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

Joanna AertsDariusz PiwczyńskiHeydar GhiasiBeata SitskowskaMagdalena KolendaHasan Önder
Published in: Animals : an open access journal from MDPI (2021)
The automatic milking system (AMS) provides a large amount of information characterizing the course of each milking cow, which is not available in the conventional system. The aim of our study was to estimate heritability and genetic correlations for milk yield (MY), milking frequency (MF), and speed (MS) for 1713 Polish Holstein-Friesian primiparous cows milked in barns with an AMS. Daily heritability indicators estimated using second-order Legendre polynomials and Random Regression Models showed high variation during lactation, ranging 0.131-0.345 for MY, 0.153-0.322 for MF, and 0.336-0.493 for MS. The rates of genetic correlation between traits ranged: 0.561-0.929 for MY-MF, (-0.255)-0.090 for MF-MS, (-0.174)-0.020 for MY-MS. It is possible to carry out effective selection for milking speed, which provides an opportunity to increase the number of cows per milking robot, and thus increase the profitability of production in the herd. The results proved that selection for milk yield and daily milking frequency is also feasible. The research showed a high, positive genetic correlation between milking frequency and milk yield, which allows us to conclude that preferring breeding cows with a natural tendency to frequent visits to the milking robot should indirectly improve the genetic basis of milking.
Keyphrases
  • genome wide
  • mass spectrometry
  • multiple sclerosis
  • ms ms
  • dairy cows
  • machine learning
  • dna methylation
  • healthcare
  • heat stress
  • gene expression
  • electronic health record
  • preterm birth
  • low birth weight