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Ortiz X.A.,University of Arizona | Smith J.F.,University of Arizona | Rojano F.,University of Arizona | Choi C.Y.,University of Wisconsin - Madison | And 5 more authors.
Journal of Dairy Science | Year: 2015

Cooling systems used to reduce heat stress in dairy operations require high energy, water usage, or both. Steady increases in electricity costs and reduction of water availability and an increase in water usage regulations require evaluation of passive cooling systems to cool cows and reduce use of water and electricity. A study was conducted to evaluate the use of heat exchangers buried 25. cm below the surface as components in a conductive system for cooling cows. Six cows were housed in environmentally controlled rooms with tie-stall beds, which were equipped with a heat exchanger and filled with 25. cm of either sand or dried manure. Beds were connected to supply and return lines and individually controlled. Two beds (one per each kind of bedding material) constituted a control group (water off), and the other 4 (2 sand and 2 dried manure) used water at 7°C passing through the heat exchangers (water on). The experiment was divided in 2 periods of 40. d, and each period involved 3 repetitions of 3 different climates (hot and dry, thermo neutral, and hot and humid). Each cow was randomly assigned to a different treatment after each repetition was over. Sand bedding remained cooler than dried manure bedding in all environments and at all levels of cooling (water on or off). Bed temperatures were lower and heat flux higher during the bed treatment with sand and water on. We also detected a reduction in core body temperatures, respiration rates, rectal temperatures, and skin temperatures of those cows during the sand and water on treatment. Feed intake and milk yield numerically increased during the bed treatment with sand and water on for all climates. No major changes were observed in the lying time of cows or the composition of the milk produced. We conclude that use of heat exchangers is a viable adjunct to systems that employ fans, misters, and evaporative cooling methods to mitigate effects of heat stress on dairy cows. Sand was superior to dried manure as a bedding material in combination with heat exchangers. © 2015 American Dairy Science Association. Source


Watters R.D.,Cornell University | Schuring N.,GEA Farm Technologies | Erb H.N.,Section of Epidemiology | Schukken Y.H.,Cornell University | Galton D.M.,Cornell University
Journal of Dairy Science | Year: 2012

Premilking udder preparation (including forestripping and duration of lag time-the time between first tactile stimulation and attachment of milking unit) might influence milking measures such as milking unit on-time, incidence of bimodality, and milk flow rates in Holstein cows milked 3 times daily. Holstein cows (n=786) from an 1,800-cow commercial dairy herd were enrolled under a restricted randomized design to determine the effect of 9 different premilking routines. Lag times were 0, 60, 90, 120, and 240. s and included forestripping or no forestripping for a total of 9 treatments (no forestripping for 0 lag time); the study was conducted from February to November 2008. All cow-treatment combinations were compared with the control: predipping plus forestripping and drying with 90. s of lag time. Cows were initially assigned to 1 of 3 treatments for a period of 7. d and upon completion of the first 7-d period were reassigned to a different treatment until all treatments had been completed. From one treatment period to the next, cows had to switch stimulation method with no restriction on lag time. Cows did not receive all treatments during the duration of the trial. Early- to mid-lactation cows (EML; 17-167 DIM) and late-lactation cows (LL; 174-428 DIM) were housed in 2 different pens. Milk yield was significantly different between dip. +. forestrip and dip. +. dry for 2 of the treatments for EML cows compared with dip. +. forestrip and 90. s of lag-time (DF90); however, this was not thought to be due to treatment because the significant lag times were very different (60 and 240. s) and neither was an extreme value. Milk yield did not differ with treatment for the LL cows. Milking unit on-time did not differ when comparing all treatments for EML with treatment DF90; however, an increase in milking unit on-time occurred when lag time was 60. s or less for LL cows. The highest incidence of bimodal milk curves was when lag time=0 and this was independent of stage of lactation; a lag time of 240. s had the second-highest incidence of bimodal milk curves for EML and LL cows. Milk harvested in the first 2. min was lower for lag times of 0 and 240. s when compared with DF90. Increasing the lag time for all cows appeared to improve overall milking time efficiency (although lag time had no effect on EML cows). © 2012 American Dairy Science Association. Source


Watters R.D.,Cornell University | Bruckmaier R.M.,University of Bern | Crawford H.M.,GEA Farm Technologies | Schuring N.,GEA Farm Technologies | And 2 more authors.
Journal of Dairy Science | Year: 2015

Prestimulation administered to a cow before attachment of the milking unit has historically been performed manually. Development of innovative milking technology has allowed manual stimulation to be replaced by mechanical forms of stimulation. Holstein cows (n=30) were enrolled in a crossover design to determine the effect of manual stimulation (forestripping and drying) and high-vibration pulsation on oxytocin profiles, milk yield, milk flow rates, incidence of delayed milk ejection causing bimodal milk flow curves, and residual milk in Holstein cows milked 3 times daily (3×). All cows were subjected to all treatments. Cows received manual (forestripping and drying) or mechanical (high-vibration pulsation) stimulation along with lag times of 0, 30, or 90 s for 21 consecutive milkings. Forestripping involved the manual removal of 2 streams of milk from each teat and drying of the teats. High-vibration pulsation involved increasing the pulsation cycles from 60 to 300 pulses/min and reducing the vacuum in the pulsation chamber to 20 kPa. The 5 treatments were (1) immediate attachment of the milking machine under normal pulsation (T0); (2) dip plus forestrip and drying with 30-s lag time (FD30); (3) dip plus forestrip and drying with 90-s lag time (FD90); (4) high-vibration pulsation for 30 s (HV30); and (5) high-vibration pulsation for 90 s (HV90). Milk yield per milking averaged 14.0kg and was significantly different among treatments; however, the maximum difference detected among treatments was 0.8kg/milking. Milking unit on-time, which represents the time when the milking unit is under normal pulsation and harvesting milk (excluding the high-vibration pulsation time of 30 or 90 s), was shortest (245 s) for cows subjected to 90 s of high-vibration pulsation (HV90) and ranged from 256 to 261 s for all other treatments. Milk harvest may have begun during high-vibration pulsation; however, only 0.13 and 0.32kg of milk was harvested during high-vibration pulsation for HV30 and HV90, respectively. The incidence of bimodal milk curves was lowest for FD90 (7%) and highest for T0 (21%). The somatic cell count was <72×103 cells/mL for all treatments. Residual milk obtained by giving 10 IU of oxytocin in the jugular vein followed by 2min of milking unit attachment represented 12 to 14% of the total milk and did not differ among treatments. Endogenous oxytocin profiles peaked between 12.4 and 18.3 pg/mL for all treatments, and the peak occurred sooner in manually stimulated cows; however, we detected no difference in oxytocin concentration beyond 2min after milking unit attachment. High-vibration pulsation elicited a similar oxytocin release when taking the start time of stimulation from manual stimulation or high vibration into consideration. Forestripping for visual observation of milk combined with the use of high-vibration stimulation may reduce variation in the milking routine. A predetermined lag time with minimal variation may be achieved via the time spent in high-vibration stimulation instead of a lag period dictated by milking personnel. © 2015 American Dairy Science Association. Source


Weber A.,University of Kiel | Salau J.,University of Kiel | Haas J.H.,University of Kiel | Junge W.,University of Kiel | And 7 more authors.
Livestock Science | Year: 2014

Increasing milk production per cow over the last decades has led to a more intense negative energy balance and extended the duration of body fat mobilization. Management of body condition requires that body condition scores be evaluated on a visual basis. A more objective approach is the measurement of the backfat thickness (BFT) using an ultrasound device. Metering precision of 1. mm enables the recognition of even slight changes in the subcutaneous fat thickness. Because both methods are time consuming in large dairy herds, automating body condition[U+05F3]s routine evaluation is of rising concern. This study investigated whether traits of the animals[U+05F3] rear area extracted from Time-of-Flight camera recordings might be useful indicators of BFT. Furthermore, characteristics of BFT within and across different lactation stages were analyzed. Data recording was performed on the dairy research farm Karkendamm of the Institute of Animal Breeding and Husbandry of the University of Kiel (Germany) from July 2011 to May 2012. BFT measures (n=2931) and two measures (n=1779 and n=1848) obtained from Time-of-Flight recordings from 96 primiparous and multiparous Holstein-Friesian dairy cows were analyzed using seven different linear (mixed) models. BFT estimation using the cow as random or fixed effect, lactation week and observation month as fixed effects, and a linear regression on the two Time-of-Flight measurements has been promising. The correlation among observed values and estimator was 0.96. Repeatability of BFT within each of the three lactation stages was large and ranged from 0.80 to 0.89. Correlations of cow effects among lactation stages were also high and range from 0.65 between first and third lactation stage to 0.89 between second and third lactation stage. © 2014 Elsevier B.V. Source

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