Article

Energy expenditure of gazing cows and cows fed grass indoors as determined by the 13C bicarbonate dilution technique using an automatic blood sampling system

Agroscope Liebefeld-Posieux Research Station ALP, 1725 Posieux, Switzerland.
Journal of Dairy Science (Impact Factor: 2.57). 04/2011; 94:1989-2005. DOI: 10.3168/jds.2010-3658
Source: PubMed

ABSTRACT

The objectives of the study were to assess the 13C bicarbonate
dilution technique using an automatic blood
sampling system and to use this technique to estimate
energy expenditure (EE) based on the CO2 production
of 14 lactating Holstein cows on pasture or in a freestall
barn. The effects of physical activity and eating
behavior on EE were also assessed. Cows were exposed
to each feeding system in a crossover design with two
14-d experimental periods, each consisting of an adaptation
period and a 7-d data collection period. Cows
either grazed on pasture or had ad libitum access, in
the freestall barn, to grass cut daily from the same paddock.
All cows were supplemented with a cereal-based
concentrate. The EE of each cow was determined from
0700 to 1300 h on 1 d of each collection period. Blood
samples for the 13C bicarbonate dilution technique were
taken either manually in the barn or using an automatic
blood sampling system on pasture. Eating pattern and
physical activity were recorded from 0700 to 1300 h
using a behavior recorder and an activity meter, respectively.
Milk yield was recorded daily. Individual feed
intake was estimated using the alkane double-indicator
technique. Two preceding experiments confirmed that
the sampling technique (manual or automatic) and the
following storage of the blood samples (frozen directly
after withdrawal or first cooled on ice and then frozen
6 h later) had no effect on 13CO2 enrichment in the extracted
blood CO2 or on the subsequent calculation of
CO2 production. During the 6-h measurement period,
the EE of cows on pasture was higher than that of
cows in the freestall barn. Daily feed intake and milk
production were not affected by the feeding treatment.
Grazing cows spent more time walking and less time
standing and lying than did cows fed indoors. Time
spent eating was greater and time spent ruminating
was lower for cows on pasture compared with grass-fed cows in the barn. In conclusion, the 13C bicarbonate
dilution technique, combined with an automatic blood
sampling system, is a suitable method to determine the
EE of lactating dairy cows on pasture. Positive correlations
between EE and walking and eating time indicate
that the higher energy requirements of dairy cows on
pasture may be at least partly caused by a higher level
of physical activity. However, before specific recommendations
about additional energy supply can be given,
it must be determined whether EE measured over 6 h
can be extrapolated to 24 h. Furthermore, the apparent
inconsistency between EE, feed intake, and milk
production needs to be resolved.

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    • "Heat production (HP) estimated (MJ/d) = (4.96 + 16.07 ÷ respiratory quotient) × QCO 2 (L/d) ÷ 1,000 (Kaufmann et al., 2011). "
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    ABSTRACT: 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 ± 37 d in milk and 4 primiparous cows averaging 179 ± 27 d 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 22 d with 14 d for treatments adaptation and 8 d 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 12 h between the 2 daily samples. Sampling points were advanced 2 h from a day to the next to yield 16 gas samples per cow over 8 d 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. 22.4 kg/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. 20.2 kg/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.
    Full-text · Article · Oct 2015 · Journal of Dairy Science
    • "Alternative techniques to respiratory chambers are enabling scientists to collect or record gas measurements from cattle in their own production settings (e.g., grazing, free stall). Specific examples include quantifications of (1) heat production (HP) from O 2 consumption per heartbeat (Brosh et al., 1998; Aharoni et al., 2006), (2) energy expenditure using the 13 C bicarbonate technique coupled with O 2 consumption and respiratory quotient (RQ; Junghans et al., 2007; Kaufmann et al., 2011), (3) carbon emissions using tracer techniques (Stewart et al., 2008; Madsen et al., 2010), and (4) CO 2 flux (QCO 2 ) and CH 4 flux (QCH 4 ) in animal breath (Branco et al., 2015; Dorich et al., 2015; Huhtanen et al., 2015). A portable, automated, open-circuit gas quantification system (GQS; GreenFeed; C-Lock Inc., Rapid City, SD) has been used recently to obtain spot shortterm measurements of QCH 4 and QCO 2 in near realtime mode and with minimal disturbance to the natural behavior of the cow (Branco et al., 2015; Dorich et al., 2015; Huhtanen et al., 2015). "
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    ABSTRACT: Abstract Text: Real time measurements of CH4 (QCH4) and CO2 (QCO2) fluxes were used in a pilot study to estimate heat production1 (HP) and energy conversion efficiency in lactating dairy cows. Oxygen utilization (QO2) was estimated according to the respiration quotient2. Eleven multiparous and 4 primiparous lactating Holstein cows averaging 176 ± 34 DIM, 42.9 ± 6.8 kg of milk yield and 681 ± 48 kg of BW were blocked by DIM, parity, and DMI (as % of BW) and, within each block, randomly assigned to 1 of 2 treatments: restricted intake (RI) (90% DMI) or ad libitum intake (AI) according to a crossover design. Each experimental period lasted 22 d with 14 d for treatments adaptation and 8 d for data and sample collection. Diets contained (DM basis): 40% corn silage, 12% grass-legume haylage, and 48% concentrate. Spot gas measurements were taken in 5-min sampling periods from all cows using a portable automated head chamber system [GreenFeed® (GF); C-Lock Inc., Rapid City, SD] with intervals of 12 h between the 2 daily samplings. Sampling points were advanced 2 h from a day to the next to yield 14 gas samplings/cow over 7 d to account for diurnal variation in QCH4 and QCO2. Data were analyzed using the Fit Model procedure in JMP, and least square means are reported. Cows on RI converted more feed gross energy3 into milk energy4 (28.3 vs. 27.0%, SEM = 0.63; P = 0.04) and more DMI into metabolizable energy5 than AI cows (11.8 vs. 11.3 MJ/kg of DMI; SEM = 0.22 P = 0.02). Conversely, RI cows yielded more HP/kg of DMI (6.65 vs. 6.36 MJ/kg; SEM = 0.18; P = 0.04). Our results suggest that the proposed methodology has potential to identify more efficient dairy cows according to real time measurements of QCH4 and QCO2 using the GF. Equations used for estimations: 1Estimated HP MJ/cow/d = [(3.86 × QO2) + (1.2 × QCO2) – (0.518 × QCH4)] × 4.184/1000 (Brouwer, 1965) 2QO2/QCO2 = 0.95 (Madsen et al., 2010) 3Gross energy intake MJ/cow/d = [dietary CP% × DMIkg × 17 × 0.6] × 4.184 (IPCC, 2006) 4Milk energy MJ/cow/d = [(0.384 × fat%) + (0.223 × protein%) + (0.199 × lactose%) – 0.108] × milk yield kg/cow/d (AFRC, 1993) 5Metabolizable energy MJ/cow/d = HP + Milk energy ± (19.99 × kg of mobilized weight) (AFRC, 1990) Keywords: energy conversion efficiency, heat production, GreenFeed
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