نتایج جستجو برای: blup

تعداد نتایج: 649  

2003
R. Kelley Pace James P. LeSage

A conditional spatial autoregression (CAR) specifies dependence via a weight matrix. Employing a doubly stochastic weight matrix allows users to interpret the CAR prediction rule as a semiparametric prediction rule and as BLUP with smoothing in addition to other benefits. We examine standard and doubly stochastic weight matrices in the context of an illustrative data set to demonstrate feasibil...

Journal: :The Iraqi Journal of Agricultural science 2022

The study was conducted on 118 partridges (Alectoris graeca) chicks in order to find the effect of non-genetic factors and genetic evaluation live weight carcass this bird. results showed a highly significant superiority weights males over females most age stages (437.71 ± 4.40 vs 375.90 3.66 g/ bird at marketing age) daily gain (ADG) from one day (4.70 0.06 4.01 0.04 day/bird). breeding values...

2012
Satish Kumar David Chagné Marco C. A. M. Bink Richard K. Volz Claire Whitworth Charmaine Carlisle

The genome sequence of apple (Malus×domestica Borkh.) was published more than a year ago, which helped develop an 8K SNP chip to assist in implementing genomic selection (GS). In apple breeding programmes, GS can be used to obtain genomic breeding values (GEBV) for choosing next-generation parents or selections for further testing as potential commercial cultivars at a very early stage. Thus GS...

2011
Jeffrey B. Endelman

Many important traits in plant breeding are polygenic and therefore recalcitrant to traditional marker-assisted selection. Genomic selection addresses this complexity by including all markers in the prediction model. A key method for the genomic prediction of breeding values is ridge regression (RR), which is equivalent to best linear unbiased prediction (BLUP) when the genetic covariance betwe...

2017
Réka Howard Alicia L. Carriquiry William D. Beavis

An epistatic genetic architecture can have a significant impact on prediction accuracies of genomic prediction (GP) methods. Machine learning methods predict traits comprised of epistatic genetic architectures more accurately than statistical methods based on additive mixed linear models. The differences between these types of GP methods suggest a diagnostic for revealing genetic architectures ...

Journal: :Annales de Génétique et de Sélection Animale 1978

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