The inclusion of forage mixtures in the diet of growing dairy heifers: Impacts on digestion, energy utilisation, and methane emissions

Hammond, K.J.; Humphries, D. J.; Westbury, Duncan B.; Thompson, A.; Crompton, L.A.; Kirton, P.; Green, C.; Reynolds, C.K.

doi:10.1016/j.agee.2014.07.016

Cited by 37 publications

(38 citation statements)

References 21 publications

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“…However, this effect would still be too small to account for all of the difference in MP. Recent research from the United Kingdom (Hammond et al 2014) supports Irish research (Yan et al 2000) showing that MY is higher for ensiled forages. Hammond et al (2014) found MY to be between 28.0 and 28.9 g/kg DMI for ryegrass and ryegrass-legume silages.…”

Section: Methane Yieldmentioning

confidence: 86%

“…However, when similar forages were grazed, MY was <23 g/kg DMI. It should be noted that Hammond et al (2014) used respiration chambers for the silage study, while the SF 6 technique was used for the grazing study. In the United States, calculations for estimating national emissions rely on an empirical approach for beef cattle based on Tier 2 methods for feedlots (USDA 2011).…”

Section: Methane Yieldmentioning

confidence: 99%

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A universal equation to predict methane production of forage-fed cattle in Australia

Charmley

Williams²,

Moate³

et al. 2016

Anim. Prod. Sci.

210

138

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Abstract. The methods for estimating methane emissions from cattle as used in the Australian national inventory are based on older data that have now been superseded by a large amount of more recent data. Recent data suggested that the current inventory emissions estimates can be improved. To address this issue, a total of 1034 individual animal records of daily methane production (MP) was used to reassess the relationship between MP and each of dry matter intake (DMI) and gross energy intake (GEI). Data were restricted to trials conducted in the past 10 years using open-circuit respiration chambers, with cattle fed forage-based diets (forage >70%). Results from diets considered to inhibit methanogenesis were omitted from the dataset. Records were obtained from dairy cattle fed temperate forages (220 records), beef cattle fed temperate forages (680 records) and beef cattle fed tropical forages (133 records). Relationships were very similar for all three production categories and single relationships for MP on a DMI or GEI basis were proposed for national inventory purposes. These relationships were MP (g/day) = 20.7 (AE0.28) · DMI (kg/day) (R 2 = 0.92, P < 0.001) and MP (MJ/day) = 0.063 (AE0.008) · GEI (MJ/day) (R 2 = 0.93, P < 0.001). If the revised MP (g/day) approach is used to calculate Australia's national inventory, it will reduce estimates of emissions of forage-fed cattle by 24%. Assuming a global warming potential of 25 for methane, this represents a 12.6 Mt CO 2 -e reduction in calculated annual emissions from Australian cattle.

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Section: Methane Yieldmentioning

confidence: 86%

Section: Methane Yieldmentioning

confidence: 99%

A universal equation to predict methane production of forage-fed cattle in Australia

Charmley

Williams²,

Moate³

et al. 2016

Anim. Prod. Sci.

210

138

View full text Add to dashboard Cite

show abstract

“…This discrepancy between Irish and Australian data may be attributed to the predominance of extensively fermented grass silages in many of the Irish studies. Dairy research from the United Kingdom (Hammond et al 2014) supports Irish research (Yan et al 2000), showing that MY is higher for ensiled forages than fresh pasture. We included relative amount of grain in the diet (d_diet) as a fixed categorical effect, but other dietary effects, such as fresh versus ensiled pasture, were not included for reasons given previously.…”

Section: Other Methane Meta-analysesmentioning

confidence: 93%

Global beef cattle methane emissions: yield prediction by cluster and meta-analyses

Cottle

Eckard

2018

Anim. Prod. Sci.

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Abstract.Methane yield values (MY; g methane/kg dry-matter intake) in beef cattle reported in the global literature (expanded MitiGate database of methane-mitigation studies) were analysed by cluster and meta-analyses. The Ward and k means cluster analyses included accounting for the categorical effects of methane measurement method, cattle breed type, country or region of study, age and sex of cattle, and proportion of grain in the diet and the standardised continuous variables of number of animals, liveweight and MY. After removal of data from outlier studies, meta-analyses were conducted on subsets of data to produce prediction equations for MY. Removing outliers with absolute studentised residual values of >1, followed by meta-analysis of data accounting for categorical effects, is recommended as a method for predicting MY. The large differences among some countries in MY values were significant but difficult to interpret. On the basis of the datasets available, a single, global MY or percentage of gross energy in feed converted to methane (Y m ) value is not appropriate for use in Intergovernmental Panel on Climate Change (IPCC) greenhouse accounting methods around the world. Therefore, ideally country-specific MY values should be used in each country's accounts (i.e. an IPCC Tier 2 or 3 approach) from data generated within that country.

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“…Further details of these treatments are given in Hammond et al (2014). Similar to experiment 1, experiment 2 was a 4 × 4 Latin Square design with 33 day periods, with animals fed and housed in a similar manner as detailed for experiment 1.…”

Section: Methodsmentioning

confidence: 99%

Methane emissions from cattle: Estimates from short-term measurements using a GreenFeed system compared with measurements obtained using respiration chambers or sulphur hexafluoride tracer

Hammond

Humphries

Crompton

et al. 2015

Animal Feed Science and Technology

Self Cite

108

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a b s t r a c tThe GreenFeed (GF) system (C-Lock Inc., Rapid City, USA) is used to estimate total daily methane emissions of individual cattle using short-term measurements obtained over several days. Our objective was to compare measurements of methane emission by growing cattle obtained using the GF system with measurements using respiration chambers (RC) or sulphur hexafluoride tracer (SF 6 ). It was hypothesised that estimates of methane emission for individual animals and treatments would be similar for GF compared to RC or SF 6 techniques. In experiment 1, maize or grass silage-based diets were fed to four growing Holstein heifers, whilst for experiment 2, four different heifers were fed four haylage treatments. Both experiments were a 4 × 4 Latin square design with 33 day periods. GreenFeed measurements of methane emission were obtained over 7 days (days 22-28) and compared to subsequent RC measurements over 4 days (days 29-33). For experiment 3, 12 growing heifers rotationally grazed three swards for 26 days, with simultaneous GF and SF 6 measurements over two 4 day measurement periods (days 15-19 and days 22-26). Overall methane emissions (g/day and g/kg dry matter intake [DMI]) measured using GF in experiments 1 (198 and 26.6, respectively) and 2 (208 and 27.8, respectively) were similar to averages obtained using RC (218 and 28.3, respectively for experiment 1; and 209 and 27.7, respectively, for experiment 2); but there was poor concordance between the two methods (0.1043 for experiments 1 and 2 combined). Overall, methane emissions measured using SF 6 were higher (P<0.001) than GF during grazing (186 vs. 164 g/day), but there was significant (P<0.01) concordance between the two methods (0.6017). There were fewer methane measurements by GF under grazing conditions in experiment 3 (1.60/day) compared to indoor measurements in experiments 1 (2.11/day) and 2 (2.34/day). Significant treatment effects on methane emission measured using RC and SF 6 were not evident for GF measurements, and the ranking for treatments and individual animals differed using the GF system. We conclude that under our conditions of use the GF system was unable to detect significant treatment and individual animal differences in methane emissions that were Abbreviations: CI, confidence interval; DM(I), dry matter (intake); GF, GreenFeed; LW, live weight; LWG, LW gain; NDIR, non-dispersive infrared; RC, respiration chambers; RFID, radio frequency identification; SF6, sulphur hexafluoride tracer. identified using both RC and SF 6 techniques, in part due to limited numbers and timing of measurements obtained. Our data suggest that successful use of the GF system is reliant on the number and timing of measurements obtained relative to diurnal patterns of methane emission.

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The inclusion of forage mixtures in the diet of growing dairy heifers: Impacts on digestion, energy utilisation, and methane emissions

Cited by 37 publications

References 21 publications

A universal equation to predict methane production of forage-fed cattle in Australia

A universal equation to predict methane production of forage-fed cattle in Australia

Global beef cattle methane emissions: yield prediction by cluster and meta-analyses

Methane emissions from cattle: Estimates from short-term measurements using a GreenFeed system compared with measurements obtained using respiration chambers or sulphur hexafluoride tracer

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