Livestock Breeding in the Age of Digital Agriculture

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Animal Genetics and Genomics".

Deadline for manuscript submissions: closed (15 December 2021) | Viewed by 3957

Special Issue Editor

Centre for Genetic Improvement of Livestock (CGIL), Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
Interests: animal phenomics; bioinformatics; computational biology; comparative genomics; machine learning; optimization algorithms; biological data visualization

Special Issue Information

Dear Colleagues,

In an era of massive information digitization, modern farming technologies and animal breeding systems produce massive amounts of data due, in part, to the advent and ever-reducing costs of genotyping and sequencing technologies. High-performance computing approaches, efficient data acquisition, warehousing, and analytics combined with super-fast data transfer technologies are in development. Data mining algorithms, statistical machine learning, and efficient mathematical optimization techniques for large matrix operations are currently developed to face the current challenges related to constructing genetic evaluation models based on genotypic, phenotypic, and sensor-based information from millions of animals and their farming environments. This Special Issue will consider how livestock breeding computational approaches have adapted to face these challenges, how such approaches are applied to current breeding problems and how they attempt to predict and address future trends.

Dr. Dan Tulpan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Animals is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • livestock
  • breeding
  • genomics
  • production systems
  • animal models
  • production systems

Published Papers (1 paper)

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Research

11 pages, 266 KiB  
Article
Genetic Parameters for Age at First Calving and First Calving Interval of Beef Cattle
by Michaela Brzáková, Jindřich Čítek, Alena Svitáková, Zdeňka Veselá and Luboš Vostrý
Animals 2020, 10(11), 2122; https://doi.org/10.3390/ani10112122 - 16 Nov 2020
Cited by 12 | Viewed by 3237
Abstract
The objective of this study was to estimate genetic parameters for age at first calving (AFC) and first calving interval (FCI) for the entire beef cattle population and separately for the Charolais (CH) and Aberdeen Angus (AA) breeds in the Czech Republic. The [...] Read more.
The objective of this study was to estimate genetic parameters for age at first calving (AFC) and first calving interval (FCI) for the entire beef cattle population and separately for the Charolais (CH) and Aberdeen Angus (AA) breeds in the Czech Republic. The database of performance testing between the years 1991 and 2019 was used. The total number of cows was 83,788 from 11 breeds. After editing, the data set contained 33,533 cows, including 9321 and 4419 CH and AA cows, respectively. The relationship matrix included 85,842 animals for the entire beef population and 24,248 and 11,406 animals for the CH and AA breeds, respectively. A multibreed multitrait animal model was applied. The estimated heritability was low to moderate. Genetic correlations between AFC and FCI varied depending on the breeds from positive to negative. Differences between variance components suggest that differences between breeds should be considered before selection and breeding strategy should be developed within a breed. Full article
(This article belongs to the Special Issue Livestock Breeding in the Age of Digital Agriculture)
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