What is he best known for?
The fields of study he is best known for:
Oscar González-Recio spends much of his time researching Fertility, Animal science, Dairy cattle, Machine learning and Artificial intelligence.
His biological study spans a wide range of topics, including Genetic correlation, Artificial insemination, Pregnancy rate, Genetic gain and Insemination.
Oscar González-Recio interconnects Biotechnology, Selection and Heritability in the investigation of issues within Genetic correlation.
His Animal science study incorporates themes from Pregnancy, Lactation, Internal medicine and Endocrinology.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in SNP and Single-nucleotide polymorphism.
In his research, Regression and Regression analysis is intimately related to Cross-validation, which falls under the overarching field of Random forest.
His most cited work include:
- Inbreeding depression on female fertility and calving ease in Spanish dairy cattle. (110 citations)
- Predictive ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers. (103 citations)
- Nonparametric Methods for Incorporating Genomic Information Into Genetic Evaluations: An Application to Mortality in Broilers (100 citations)
What are the main themes of his work throughout his whole career to date?
Oscar González-Recio mostly deals with Animal science, Genetics, Heritability, Dairy cattle and Selection.
The study incorporates disciplines such as Fertility, Biotechnology, Genetic correlation and Ice calving in addition to Animal science.
His work focuses on many connections between Genetics and other disciplines, such as Statistics, that overlap with his field of interest in Best linear unbiased prediction.
His studies in Heritability integrate themes in fields like Epistasis, Sire and Somatic cell count.
His work deals with themes such as Internal medicine and Endocrinology, which intersect with Dairy cattle.
His research in Regression tackles topics such as Regression analysis which are related to areas like Random forest.
He most often published in these fields:
- Animal science (43.96%)
- Genetics (34.07%)
- Heritability (32.97%)
What were the highlights of his more recent work (between 2018-2021)?
- Animal science (43.96%)
- Metagenomics (7.69%)
- Heritability (32.97%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Animal science, Metagenomics, Heritability, Dairy cattle and Microbiome.
His Animal science research includes themes of Methane emissions, Methane and Ice calving, Lactation.
The various areas that Oscar González-Recio examines in his Lactation study include Breed, Herd, Prevotellaceae and Dry matter.
The concepts of his Metagenomics study are interwoven with issues in Biotechnology, Food science, Animal feed, Firmicutes and Methanobacteria.
Oscar González-Recio has researched Heritability in several fields, including Fertility, Genetic correlation, Spearman's rank correlation coefficient, Statistics and Selection.
Oscar González-Recio has included themes like Carbon tax, Greenhouse gas, Somatic cell count, Genetic gain and Selective breeding in his Dairy cattle study.
Between 2018 and 2021, his most popular works were:
- Whole rumen metagenome sequencing allows classifying and predicting feed efficiency and intake levels in cattle (50 citations)
- Changes in the rumen and colon microbiota and effects of live yeast dietary supplementation during the transition from the dry period to lactation of dairy cows (18 citations)
- Mitigation of greenhouse gases in dairy cattle via genetic selection: 2. Incorporating methane emissions into the breeding goal (6 citations)
In his most recent research, the most cited papers focused on:
The scientist’s investigation covers issues in Animal science, Metagenomics, Methane, Genetic selection and Dairy cattle.
His work carried out in the field of Animal science brings together such families of science as Ice calving and Lactation.
His studies deal with areas such as Food science, Animal feed, Firmicutes, Methanobrevibacter and Methanobacteria as well as Metagenomics.
His Methane research is multidisciplinary, relying on both Repeatability, Concordance correlation coefficient and Non invasive.
His Genetic selection research covers fields of interest such as Methane measurement, Carbon tax, Selective breeding, Genetic gain and Greenhouse gas.
His Dairy cattle research incorporates elements of Fibrobacteres, Genetic correlation, Neocallimastix and Heritability.
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