ICAR Technical Series no. 7 - Nitra Proc.

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Rittershaus et al.%35302520151050t startingroutine untilput on:Farm 1(Stimulationmanuel)1,32 minFarm 2(Stimulationautomatically)0,10 minFarm 3(Stimulationmanuel)1,00 minFarm 4(Stimulationmanuel)2,10 minFigure 1. Share of bimodal milk flow curves in per cent (n=1590).bimodal milk flow curves (23%). The smallest proportion of bimodal milkflow curves could be found on the farm, which manually prepared theudder and had exactly 1 minute between beginning of routine and fixingthe milking unit.The bimodal process of the milk flow curve highly significant correlateswith the time of the first contact up to fixing with r = 0.166 (Table 1). Exactlythe same negative high significant correlation exists for stimulation andto the milk flow before stimulation. No connection between the behaviorduring milking and bimodal milk flow curves could be found, however aTable 1. Correlation of bimodality with selected parameters.MilkingplaceMFbeforestimulationStimulationt untilattachingFit of theunit BehaviourPostmilkingSomaticcell countMicrobiologyBimodality -0,042** -0,076** -0,062** 0,166** -0,188** -0,026 -0,086** 0,102** 0,045**LactationStadiumoflactationMilkyieldHMF tMHG tPL tAB tBMG DMHGBimodality -0,081** 0,142** -0,182** 0,182** -0,158** -0,299** -0,058** -0,026** -0,061**ICAR Technical Series - No 771
Evaluation of milking routine by LactoCorderstrong correlation between stepping during milking and bimodality.Assertion for the fact is that animals, which are exposed to stress andtherefore step during milking, keep the milk and thus have a bimodalcurve. Bimodal curves are very strongly correlated with the parameters ofmilking. A bad beginning of milking affects thus the entire milking processnegatively. The time for the main milk flow (tMHG), the plateau phase(tPL) and phase of descent (tAB) is reduced. Also milk quantity andbimodality are high significantly correlated. Further lactation and stadiumof lactation have a high-significant influence on bimodality of the milkflow curve.The effects of the bimodality on udder health can be detected by means ofantiseptical quarter foremilk samples. Parameter for udder health is amongother things the number of cells, whereby a cow is considered as udderhealthy, if it has a cell content less than 100 000 cells/ml on all four quarters(Deutsche Veterinämedizinische Gesellschaft, 1994). A cell content between100 000 and 200 000 is already considered as health and also qualityimpairing; higher cell contents must be defined as pathological. Of theanimals, which had a one peak milk flow curve, 35% were udder healthy.If one regards against it the cows with bimodal curve due to stimulationlacking, then here the proportion of healthy animals (29%) is smaller.These results are acknowledged by the highly significant correlation(r = 0.102) of the bimodal curves and the cell numbers. For further analysisthe data were calculated over the analysis of variance. In figure 2 the effectsfrom stimulation and time to fixing are represented on the cell content ofthe milk. For this the time up to fixing was divided in classes. The smallest2,252,001,751,621,50lg SCC1,251,000,750,500,250,00Bimo0Bimo12,51Figure 2 Effects of Stimulation and time “first touch until attaching the unit” on SCC.72Conference on "Physiological and technicalaspects of machine milking"
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The designationsemployed and thepre
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The organisers of the meeting want
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Milking variables in relation to te
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Modelling of liner behaviour using
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ForewordThe second half of the part
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Rosatiorganizations. The “Lactati
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Rosatito guarantee correctness of s
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RosatiICAR also sponsors books belo
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Technical developments in Slovak co
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Technical developments in Slovak co
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Page 25 and 26: de Koning & HuijsmanThe Dutch Quali
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Page 29 and 30: de Koning & HuijsmanThe pulsation c
Page 31 and 32: de Koning & HuijsmanBalances which
Page 33 and 34: Tancin et al.Physiology of milk let
Page 35 and 36: Tancin et al.In the dairy practice
Page 37 and 38: Tancin et al.Mayer, H., D. Schams,
Page 39 and 40: Effect of machine milking on teatIn
Page 41 and 42: Effect of machine milking on teatBe
Page 43 and 44: Effect of machine milking on teatTa
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Page 47 and 48: Measurements of vacuum stabilityInt
Page 49 and 50: Measurements of vacuum stabilityTab
Page 51 and 52: Measurements of vacuum stabilityFor
Page 53 and 54: Marnet et al.Comparative study of p
Page 55 and 56: Marnet et al.production during the
Page 57 and 58: Marnet et al.prestimulation by the
Page 59 and 60: Worstorff & BilgeryEffects of liner
Page 61 and 62: Worstorff & BilgeryTable 1 summaris
Page 63 and 64: Worstorff & Bilgeryseries 40/32 kPa
Page 65 and 66: Differential staining of somatic ce
Page 67 and 68: Different diagnostic measures for m
Page 73: Evaluation of milking routine by La
Page 77 and 78: Fryc et al.The assessment parameter
Page 79 and 80: Fryc et al.p n[kPa]p n1p n2p npt st
Page 81 and 82: Fryc et al.rate. There were three s
Page 83 and 84: Milking devices disturbance on SCCm
Page 85 and 86: Milking devices disturbance on SCCL
Page 87 and 88: Milking devices disturbance on SCCT
Page 89 and 90: Turki & WinnickiMilking variables i
Page 91 and 92: Table1. Milk flow time from in indi
Page 93 and 94: Table 2. First minute milk flow, av
Page 95 and 96: Turki & WinnickiMayer H., Schams D.
Page 97 and 98: Milk recording in GermanyTable 1. E
Page 99 and 100: Milk recording in GermanyTable 3. A
Page 101 and 102: Milk recording in GermanyTable 5. M
Page 103 and 104: Main fields ofactivities of theGerm
Page 105 and 106: Influence of duration of a and c ph
Page 111 and 112: Nosal & BilgeryVibrations and vacuu
Page 113 and 114: Nosal & BilgerykPa45.645.445.245.04
Page 115 and 116: Nosal & BilgeryIn case of problems
Page 117 and 118: Testing of vacuum during milkingEva
Page 119 and 120: Testing of vacuum during milkingthe
Page 121 and 122: Ryšánek et al.Vacuum fluctuation
Page 123 and 124: Ryšánek et al.Teat injuries were
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Ryšánek et al.Particular attentio
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de KoningAutomatic milking:Chances
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de Koningfor some time after the mi
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de KoningMilk quality is without do
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de Koningwhen the bulk tank is empt
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de KoningLand, A. van ‘t et al, 2
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Characterising the farms equipped w
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Designing optimal robotic milking b
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ArtmannThe effects of automatic mil
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ArtmannData was collected on the ma
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ArtmannThe differences of the co-ef
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BarthEvaluation of somatic cell cou
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BarthTable 1. Determined and real m
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Barthyield is often a side effect o
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Milking parameters in modified milk
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Pallas & WendtThe development of ud
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Pallas & WendtSCC (x 1,000) / ml250
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Pallas & WendtTrilk, J. und Münch,
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Udder health and milk low profilesA
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Udder health and milk low profilesD
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AMS in Czech RepublicThis farm size
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AMS in Czech RepublicTable 1. Effec
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AMS in Czech RepublicFigure 1. Stab
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BruckmaierSpecific aspects of milk
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Bruckmaiertowards the end of lactat
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BruckmaierBruckmaier, R.M., D. Scha
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Teat callosity and mastitisResultsT
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de Koning et al.Milking characteris
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de Koning et al.Table 1. Statistica
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Influence of ageing on linersThe re
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Neijenhuis & HogeveenMilking interv
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Knízková et al.Effect of old and
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Knízková et al.Thermograms of the
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Knízková et al.Kunc, P., Knízkov
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Postmilking teat disinfectingIntrod
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Postmilking teat disinfectingNDT an
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Los & MaškováTeatcup hardness aft
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Los & MaškováIt follows from the
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Trends in milking equipmentThe fina
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Olechnowicz & TurkiMilking and milk
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Table 2. Milk components and somati
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Lipinski et al.Effect of some selec
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Lipinski et al.Milk hygiene quality
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Lipinski et al.1. The technical and
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Effect of two milking systems on te
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Effect of two milking systems on te
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Milk quality and mastitis monitorin
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Nitra in ICAR interlaboratory studi
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Botto et al.Effect of ultrasound in
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Báder et al.Change of udder confor
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Báder et al.6050%4030201.scor.2.sc
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Luger et al.Effect of inclination a
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Luger et al.There is no difference
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Harty et al.Modelling of liner beha
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Harty et al.A solid plane was const
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Provolo & SangiorgiUsing daily data
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Provolo & SangiorgiFigure 3. Averag
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Provolo & SangiorgiFigure 7. Cow no
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Provolo & Sangiorgistandardisation
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Cognome/iInhibition of oxytocin rel
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Tancin et al.Milk flow patterns: in
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Szlachta & AleksanderThe influence
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Szlachta & Aleksanderforces in the
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Szlachta & Aleksanderpressure diffe
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List of participantsŠtefan BodoSPU
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List of participantsMarian GregušI
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List of participantsMarija KlopcicD
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List of participantsŠtefan MihinaV
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List of participantsEduard Pravnans
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List of participantsJozef Tonhauser
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ICAR Technical Series no. 7 - Nitra Proc.

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