrared spectroscopy are highly variable, and several hundred measurements are required during a short period of time to quantify the mean of the dependent variable for individual animals (Lassen and Løvendahl, 2016). However, daily CH 4 output measured in respiration chambers and estimated using infrared spectroscopy had a linear relationship (R 2 = 0.79) for a group of 12 Holstein cows (Garnsworthy et al., 2012). The method is primarily used for dairy cows because the data can be collected during times of feeding or milking. ...
Methane (CH4) is a greenhouse gas that is produced and emitted from ruminant animals through enteric fermentation. Methane production from cattle has an environmental impact and is an energetic inefficiency. In the beef industry, CH4 production from enteric fermentation impacts all three pillars of sustainability: environmental, social, and economic. A variety of factors influence the quantity of CH4 produced during enteric fermentation, including characteristics of the rumen and feed composition. There are several methodologies available to either quantify or estimate CH4 production from cattle, all with distinct advantages and disadvantages. Methodologies include respiration calorimetry, the sulfur-hexafluoride tracer technique, infrared spectroscopy, prediction models, and the GreenFeed system. Published studies assess the accuracy of the various methodologies and compare estimates from different methods. There are advantages and disadvantages of each technology as they relate to the use of these phenotypes in genetic evaluation systems. Heritability and variance components of CH4 production have been estimated using the different CH4 quantification methods. Agreement in both the amounts of CH4 emitted and heritability estimates of CH4 emissions between various measurement methodologies varies in the literature. Using greenhouse gas traits in selection indices along with relevant output traits could provide producers with a tool to make selection decisions on environmental sustainability while also considering productivity. The objective of this review was to discuss factors that influence CH4 production, methods to quantify CH4 production for genetic evaluation, and genetic parameters of CH4 production in beef cattle.
... Methane emissions from livestock farms must be accurately estimated in order to mitigate GHG emissions and to explore alternatives for reducing them. Precise quantification of methane emissions offers a baseline for measuring the efficacy of emission reduction efforts and enables the formulation of realistic targets [26][27][28]. Current methods for measuring CH 4 emissions from ruminants show high accuracy compared to the respiration chamber method, which is considered the golden standard technique in quantifying the CH 4 emissions from animals. ...
... Using this method, cows' eructation (belches) is continually sampled for gases into a polyethylene sampling tube that is inserted in the feed trough of an automatic milking system [27,28]. An infrared methane concentration analyzer is then used to examine the gases that were sampled. ...
... The sniffer technique has the benefit of being able to quickly and frequently assess methane concentrations from a large number of individual lactating dairy cows during normal milking under commercial settings. The sniffer technique has been found to provide a linear correlation between methane emission rate and methane production measured by the respiration chamber method, and the sniffer technique's estimation of daily methane emissions is in good agreement with predictions based on milk yield and dairy cow body weight [27,28]. The sniffer technique can also distinguish between cows with high and low methane emissions. ...
Simple Summary
This paper explores the methane emissions from the livestock industry and their large impact on climate change, with a particular focus on cattle. It emphasizes how important it is to monitor and control methane accurately because it is a powerful greenhouse gas that accounts for 14–16% of world emissions. The study evaluates both conventional and AI-powered techniques for methane emission detection, emphasizing the significance of cattle in particular. It has been determined that region-specific formulations are required. The review discusses a number of topics, such as the methane emissions from livestock, the promise of AI technology, difficulties in gathering data, the use of methane in carbon credit programs, and current research and innovation. The review aims to improve knowledge and practices for climate change mitigation by highlighting the crucial role that accurate measurement and estimation methodologies play. It draws attention to the role that methane produced by livestock, particularly cattle, plays in climate change and stresses the need for precise measuring methods to be integrated into mitigation efforts.
Abstract
This review examines the significant role of methane emissions in the livestock industry, with a focus on cattle and their substantial impact on climate change. It highlights the importance of accurate measurement and management techniques for methane, a potent greenhouse gas accounting for 14–16% of global emissions. The study evaluates both conventional and AI-driven methods for detecting methane emissions from livestock, particularly emphasizing cattle contributions, and the need for region-specific formulas. Sections cover livestock methane emissions, the potential of AI technology, data collection issues, methane’s significance in carbon credit schemes, and current research and innovation. The review emphasizes the critical role of accurate measurement and estimation methods for effective climate change mitigation and reducing methane emissions from livestock operations. Overall, it provides a comprehensive overview of methane emissions in the livestock industry by synthesizing existing research and literature, aiming to improve knowledge and methods for mitigating climate change. Livestock-generated methane, especially from cattle, is highlighted as a crucial factor in climate change, and the review underscores the importance of integrating precise measurement and estimation techniques for effective mitigation.
... The sniffer method was first described by Garnsworthy et al. (2012). Using this method air is sampled near the cow's nostrils through a tube fixed in the feed bin within an automatic milking robot (AMS) and connected directly to a gas analyzer (Bell et al., 2014;Garnsworthy et al., 2012;Lassen et al., 2012;Pszczola et al., 2017). ...
... The sniffer method was first described by Garnsworthy et al. (2012). Using this method air is sampled near the cow's nostrils through a tube fixed in the feed bin within an automatic milking robot (AMS) and connected directly to a gas analyzer (Bell et al., 2014;Garnsworthy et al., 2012;Lassen et al., 2012;Pszczola et al., 2017). There are no standard sniffers, and different research centers are using different gas analyzers, however, nondispersive infrared gas sensors are often used to measure gas concentrations in breath and belches and often with very short sampling intervals from one to a few seconds (López-Paredes et al., 2020;van Engelen et al., 2018;Manzanilla-Pech et al., 2022). ...
Mitigating the considerable contribution of ruminant livestock to global methane emissions, which accounts for 17%, is of vital importance. One significant approach to this is the genetic selection of cows for reduced methane emissions, a strategy that demands large-scale, accurate methane emission measurements from individual cows in commercial farms. The existing 'sniffer' technique, which obtains samples of the air near the cow's nostrils through a tube fixed in the feed bin within an automated milking system (AMS), presents challenges due to the cow's head movements during the milking recording, creating anomalies in the gas emission data. Moreover, correcting these anomalies directly remains a pressing issue. This study presents a novel data mining approach for detecting anomalous by approximating the cow head position using CO 2 time series data collected from cows. The data was collected using sniffer machines on two dairy cattle farms and analyzed using a data-decomposition approach. The performance of the proposed method was evaluated using probabilistic methods such as the Kolmogorov-Smirnov (KS) test and confusion matrix. Results showed that the proposed method was able to accurately detect anomalous peaks in the synthetic CO 2 time series, with more than 95% of anomalous peaks being detected. This study demonstrates the potential of the proposed method to improve the accuracy of methane emissions estimates from cows and the understanding of cows' behavior. To further validate the effectiveness of the proposed method, it was tested on the gas emission dataset recorded by GreenFeed (C-Lock), which contains various CO 2 time series with annotated anomalous points. The validation results demonstrated that the method successfully detected more than 90% of the anomalous points in the time series while marking the peaks containing the anomalous data points. This approach proved to be efficient and accurate, as the peaks represent regions of high anomaly concentration and are more likely to contain true anomalies.
... Methane concentration in feed bins during milking was determined by the "Sniffer method" as described in [19][20][21]. Briefly, an infrared methane analyzer (Guardian Plus; Edinburgh Instruments Ltd., Livingstone, UK) was outside the feed bin of each milking robot with a sampling tube extended into the feed bin. ...
Simple Summary
Enteric methane emissions from ruminants have emerged as a major challenge to the global agriculture industry. However, the lack of tools available to commercial farmers to measure and mitigate these emissions is preventing this challenge from being addressed. This study aimed to evaluate natural sugarcane extract’s potential to mitigate these emissions in a commercial dairy environment and assess any impact on milk production and composition. The results of this study indicate a significant increase in milk production, with less methane detected across the herd. Bulk tank somatic cell counts were also reduced indicating improved udder health of cows.
Abstract
(1) Background: The purpose of this study was to assess the influence of a natural sugarcane extract (Polygain™) on milk production, milk composition and methane emissions on a commercial dairy farm. (2) Methods: A three-week baseline was established for lactating Holstein × Friesian animals. Following this baseline period, these animals were fed Polygain™ at 0.25% of their estimated dry matter intake for 3 weeks. Methane concentration in the feed bin was determined at each milking using the Gascard NG Infrared Sensor (Edinburgh Sensors LTD). (3) Results: During the intervention phase milk yield increased significantly from 26.43 kg to 28.54 kg per cow per day, whilst methane emissions and bulk tank somatic cell counts decreased significantly in the intervention phase. For methane concentration, an average of 246 ppm during the baseline periods reduced to an average of 161.09 ppm during the intervention phase. For the bulk tank somatic cell counts, the average was observed at 283,200 during the baseline and reduced to an average value of 151,100 during the intervention phase. (4) Conclusions: The natural sugarcane extract was shown to have the potential to mitigate enteric methane emissions while also increasing production and animal wellbeing outcomes in a commercial dairy setting.
... Consequently, while this study may exhibit reduced statistical power due to its sample size, this limitation is often addressed by demonstrating statistical significance exclusively for stronger correlation values. Also, while previous studies demonstrated a correlation between DMI and CH 4 emissions [25,26], our results did not reveal such trends. In fact, it is likely that the homogenous experimental conditions and the similarity between individuals encompassing factors such as weight, feed intake, and physiological conditions may have played a pivotal role in shaping the results obtained. ...
... The variations observed between other studies and the present study may also be related to the control of GF measurements, such as the timing of sampling events [7] or the number of GF visits per animal [30]. Additionally, cattle tend to release considerable amounts of methane through eructation while eating, resulting in elevated emission rates and more frequent occurrences of methane peaks characterized by higher concentrations [26]. In this study, more emphasis was placed on the duration for which the animal's head remained in the GF unit, rather than the frequency of visits. ...
... Regarding methane emission measurements obtained from GF technology, comparisons between housed dairy cows and non-lactating cows under GF, sulfur hexafluoride (SF 6 ) tracer technique, sniffer methods, and laser detector methods suggested that less variable data and a more realistic range of emission estimates could be obtained under GF conditions [7,26,27,41]. Liu et al. [42] developed prediction models for lactating Holstein cows in terms of the daily and average methane production (g/d), yield (g/kg DMI), and intensity (g/kg fat-and protein-corrected milk). Their study reported higher methane emissions for both daily and average (372.60 vs. 350.20 ...
This study investigated the impact of feeding systems on the determination of enteric methane (CH 4) emissions factor in cattle. Real-time feed intake data, a crucial CH 4 conversion rate (Y m value) parameter, were obtained using a roughage intake control (RIC) unit within a smart farm system. Greenhouse gas (GHG) emissions, including CH 4 and carbon dioxide (CO 2), from Holstein steers were monitored using a GreenFeed (GF) 344 unit. The results revealed satisfactory body weight (383 ± 57.19 kg) and daily weight gain (2.00 ± 0.83 kg), which are crucial factors. CO 2 production exhibited positive correlations with the initial body weight (r = 0.72, p = 0.027), feed intake (r = 0.71, p = 0.029), and feed conversion ratio (r = 0.69, p = 0.036). Five different emission factors (EFs), EF A (New Equation 10.21A) and Equation 10.21 (EF B , EF C , EF D , and EF E), were used for GHG calculations following the Intergovernmental Panel on Climate Change (IPCC) Tier 2 approach. The estimated CH 4 EFs using these equations were 69.91, 69.91, 91.79, 67.26, and 42.60 kg CH 4 /head/year. These findings highlight the potential for further exploration and adoption of smart farming technology , which has the potential to enhance prediction accuracy and reduce the uncertainty in Y m values tailored to specific countries or regions.
... Other studies have found no effects of grazing on milk production or CH 4 emissions from grazing cows (Dall-Orsoletta et al., 2016;Cameron et al., 2018). Enteric CH 4 emissions from grazing dairy cows can be recorded using several techniques such as the sulphur hexafluoride (SF 6 ) tracer technique (Pinares-Patiño & Clark, 2008) or direct measurements of emissions during milking by the sniffer technic (Garnsworthy et al., 2012). However, neither of these techniques can monitor short-term effects on CH 4 emissions over the course of a day. ...
... Methane (CH 4 ) emission estimates were carried out daily during milking (07:00 and 09:00) for 10 consecutive days. During this time, cows received concentrate in a custommade headbox fitted with a methane IR analyzer (range 0-10,000 ppm; Guardian Plus; Edinburgh Instruments Ltd., Livingston, UK), based on the methodology developed by Garnsworthy et al. (2012a) [46]. The headbox measured 58 × 47 × 102 cm, with a trough where concentrate was supplied ( Figure 1). ...
... Recordings were carried out in early to mid-lactation cows without interference in the regular daily management routine in each system. Daily methane emissions (g·d −1 ) and methane emissions per kg DM intake (g·kg) were calculated based on the equations reported by Garnsworthy et al. (2012a) [46]. intake means metabolizable energy intake expressed as megaJoules d −1 /animal. ...
... Methane (CH4) emission estimates were carried out daily during milking (07:00 and 09:00) for 10 consecutive days. During this time, cows received concentrate in a custom-made headbox fitted with a methane IR analyzer (range 0-10,000 ppm; Guardian Plus; Edinburgh Instruments Ltd., Livingston, UK), based on the methodology developed by Garnsworthy et al. (2012a) [46]. The headbox measured 58 × 47 × 102 cm, with a trough where concentrate was supplied ( Figure 1). ...
Assessments of the efficiency of grazing systems, in terms of productivity and ecological sustainability, are necessary in view of the increased demand for animal protein. In this study, the methane (CH4) emissions (sniffer methodology), dry matter (DM) yield, paddock chemical composition (AOAC and Van Soest methods), nutrient intake (dry matter, DMI; crude protein, CPI; metabolizable energy, MEI), daily milk yield (DMY), body condition score (BCS), and body weight (BW) of cattle, in intensive silvopastoral systems (ISPSs) and monoculture systems (MSs), in the tropics of Mexico were evaluated. In the ISPS, CH4 emissions (18% less) and DMY were lower than in the MS. Cows from MSs tend to disperse across higher values of CH4 emissions per kg of DMI, as well as higher milk production, while cows from the ISPS were dispersed over a higher intake (DMI, CPI, and MEI) and lower CH4 emissions. There were no differences between systems in paddock DM yield, chemical composition, cows’ BCS, and BW, regardless of whether it was the dry (April to May) and rainy (September to October) season. Based on the results obtained in this study, ISPSs contribute to the mitigation of methane emissions in cattle; forage and animal production variables in both systems were similar, with a lower use of imported inputs in the ISPS.
... However, this method is accompanied by disruption of the animal's natural behavior and needs great technical and personnel requirements, limiting its widespread use for practical and research purposes [12,13]. Consequently, numerous short-term methods for measuring enteric CH 4 emissions have been established, such as GreenFeed and methane hood system, sniffer method and laser methane detection, which are applicable to a larger number of animals at lower costs and enable the accurate measurement of enteric CH 4 emissions in the natural environment of animals [11][12][13][14][15][16][17][18]. Bearing in mind that a large number of factors infl uence methane emission, the average CH 4 emission values are not suffi cient to defi ne the phenotype of cows according to CH 4 production. ...
Ruminant husbandry contributes to global methane (CH 4 ) emissions and beside its negative impact on the environment, enteric CH 4 emissions cause a loss of gross energy intake in cows. The study is aimed to estimate CH 4 emission and metabolic status in dairy cows via the methane concentration profile as a tool for analyzing the CH4 production pattern. The study included eighteen cows whose enteric CH 4 emission was measured during three consecutive days in three periods: 2 hours before (P1), 2–4 hours (P2) and 6–8 hours (P3) after the morning feeding. Based on CH 4 enteric emissions, cows were divided into two groups (n=6, respectively): HM (average CH 4 concentration: 5430.08 ± 365.92 ppm) and LM (average CH 4 concentration: 1351.85 ± 205.20 ppm). Following CH 4 measurement, on day 3, venous blood was sampled to determine the indicators of the metabolic status. HM cows had significantly higher average CH 4 concentrations, maximum and average CH4 peak amplitude than LM cows in all measuring periods (P1-P3), while the number of CH 4 peaks tended to be higher in HM than in LM cows in P2. There were no differences in the maximum and average CH 4 peak width and average distance among two CH4 peaks between examined groups of cows. HM cows had significantly higher total protein concentrations and significantly lower total bilirubin and NEFA concentrations than LM cows. In conclusion, HM cows have a greater number of eructations and release more CH 4 per eructation than LM cows, hence the differences in metabolic status are most likely related to the differences in their liver function.
... Comparing the results of storage-related methane emissions of rations 1 and 2, it is evident that increasing the amount of corn in the feed ration is a strategy to reduce CH 4 emissions (Garnsworthy et al. (2012), Wilkinson and Garnsworthy (2016), Hristov et al. (2013), Hassanat et al. (2013)). Comparable results were shown by Van Middelaar et al. (2013) and Wilkinson and Garnsworthy (2016). ...
Reducing CO2 emissions is one of the highest priorities in animal production. Regarding methane reduction, feed additives are of growing importance. As shown in a meta-analysis, the use of the essential oil (EO) blend Agolin Ruminant affects methane production per day (- 8.8%), milk yield (+ 4.1%), and feed efficiency (+ 4.4%). Building on these results, the present study investigated the effect of varying individual parameters on the carbon footprint of milk. The environmental and operational management system REPRO was applied to calculate the CO2 emissions. Calculation of CO2 emissions include enteric and storage-related CH4, storage-, and pasture-related N2O as well as direct and indirect energy expenditures. Three feed rations were created, differing in their basic feed components such as grass silage, corn silage, and pasture. Each feed ration was differentiated into three variants: variant 1 CON (no additive), variant 2 EO, and variant 3 (15% reduction of enteric methane compared to CON). Due to the reducing effect of EO on enteric methane production, a reduction potential of up to 6% could be calculated for all rations. Considering other variable parameters, such as the positive effects on ECM yield and feed efficiency, a GHG reduction potential of up to 10% can be achieved for the silage rations and almost 9% for the pasture ration. Modeling showed that indirect methane reduction strategies are important contributors to environmental impacts. Reduction of enteric methane emissions is fundamental, as they account for the largest share of GHG emissions from dairy production.
