Literature DB >> 26898275

Factors associated with increased milk production for automatic milking systems.

Marlène Tremblay1, Justin P Hess2, Brock M Christenson2, Kolby K McIntyre2, Ben Smink3, Arjen J van der Kamp4, Lisanne G de Jong4, Dörte Döpfer2.   

Abstract

Automatic milking systems (AMS) are increasingly popular throughout the world. Our objective was to analyze 635 North American dairy farms with AMS for (risk) factors associated with increased milk production per cow per day and milk production per robot per day. We used multivariable generalized mixed linear regressions, which identified several significant risk factors and interactions of risk factors associated with milk production. Free traffic was associated with increased production per cow and per robot per day compared with forced systems, and the presence of a single robot per pen was associated with decreased production per robot per day compared with pens using 2 robots. Retrofitted farms had significantly less production in the first 4 yr since installation compared with production after 4 yr of installation. In contrast, newly built farms did not see a significant change in production over time since installation. Overall, retrofitted farms did not produce significantly more or less milk than newly constructed farms. Detailed knowledge of factors associated with increased production of AMS will help guide future recommendations to producers looking to transition to an AMS and maximize their production.
Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  automatic milking system; benchmark; milk production; number of robots per pen; traffic type

Mesh:

Year:  2016        PMID: 26898275     DOI: 10.3168/jds.2015-10152

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


  1 in total

1.  Forecasting Milking Efficiency of Dairy Cows Milked in an Automatic Milking System Using the Decision Tree Technique.

Authors:  Joanna Aerts; Magdalena Kolenda; Dariusz Piwczyński; Beata Sitkowska; Hasan Önder
Journal:  Animals (Basel)       Date:  2022-04-16       Impact factor: 2.752

  1 in total

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