Literature DB >> 29174159

Fluctuations in milk yield are heritable and can be used as a resilience indicator to breed healthy cows.

G G Elgersma1, G de Jong2, R van der Linde2, H A Mulder3.   

Abstract

Automatic milking systems record an enormous amount of data on milk yield and the cow itself. These type of big data are expected to contain indicators for health and resilience of cows. In this study, the aim was to define and estimate heritabilities for traits related with fluctuations in daily milk yield and to estimate genetic correlations with existing functional traits, such as udder health, fertility, claw health, ketosis, and longevity. We used daily milk yield records from automatic milking systems of 67,025 lactations in the first parity from 498 herds in the Netherlands. We defined 3 traits related to the number of drops in milk yield using Student t-tests based on either a rolling average (drop rolling average) or a regression (drop regression) and the natural logarithm of the within-cow variance of milk yield (LnVar). Average milk yield was added to investigate the relationships between milk yield and these new traits. ASReml was used to estimate heritabilities, breeding values (EBV), and genetic correlations among these new traits and average milk yield. Approximate genetic correlations were calculated using correlations between EBV of the new traits and existing EBV for health and functional traits correcting for nonunity reliabilities using the Calo method. Partial genetic correlations controlling for persistency and average milk yield and relative contributions to reliability were calculated to investigate whether the new traits add new information to predict fertility, health, and longevity. Heritabilities were 0.08 for drop rolling average, 0.06 for drop regression, and 0.10 for LnVar. Approximate genetic correlations between the new traits and the existing health traits differed quite a bit, with the strongest correlations (-0.29 to -0.52) between LnVar and udder health, ketosis, persistency, and longevity. This study shows that fluctuations in daily milk yield are heritable and that the variance of milk production is best among the 3 fluctuations traits tested to predict udder health, ketosis, and longevity. Using the residual variance of milk production instead of the raw variance is expected to further improve the trait to breed healthy, resilient, and long-lasting dairy cows.
Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  big data; fluctuation; health; resilience; variance

Mesh:

Year:  2017        PMID: 29174159     DOI: 10.3168/jds.2017-13270

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


  12 in total

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Authors:  Lauren R Wottlin; Gordon E Carstens; William C Kayser; William E Pinchak; Jennifer M Thomson; Valerie Copié; Galen P O'Shea-Stone
Journal:  J Anim Sci       Date:  2020-12-22       Impact factor: 3.159

2.  Using egg production longitudinal recording to study the genetic background of resilience in purebred and crossbred laying hens.

Authors:  Nicolas Bedere; Tom V L Berghof; Katrijn Peeters; Marie-Hélène Pinard-van der Laan; Jeroen Visscher; Ingrid David; Han A Mulder
Journal:  Genet Sel Evol       Date:  2022-04-20       Impact factor: 5.100

3.  Differential haptoglobin responsiveness to a Mannheimia haemolytica challenge altered immunologic, physiologic, and behavior responses in beef steers.

Authors:  Lauren R Wottlin; Gordon E Carstens; William C Kayser; William E Pinchak; Jennifer M Thomson; Valerie Copié; Galen P O'Shea-Stone
Journal:  J Anim Sci       Date:  2021-01-01       Impact factor: 3.159

4.  Opportunities to Improve Resilience in Animal Breeding Programs.

Authors:  Tom V L Berghof; Marieke Poppe; Han A Mulder
Journal:  Front Genet       Date:  2019-01-14       Impact factor: 4.599

5.  Exploring milk shipment data for their potential for disease monitoring and for assessing resilience in dairy farms.

Authors:  Nils Fall; Anna Ohlson; Ulf Emanuelson; Ian Dohoo
Journal:  Prev Vet Med       Date:  2018-03-19       Impact factor: 2.670

6.  Body Weight Deviations as Indicator for Resilience in Layer Chickens.

Authors:  Tom V L Berghof; Henk Bovenhuis; Han A Mulder
Journal:  Front Genet       Date:  2019-12-13       Impact factor: 4.599

7.  Detection of unrecorded environmental challenges in high-frequency recorded traits, and genetic determinism of resilience to challenge, with an application on feed intake in lambs.

Authors:  Carolina Andrea Garcia-Baccino; Christel Marie-Etancelin; Flavie Tortereau; Didier Marcon; Jean-Louis Weisbecker; Andrés Legarra
Journal:  Genet Sel Evol       Date:  2021-01-06       Impact factor: 4.297

Review 8.  Breeding for disease resilience: opportunities to manage polymicrobial challenge and improve commercial performance in the pig industry.

Authors:  Xuechun Bai; Graham S Plastow
Journal:  CABI Agric Biosci       Date:  2022-01-15

Review 9.  Why breed disease-resilient livestock, and how?

Authors:  Pieter W Knap; Andrea Doeschl-Wilson
Journal:  Genet Sel Evol       Date:  2020-10-14       Impact factor: 4.297

Review 10.  Historical Evolution of Cattle Management and Herd Health of Dairy Farms in OECD Countries.

Authors:  Ivo Medeiros; Aitor Fernandez-Novo; Susana Astiz; João Simões
Journal:  Vet Sci       Date:  2022-03-09
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