Integrating spot short-term measurements of carbon emissions and backward dietary energy partition calculations to estimate intake in lactating dairy cows fed ad libitum or restricted.

The objective of this study was to use spot short-term measurements of CH4 (QCH4) and CO2 (QCO2) integrated with backward dietary energy partition calculations to estimate dry matter intake (DMI) in lactating dairy cows. Twelve multiparous cows averaging 173±37d in milk and 4 primiparous cows averaging 179±27d in milk were blocked by days in milk, parity, and DMI (as a percentage of body weight) and, within each block, randomly assigned to 1 of 2 treatments: ad libitum intake (AL) or restricted intake (RI=90% DMI) according to a crossover design. Each experimental period lasted 22d with 14d for treatments adaptation and 8d for data and sample collection. Diets contained (dry matter basis): 40% corn silage, 12% grass-legume haylage, and 48% concentrate. Spot short-term gas measurements were taken in 5-min sampling periods from 15 cows (1 cow refused sampling) using a portable, automated, open-circuit gas quantification system (GreenFeed, C-Lock Inc., Rapid City, SD) with intervals of 12h between the 2daily samples. Sampling points were advanced 2h from a day to the next to yield 16 gas samples per cow over 8d to account for diurnal variation in QCH4 and QCO2. The following equations were used sequentially to estimate DMI: (1) heat production (MJ/d)=(4.96 + 16.07 ÷ respiratory quotient) × QCO2; respiratory quotient=0.95; (2) metabolizable energy intake (MJ/d)=(heat production + milk energy) ± tissue energy balance; (3) digestible energy (DE) intake (MJ/d)=metabolizable energy + CH4 energy + urinary energy; (4) gross energy (GE) intake (MJ/d)=DE + [(DE ÷ in vitro true dry matter digestibility) - DE]; and (5) DMI (kg/d)=GE intake estimated ÷ diet GE concentration. Data were analyzed using the MIXED procedure of SAS (SAS Institute Inc., Cary, NC) and Fit Model procedure in JMP (α=0.05; SAS Institute Inc.). Cows significantly differed in DMI measured (23.8 vs. 22.4kg/d for AL and RI, respectively). Dry matter intake estimated using QCH4 and QCO2 coupled with dietary backward energy partition calculations (Equations 1 to 5 above) was highest in cows fed for AL (22.5 vs. 20.2kg/d). The resulting R(2) were 0.28 between DMI measured and DMI estimated by gaseous measurements, and 0.36 between DMI measured and DMI predicted by the National Research Council model (2001). Results showed that spot short-term measurements of QCH4 and QCO2 coupled with dietary backward estimations of energy partition underestimated DMI by 7.8%. However, the approach proposed herein was able to significantly discriminate differences in DMI between cows fed for AL or RI.

Short communication: Use of a portable, automated, open-circuit gas quantification system and the sulfur hexafluoride tracer technique for measuring enteric methane emissions in Holstein cows fed ad libitum or restricted.

The objective of this study was to measure enteric CH4 emissions using a new portable automated open-circuit gas quantification system (GQS) and the sulfur hexafluoride tracer technique (SF6) in midlactation Holstein cows housed in a tiestall barn. Sixteen cows averaging 176 ± 34 d in milk, 40.7 ± 6.1 kg of milk yield, and 685 ± 49 kg of body weight were randomly assigned to 1 out of 2 treatments according to a crossover design. Treatments were (1) ad libitum (adjusted daily to yield 10% orts) and (2) restricted feed intake [set to restrict feed by 10% of baseline dry matter intake (DMI)]. Each experimental period lasted 22d, with 14 d for treatment adaptation and 8d for data and sample collection. A common diet was fed to the cows as a total mixed ration and contained 40.4% corn silage, 11.2% grass-legume haylage, and 48.4% concentrate on a dry matter basis. Spot 5-min measurements using the GQS were taken twice daily with a 12-h interval between sampling and sampling times advanced 2h daily to account for diurnal variation in CH4 emissions. Canisters for the SF6 method were sampled twice daily before milking with 4 local background gas canisters inside the barn analyzed for background gas concentrations. Enteric CH4 emissions were not affected by treatments and averaged 472 and 458 g/d (standard error of the mean = 18 g/d) for ad libitum and restricted intake treatments, respectively (data not shown). The GQS appears to be a reliable method because of the relatively low coefficients of variation (ranging from 14.1 to 22.4%) for CH4 emissions and a moderate relationship (coefficient of determination = 0.42) between CH4 emissions and DMI. The SF6 resulted in large coefficients of variation (ranging from 16.0 to 111%) for CH4 emissions and a poor relationship (coefficient of determination = 0.17) between CH4 emissions and DMI, likely because of limited barn ventilation and high background gas concentration. Research with improved barn ventilation systems or outdoors is warranted to further assess the GQS and SF6 methodologies.