نتایج جستجو برای: blup
تعداد نتایج: 649 فیلتر نتایج به سال:
The REML/BLUP statistics are analyses that can be used as selective criteria in the routine of maize breeding programs. The present study aims to determine the genetic potential in crosses of landrace populations applying the REML/BLUP methodology, and to identify populations for the synthesis of new populations and intrapopulation selection for family farming systems, as well as genetic consti...
First lactation production records of 7,825 Mehsana buffaloes, sired by 200 sires maintained at DudhsagarResearch and Development Association, Dudhsagar Dairy, over a period 25 years (1989-2013), wereutilised for estimation breeding value the first milk yield using BLUP - Univariate sire model andanimal WOMBAT software. The study aimed to find out optimum number daughters that maybe sufficient ...
در این پژوهش، روش برای پیشبینی فراسنجههای ناشناختۀ پنج مدل بهترین پیشبینی نااریب خطی ژنگانی (ژنومی G-BLUP) از روش بیز و نمونهگیری گیبس استفاده شد. در هر مدل از مقیاسهای متفاوتی برای ماتریس G شامل استفاده از فراوانی آللی جمعیت بنیانگذار (Gfoun)، فراوانی آللی جمعیت مرجع (Gref)، فراوانی آللی برابر با 5/0 (G05)، یک ماتریس نرمال شده با میانگین عنصرهای قطری برابر با یک (Gnorm) و یک ماتریس G وزن...
La estimación del mérito o valor genético (Breeding value en inglés) juega un papel muy importante en el Esquema de Selección de la Raza Ovina Manchega (ESROM), el cual comenzó hace quince años con el objetivo de mejorar las cifras en cuanto a la producción de la oveja manchega. En el esquema ESROM el valor genético se estima cada semestre empleando el modelo de evaluación genética BLUP. En est...
In a breeding scheme, the aim is high rates of genetic gain with limited inbreeding. A dynamic selection rule is developed that maximizes selection response in populations with overlapping generations. The rule maximizes the genetic merit of selected animals while limiting the average relationship of the population after the current round of selection. The latter is shown to limit the contribut...
The success of genomic selection depends on the potential to predict genome-assisted breeding values (GEBVs) with high accuracy over several generations without additional phenotyping after estimating marker effects. Results from both simulations and practical applications have to be evaluated for this potential, which requires linkage disequilibrium (LD) between markers and QTL. This study sho...
Genomic selection can increase genetic gain per generation through early selection. Genomic selection is expected to be particularly valuable for traits that are costly to phenotype, and expressed late in the life-cycle of long-lived species. Alternative approaches to genomic selection prediction models may perform differently for traits with distinct genetic properties. Here the performance of...
Four approaches using single-nucleotide polymorphism (SNP) information (F(infinity)-metric model, kernel regression, reproducing kernel Hilbert spaces (RKHS) regression, and a Bayesian regression) were compared with a standard procedure of genetic evaluation (E-BLUP) of sires using mortality rates in broilers as a response variable, working in a Bayesian framework. Late mortality (14-42 days of...
Genomic best linear unbiased prediction (BLUP) is a statistical method that uses relationships between individuals calculated from single-nucleotide polymorphisms (SNPs) to capture relationships at quantitative trait loci (QTL). We show that genomic BLUP exploits not only linkage disequilibrium (LD) and additive-genetic relationships, but also cosegregation to capture relationships at QTL. Simu...
Genomic selection involves computing a prediction equation from the estimated effects of a large number of DNA markers based on a limited number of genotyped animals with phenotypes. The number of observations is much smaller than the number of independent variables, and the challenge is to find methods that perform well in this context. Partial least squares regression (PLS) and sparse PLS wer...
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