نتایج جستجو برای: additive effects

تعداد نتایج: 1596227  

Journal: Desert 2018
A.R. Kiani F. Ghanbari M.R. Abdollahi S.S. Moosavi,

     Improved drought-tolerant maize hybrids would significantly reduce water consumption and increase yield in arid environments. Our knowledge about genetic parameters is very essential before starting a successful breeding program. The present research was carried out throughout three successive years between 2013-15 to reveal the pattern of inheritance in yield, yield-components and related...

A. Ayatollahi Mehrgardi, A. Sheikhy A.K. Esmailizadeh M. Assadi Foozi M. Momen

A simulation study was conducted to address the issue of how purely additive (simple) genetic architecture might impact on the efficacy of parametric and non-parametric genomic prediction methods. For this purpose, we simulated a trait with narrow sense heritability h2= 0.3, with only additive genetic effects for 300 loci in order to compare the predictive ability of 14 more practically used ge...

2015
Katarzyna Rzewuska Tomasz Strabel

The aim of this research was to estimate the influence of environmental factors, such as air temperature and milk production, on reproduction traits of primiparous Polish Holstein-Friesian cows. The following reproduction traits were considered: interval from calving to first insemination, interval from first to last insemination, interval from calving to conception, number of inseminations per...

2012
David Card Jörg Heining Patrick Kline

We study the role of establishment-specific wage premiums in generating recent increases in West German wage inequality. Models with additive fixed effects for workers and establishments are fit in four distinct time intervals spanning the period 1985-2009. Unlike standard wage models, specifications with both worker and plant-level heterogeneity components can explain the vast majority of the ...

2003
J. A. Arango L. V. Cundiff L. D. Van Vleck Roman L. Hruska

Breed differences for weight (CW), height (CH), and condition score (CS) were estimated from records (n = 12,188) of 2to 6-yr-old cows (n = 744) from Cycle IV of the U.S. Meat Animal Research Center’s Germplasm Evaluation (GPE) Program. Cows were produced from mating Angus and Hereford dams to Angus, Hereford, Charolais, Shorthorn, Galloway, Longhorn, Nellore, Piedmontese, and Salers sires. Sam...

2003
Karin Meyer

Estimating variances due sire × herd effects requires a large number of sires to be represented in multiple herds, otherwise too much variation between animals is ‘picked up’ as variance due to sire × herd effects, and heritability estimates are biased downwards. Such bias can be avoided by using only records for progeny of multiple-herd use sires to estimate the additive genetic variance. Esti...

2003
Mausumi Bose Aloke Dey

For a general cross-over design, combined intra-inter unit reduced normal equations for estimating linear functions of direct and residual effects are obtained under a mixed effects, non-additive model. The unit effects are considered as random and the model allows for possible interactions among treatments applied at successive periods. Several existing families of designs which are optimal un...

Anita Yaghotipoor Ezatollah Farshadfar, Zeinab Kazemi

Combining ability effects were estimated for different agronomic characters in line × tester crossing program comprising 21 hybrids produced by crossing 7 lines and 3 testers. Parents and hybrids differed significantly for general combining ability (GCA) and specific combining ability (SCA) effects, respectively. The variance due to GCA and SCA showed that gene action was predominantly additive...

Journal: :Neurocomputing 2009
Elia Liitiäinen Michel Verleysen Francesco Corona Amaury Lendasse

The problem of residual variance estimation consists of estimating the best possible generalization error obtainable by any model based on a finite sample of data. Even though it is a natural generalization of linear correlation, residual variance estimation in its general form has attracted relatively little attention in machine learning. both theoretically and experimentally to understand bet...

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