What is he best known for?
The fields of study he is best known for:
Y. de Haas mainly focuses on Dairy cattle, Animal science, Somatic cell count, Streptococcus uberis and Veterinary medicine.
The Dairy cattle study combines topics in areas such as Feed conversion ratio, Residual feed intake and Statistics.
His biological study deals with issues like Selection, which deal with fields such as Biotechnology and Methane.
His work on Animal feed as part of general Biotechnology research is often related to Trait, thus linking different fields of science.
His Animal science research integrates issues from Genetic correlation and Heritability.
He conducts interdisciplinary study in the fields of Somatic cell count and Herd through his works.
His most cited work include:
- Genetic parameters for predicted methane production and potential for reducing enteric emissions through genomic selection. (137 citations)
- The effect of pathogen-specific clinical mastitis on the lactation curve for somatic cell count. (128 citations)
- Associations between pathogen-specific cases of clinical mastitis and somatic cell count patterns. (117 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Animal science, Dairy cattle, Biotechnology, Feed conversion ratio and Selection.
His Animal science research incorporates themes from Udder and Genetic correlation.
His Dairy cattle study also includes
- Residual feed intake that intertwine with fields like Single-nucleotide polymorphism,
- Agronomy, which have a strong connection to Dairy farming and Methane.
His research integrates issues of Reference population, Animal breeding and Genomic selection in his study of Biotechnology.
His work carried out in the field of Feed conversion ratio brings together such families of science as Statistics and Genetic architecture.
His Selection research is multidisciplinary, relying on both Energy balance and Longevity.
He most often published in these fields:
- Animal science (35.14%)
- Dairy cattle (35.14%)
- Biotechnology (27.03%)
What were the highlights of his more recent work (between 2017-2020)?
- Feed conversion ratio (18.02%)
- Dairy cattle (35.14%)
- Animal breeding (10.81%)
In recent papers he was focusing on the following fields of study:
Y. de Haas mostly deals with Feed conversion ratio, Dairy cattle, Animal breeding, Enteric methane and Animal science.
His research investigates the link between Feed conversion ratio and topics such as Statistics that cross with problems in Milking robot.
His research brings together the fields of Biotechnology and Animal breeding.
His study explores the link between Biotechnology and topics such as Environmental impact assessment that cross with problems in Livestock.
Y. de Haas has included themes like Ranking and Methane in his Animal science study.
His Residual feed intake research incorporates elements of Single-nucleotide polymorphism and Genetic correlation.
Between 2017 and 2020, his most popular works were:
- Genome-wide association analyses based on a multiple-trait approach for modeling feed efficiency (18 citations)
- Invited review: Determination of large-scale individual dry matter intake phenotypes in dairy cattle. (14 citations)
- Can greenhouse gases in breath be used to genetically improve feed efficiency of dairy cows (6 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Genetics
- Agriculture
His primary scientific interests are in Feed conversion ratio, Animal science, Dairy cattle, Residual feed intake and Methane emissions.
His studies in Feed conversion ratio integrate themes in fields like Statistics and Single-nucleotide polymorphism.
Y. de Haas has researched Animal science in several fields, including Genetic correlation and Greenhouse gas.
His Dairy cattle research is multidisciplinary, incorporating elements of Predictive modelling and Dry matter.
His biological study spans a wide range of topics, including SNP, Genetics, Genome-wide association study, Polymorphism and Best linear unbiased prediction.
His Methane emissions research is included under the broader classification of Methane.
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