Literature DB >> 19233784

Interactions of vacuum, b-phase duration, and liner compression on milk flow rates in dairy cows.

R D Bade1, D J Reinemann, M Zucali, P L Ruegg, P D Thompson.   

Abstract

Vacuum, b-phase duration, and liner compression are 3 milking machine factors that affect peak milk flow rate; however, extreme values of these factors can also have negative effects on teat tissue health. The main and interactive effects of vacuum, b-phase duration, and liner compression on peak milk flow rate were studied by independently controlling these causal variables over a wide range of settings, using a central composite experimental design (42 to 53 kPa of system vacuum, 220 to 800 ms of b-phase, and residual vacuum for massage of 16 to 30 kPa; corresponding to a liner compression of 8 to 14 kPa). The results of this study indicated that increasing the vacuum and b-phase duration always increased peak milk flow rate (no relative maximum was reached); however, the rate of increase of flow rate decreased as the vacuum and b-phase were increased. Increasing the liner compression also increased peak flow rates, with an increasing effect at greater vacuum. The interaction between vacuum and liner compression and the lack of interaction between b-phase and liner compression indicate that for a corresponding increase in peak milk flow rate, increasing the b-phase produced less teat-end tissue congestion than increasing the vacuum. The effect of milking vacuum on peak milk flow rate was smaller than that reported in previous studies, probably because of the independent adjustment of milking vacuum and liner compression used in this study. The effect of b-phase duration on peak milk flow was also smaller in this study than in previous studies, probably because of the independent adjustment of b-phase and d-phase durations used in this study.

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Year:  2009        PMID: 19233784     DOI: 10.3168/jds.2008-1180

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  5 in total

1.  The Potentialities of Machine Learning for Cow-Specific Milking: Automatically Setting Variables in Milking Machines.

Authors:  Jintao Wang; Daniela Lovarelli; Nicola Rota; Mingxia Shen; Mingzhou Lu; Marcella Guarino
Journal:  Animals (Basel)       Date:  2022-06-23       Impact factor: 3.231

2.  Milk-flow data collected routinely in an automatic milking system: an alternative to milking-time testing in the management of teat-end condition?

Authors:  Håvard Nørstebø; Amira Rachah; Gunnar Dalen; Odd Rønningen; Anne Cathrine Whist; Olav Reksen
Journal:  Acta Vet Scand       Date:  2018-01-11       Impact factor: 1.695

3.  A new standard model for milk yield in dairy cows based on udder physiology at the milking-session level.

Authors:  Patrick Gasqui; Jean-Marie Trommenschlager
Journal:  Sci Rep       Date:  2017-08-21       Impact factor: 4.379

4.  The Usability of a Pressure-Indicating Film to Measure the Teat Load Caused by a Collapsing Liner.

Authors:  Susanne Demba; Sabrina Elsholz; Christian Ammon; Sandra Rose-Meierhöfer
Journal:  Sensors (Basel)       Date:  2016-09-28       Impact factor: 3.576

5.  Vacuum Dynamics as an Alternative Method for Detection of Bimodal Milk Ejection in Dairy Cows.

Authors:  Matthias Wieland; Christina Marie Geary; Gloria Gioia; Kerry Lynn Case; Paolo Moroni; Anja Sipka
Journal:  Animals (Basel)       Date:  2021-06-23       Impact factor: 2.752

  5 in total

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