Literature DB >> 22032361

Covariance among milking frequency, milk yield, and milk composition from automatically milked cows.

P Løvendahl1, M G G Chagunda.   

Abstract

Automatic milking systems allow cows voluntary access to milking and concentrates within set limits. This leads to large variation in milking intervals, both within and between cows, which further affects yield per milking and composition of milk. This study aimed to describe the degree to which differences in milking interval were attributable to individual cows, and how this correlated to individual differences in yield and composition of milk throughout lactation. Data from 288,366 milkings from 664 cow-lactations were used, of which 229,020 milkings had milk composition results. Cows were Holsteins, Red Danes, and Jerseys in parities 1, 2, and 3. Data were analyzed using a linear mixed model, with cow-lactation as a random effect and assuming heterogeneous residual variance over the lactation. Cow-lactation variance was fitted using linear spline functions with 5 knot-points. Residual variance was generally greatest in early lactation and declined thereafter. Accordingly, animal-related variance tended to increase with progression of lactation. Milking frequency (the reverse of milking interval) was found to be moderately repeatable throughout lactation. Daily milk yield expressed per milking was found to be highly repeatable in all breeds, with the highest values occurring by the end of lactation. Fat percentage had only moderate repeatability in early to mid lactation but increased toward the end of lactation. Individual level correlations showed that cows with higher milking frequency also had greater yields, but had lower fat percentage. Correlations were slightly weaker in very early lactation than in the remaining parts of lactation. We concluded that individual differences exist among cows milked automatically. Cows with higher yields are milked more often and have lower fat content in their milk.
Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 22032361     DOI: 10.3168/jds.2010-3589

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


  3 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

2.  Comparison of the fit of automatic milking system and test-day records with the use of lactation curves.

Authors:  B Sitkowska; M Kolenda; D Piwczyski
Journal:  Asian-Australas J Anim Sci       Date:  2019-07-01       Impact factor: 2.509

3.  Genetic Parameters Estimation of Milking Traits in Polish Holstein-Friesians Based on Automatic Milking System Data.

Authors:  Joanna Aerts; Dariusz Piwczyński; Heydar Ghiasi; Beata Sitkowska; Magdalena Kolenda; Hasan Önder
Journal:  Animals (Basel)       Date:  2021-06-29       Impact factor: 2.752

  3 in total

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