World's Best Scientists 2026 revealed!
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Animal Science and Veterinary
USA
2023

D-Index & Metrics

Animal Science and Veterinary

D-Index
69
Citations
14357
World Ranking
188
National Ranking
58

Research.com Recognitions

  • 2023 - Research.com Animal Science and Veterinary in United States Leader Award
  • 2010 - J. L. Lush Award in Animal Breeding, American Dairy Science Association
  • 2003 - Cargill Animal Nutrition Young Scientist Award, American Dairy Science Association

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Genetics
  • Gene

Kent A. Weigel mainly investigates Dairy cattle, Genetics, Herd, Animal science and Selection. His biological study spans a wide range of topics, including Sperm, Milking, Culling and Biotechnology. His studies deal with areas such as Regression analysis and Statistics as well as Genetics.

His studies in Herd integrate themes in fields like Heritability, Ice calving and Sire. His Sire research includes elements of Veterinary medicine and Progeny testing. His study in Animal science is interdisciplinary in nature, drawing from both Fertility, Artificial insemination, Standard error, Pregnancy rate and Insemination.

His most cited work include:

  • Predicting Quantitative Traits With Regression Models for Dense Molecular Markers and Pedigree (412 citations)
  • Genomic Prediction of Breeding Values when Modeling Genotype × Environment Interaction using Pedigree and Dense Molecular Markers (306 citations)
  • Semi-parametric genomic-enabled prediction of genetic values using reproducing kernel Hilbert spaces methods (204 citations)

What are the main themes of his work throughout his whole career to date?

Kent A. Weigel mainly focuses on Statistics, Dairy cattle, Animal science, Sire and Genetics. Kent A. Weigel interconnects Selection and Econometrics in the investigation of issues within Statistics. Kent A. Weigel has researched Dairy cattle in several fields, including Culling, Herd, Biotechnology, Breed and Algorithm.

The various areas that Kent A. Weigel examines in his Herd study include Milking, Milk yield and Gene–environment interaction. His studies deal with areas such as Feed conversion ratio, Residual feed intake and Ice calving, Lactation as well as Animal science. His Sire study combines topics from a wide range of disciplines, such as Fertility, Progeny testing and Heritability.

He most often published in these fields:

  • Statistics (35.45%)
  • Dairy cattle (35.00%)
  • Animal science (28.64%)

What were the highlights of his more recent work (between 2014-2021)?

  • Dairy cattle (35.00%)
  • Animal science (28.64%)
  • Residual feed intake (10.45%)

In recent papers he was focusing on the following fields of study:

His primary areas of investigation include Dairy cattle, Animal science, Residual feed intake, Feed conversion ratio and Biotechnology. He interconnects Statistics, Genome, Selection and Genotype in the investigation of issues within Dairy cattle. His Selection study incorporates themes from Quantitative genetics and Linear model.

His Animal science research is multidisciplinary, relying on both Genomic selection, Ice calving, Lactation and Heritability. His Heritability research includes themes of Single-nucleotide polymorphism and Genetic correlation. His work is dedicated to discovering how Residual feed intake, Genetics are connected with Covariate and other disciplines.

Between 2014 and 2021, his most popular works were:

  • Harnessing the genetics of the modern dairy cow to continue improvements in feed efficiency (65 citations)
  • Heterogeneity in genetic and nongenetic variation and energy sink relationships for residual feed intake across research stations and countries. (56 citations)
  • Genomic prediction of dry matter intake in dairy cattle from an international data set consisting of research herds in Europe, North America, and Australasia (42 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Genetics
  • Gene

His primary areas of study are Dairy cattle, Residual feed intake, Feed conversion ratio, Heritability and Animal science. His studies in Dairy cattle integrate themes in fields like Population genetics, Quantitative genetics, Biotechnology, Linear model and Selection. Residual feed intake and Genetics are commonly linked in his work.

His research integrates issues of Regression analysis, Machine learning and Artificial intelligence in his study of Genetics. His Heritability research incorporates elements of Single-nucleotide polymorphism, Genotype and Econometrics. The Animal science study combines topics in areas such as Ice calving and Lactation.

Best Publications

  • Predicting Quantitative Traits With Regression Models for Dense Molecular Markers and Pedigree

    Gustavo de los Campos;Hugo Naya;Daniel Gianola;José Crossa

  • Genomic Prediction of Breeding Values when Modeling Genotype × Environment Interaction using Pedigree and Dense Molecular Markers

    Juan Burgueño;Gustavo de los Campos;Kent Weigel;José Crossa

  • Semi-parametric genomic-enabled prediction of genetic values using reproducing kernel Hilbert spaces methods

    Gustavo De Los Campos;Daniel Gianola;Guilherme J. M. Rosa;Kent A. Weigel

  • Survey of management practices on reproductive performance of dairy cattle on large US commercial farms.

    D.Z. Caraviello;K.A. Weigel;P.M. Fricke;M.C. Wiltbank

  • Genomic evaluations with many more genotypes

    Paul M VanRaden;Jeffrey R O'Connell;George R Wiggans;Kent A Weigel

  • Genetic Selection for Health Traits Using Producer-Recorded Data. I. Incidence Rates, Heritability Estimates, and Sire Breeding Values

    N.R. Zwald;K.A. Weigel;Y.M. Chang;R.D. Welper

  • Evaluation of inbreeding depression in Holstein cattle using whole-genome SNP markers and alternative measures of genomic inbreeding

    D.W. Bjelland;K.A. Weigel;N. Vukasinovic;J.D. Nkrumah

  • Predicting complex quantitative traits with Bayesian neural networks: a case study with Jersey cows and wheat

    Daniel Gianola;Hayrettin Okut;Kent A Weigel;Guilherme Jm Rosa

  • Controlling Inbreeding in Modern Breeding Programs

    K.A. Weigel

  • Fertility of Dairy Cows after Resynchronization of Ovulation at Three Intervals Following First Timed Insemination

    P.M. Fricke;D.Z. Caraviello;K.A. Weigel;M.L. Welle

  • Harnessing the genetics of the modern dairy cow to continue improvements in feed efficiency

    M.J. VandeHaar;L.E. Armentano;K. Weigel;D.M. Spurlock

  • Exploring the Role of Sexed Semen in Dairy Production Systems

    K.A. Weigel

  • Machine Learning Classification Procedure for Selecting SNPs in Genomic Selection : Application to Early Mortality in Broilers

    N. Long;D. Gianola;G.J.M. Rosa;K.A. Weigel

  • Applied animal genomics: results from the field.

    Alison L. Van Eenennaam;Kent A. Weigel;Amy E. Young;Matthew A. Cleveland

  • Investigation of factors affecting voluntary and involuntary culling in expanding dairy herds in Wisconsin using survival analysis.

    K.A. Weigel;R.W. Palmer;D.Z. Caraviello

  • Genetic Selection for Health Traits Using Producer-Recorded Data. II. Genetic Correlations, Disease Probabilities, and Relationships with Existing Traits

    N.R. Zwald;K.A. Weigel;Y.M. Chang;R.D. Welper

  • Predictive ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers.

    K.A. Weigel;G. de los Campos;O. González-Recio;H. Naya

  • International genetic evaluations for feed intake in dairy cattle through the collation of data from multiple sources

    Donagh P. Berry;M.P. Coffey;J.E. Pryce;Y. De Haas

  • Genomic selection in dairy cattle: Integration of DNA testing into breeding programs

    Jonathan M. Schefers;Kent A. Weigel

  • Identification of Factors That Cause Genotype by Environment Interaction Between Herds of Holstein Cattle in Seventeen Countries

    N.R. Zwald;K.A. Weigel;W.F. Fikse;R. Rekaya

  • Technical note: an R package for fitting generalized linear mixed models in animal breeding.

    A. I. Vazquez;D. M. Bates;G. J. M. Rosa;D. Gianola

  • Prediction of insemination outcomes in Holstein dairy cattle using alternative machine learning algorithms.

    Saleh Shahinfar;David Page;Jerry Guenther;Victor Cabrera

  • Genetic parameters for reproductive traits of Holstein cattle in California and Minnesota.

    K.A. Weigel;R. Rekaya

  • Prospects for improving reproductive performance through genetic selection.

    Kent A. Weigel

  • Analysis of reproductive performance of lactating cows on large dairy farms using machine learning algorithms.

    D.Z. Caraviello;K.A. Weigel;M. Craven;D. Gianola

  • Indirect Prediction of Herd Life in Guernsey Dairy Cattle

    J. Cruickshank;K.A. Weigel;M.R. Dentine;B.W. Kirkpatrick

  • A multiple-trait herd cluster model for international dairy sire evaluation.

    K.A. Weigel;R. Rekaya

  • Assessment of the Impact of Somatic Cell Count on Functional Longevity in Holstein and Jersey Cattle Using Survival Analysis Methodology

    D.Z. Caraviello;K.A. Weigel;G.E. Shook;P.L. Ruegg

Frequent Co-Authors

Daniel Gianola
Daniel Gianola University of Wisconsin–Madison
Guilherme J. M. Rosa
Guilherme J. M. Rosa University of Wisconsin–Madison
Louis E. Armentano
Louis E. Armentano University of Wisconsin–Madison
M.J. VandeHaar
M.J. VandeHaar Michigan State University
Y. de Haas
Y. de Haas Wageningen University & Research
Robert J. Tempelman
Robert J. Tempelman Michigan State University
Roel F. Veerkamp
Roel F. Veerkamp Wageningen University & Research
Mike Coffey
Mike Coffey Scotland's Rural College
C.R. Staples
C.R. Staples University of Florida
Erin E. Connor
Erin E. Connor University of Delaware

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Related Online Degrees & Career Pathways

For students interested in Animal Science and Veterinary studies, exploring related online degrees can open diverse career opportunities. For instance, if you're drawn to the counseling aspect of animal care or animal behavior, consider advanced options such as online doctoral programs in counseling. These can complement your animal science background and lead to specialized roles in therapy and rehabilitation.

Career-wise, the field offers many well-paying options. To learn more about jobs with animals that pay well, it’s worth investigating roles beyond traditional veterinary work, such as wildlife management, animal nutrition, or zoological sciences.

Additionally, understanding leadership and health-focused roles can enhance your career prospects. For example, if you're considering managing sports programs related to animals or animal therapy, exploring what an athletic director does can provide valuable insights into organizational and managerial skills.

Lastly, coupling your animal science credentials with human health expertise is increasingly popular. You might want to study exercise science online to broaden your understanding of physical health and rehabilitation, which can be relevant for animal-assisted therapy or performance improvement roles.

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