1 Comparison of Linear Mixed Model and Random Regression Model for Weaning Weight in Hereford Cattle over a United States Longitudinal Gradient.

2018 ◽  
Vol 96 (suppl_1) ◽  
pp. 1-1
Author(s):  
J M Langdon ◽  
J S Delgadillo ◽  
A D Herring ◽  
H D Blackburn ◽  
S E Speidel ◽  
...  
Keyword(s):  
United States ◽  
Regression Model ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Random Regression ◽  
Longitudinal Gradient ◽  
Weaning Weight ◽  
Hereford Cattle ◽  
Random Regression Model

Hierarchical mixed-model expedites genome-wide longitudinal association analysis

2021 ◽  
Author(s):  
Ying Zhang ◽  
Yuxin Song ◽  
Jin Gao ◽  
Hengyu Zhang ◽  
Ning Yang ◽  
...  
Keyword(s):  
Association Analysis ◽  
Mixed Model ◽  
Repeated Measurements ◽  
Random Regression ◽  
Association Analyses ◽  
Genome Wide ◽  
Random Regression Model ◽  
A Genome ◽  
Longitudinal Association ◽  
Poultry Data

AbstractA hierarchical random regression model (Hi-RRM) was extended into a genome-wide association analysis for longitudinal data, which significantly reduced the dimensionality of repeated measurements. The Hi-RRM first modeled the phenotypic trajectory of each individual using a RRM and then associated phenotypic regressions with genetic markers using a multivariate mixed model (mvLMM). By spectral decomposition of genomic relationship and regression covariance matrices, the mvLMM was transformed into a multiple linear regression, which improved computing efficiency while implementing mvLMM associations in efficient mixed-model association expedited (EMMAX). Compared with the existing RRM-based association analyses, the statistical utility of Hi-RRM was demonstrated by simulation experiments. The method proposed here was also applied to find the quantitative trait nucleotides controlling the growth pattern of egg weights in poultry data.

scholarly journals Genotypic parameters for egg production in pure breed hens by using random regression model

2017 ◽  
Vol 47 (5) ◽  
Author(s):  
Priscila Becker Ferreira ◽  
Paulo Roberto Nogara Rorato ◽  
Fernanda Cristina Breda ◽  
Vanessa Tomazetti Michelotti ◽  
Alexandre Pires Rosa ◽  
...  
Keyword(s):  
Regression Model ◽  
Regression Models ◽  
Egg Production ◽  
Random Regression ◽  
Broad Sense Heritability ◽  
Residual Matrix ◽  
Random Regression Model ◽  
Residual Covariance ◽  
Genotypic Correlations ◽  
Selection Of

ABSTRACT: This study aimed to test different genotypic and residual covariance matrix structures in random regression models to model the egg production of Barred Plymouth Rock and White Plymouth Rock hens aged between 5 and 12 months. In addition, we estimated broad-sense heritability, and environmental and genotypic correlations. Six random regression models were evaluated, and for each model, 12 genotypic and residual matrix structures were tested. The random regression model with linear intercept and unstructured covariance (UN) for a matrix of random effects and unstructured correlation (UNR) for residual matrix adequately model the egg production curve of hens of the two study breeds. Genotypic correlations ranged from 0.15 (between age of 5 and 12 months) to 0.99 (between age of 10 and 11 months) and increased based on the time elapsed. Egg production heritability between 5- and 12-month-old hens increased with age, varying from 0.15 to 0.51. From the age of 9 months onward, heritability was moderate with estimates of genotypic correlations higher than 90% at the age of 10, 11, and 12 months. Results suggested that selection of hens to improve egg production should commence at the ninth month of age.

scholarly journals A Novel Approach to the Design and Analysis of Field Experiments to Study Variation in the Tolerance and Resistance of Cultivars to Root Lesion Nematodes (Pratylenchus spp.)

2020 ◽  
Vol 110 (10) ◽  
pp. 1623-1631
Author(s):  
Karyn L. Reeves ◽  
Clayton R. Forknall ◽  
Alison M. Kelly ◽  
Kirsty J. Owen ◽  
Joshua Fanning ◽  
...  
Keyword(s):  
Mixed Model ◽  
Field Experiments ◽  
Linear Mixed Model ◽  
Random Regression ◽  
Yield Response ◽  
Response Curves ◽  
Model Framework ◽  
Management Options ◽  
Nematode Reproduction ◽  
Yield Response Curves

The root lesion nematode (RLN) species Pratylenchus thornei and P. neglectus are widely distributed within cropping regions of Australia and have been shown to limit grain production. Field experiments conducted to compare the performance of cultivars in the presence of RLNs investigate management options for growers by identifying cultivars with resistance, by limiting nematode reproduction, and tolerance, by yielding well in the presence of nematodes. A novel experimental design approach for RLN experiments is proposed where the observed RLN density, measured prior to sowing, is used to condition the randomization of cultivars to field plots. This approach ensured that all cultivars were exposed to consistent ranges of RLN in order to derive valid assessments of relative cultivar tolerance and resistance. Using data from a field experiment designed using the conditioned randomization approach and conducted in Formartin, Australia, the analysis of tolerance and resistance was undertaken in a linear mixed model framework. Yield response curves were derived using a random regression approach and curves modeling change in RLN densities between sowing and harvest were derived using splines to account for nonlinearity. Groups of cultivars sharing similar resistance levels could be identified. A comparison of slopes of yield response curves of cultivars belonging to the same resistance class identified differing tolerance levels for cultivars with equivalent exposures to both presowing and postharvest RLN densities. As such, the proposed design and analysis approach allowed tolerance to be assessed independently of resistance.

scholarly journals Test-day or 305-day milk yield for genetic evaluation of Gir cattle

2019 ◽  
Vol 54 ◽  
Author(s):  
Rodrigo Junqueira Pereira ◽  
Denise Rocha Ayres ◽  
Mário Luiz Santana Junior ◽  
Lenira El Faro ◽  
Aníbal Eugênio Vercesi Filho ◽  
...  
Keyword(s):  
Regression Model ◽  
Milk Yield ◽  
Genetic Evaluation ◽  
Random Regression ◽  
Breeding Values ◽  
Random Regression Model ◽  
The Mean ◽  
Yield Record ◽  
Genetic Evaluations ◽  
Dairy Breed

Abstract: The objective of this work was to compare genetic evaluations of milk yield in the Gir breed, in terms of breeding values and their accuracy, using a random regression model applied to test-day records or the traditional model (TM) applied to estimates of 305-day milk yield, as well as to predict genetic trends for parameters of interest. A total of 10,576 first lactations, corresponding to 81,135 test-day (TD) records, were used. Rank correlations between the breeding values (EBVs) predicted with the two models were 0.96. The percentage of animals selected in common was 67 or 82%, respectively, when 1 or 5% of bulls were chosen, according to EBVs from random regression model (RRM) or TM genetic evaluations. Average gains in accuracy of 2.7, 3.0, and 2.6% were observed for all animals, cows with yield record, and bulls (sires of cows with yield record), respectively, when the RRM was used. The mean annual genetic gain for 305-day milk yield was 56 kg after 1993. However, lower increases in the average EBVs were observed for the second regression coefficient, related to persistency. The RRM applied to TD records is efficient for the genetic evaluation of milk yield in the Gir dairy breed.

scholarly journals Determination of the Environmental Factors that Affect the Growth and Survival of Greek Fir Seedlings

Land ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 100
Author(s):  
Vassilis Detsis ◽  
Georgios Efthimiou ◽  
Olga Theodoropoulou ◽  
Stavroula Siorokou
Keyword(s):  
Regression Model ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Clay Content ◽  
Weather Conditions ◽  
Apical Growth ◽  
Growth And Survival ◽  
Initial Height ◽  
Soil Clay ◽  
Soil Clay Content

Forests in the montane-Mediterranean zone have only recently began to be affected by wildfires, therefore the knowledge necessary for restoration projects is missing. The aim of the study was to assess the effects of factors related to seedling attributes, weather conditions and site suitability on seedling performance. The characterisation of sites was based on bedrock and soil clay content as well as pre-fire vegetation. Apical growth and survival of seedlings was monitored for four years in Parnitha National Park. The parameters of a linear mixed model were estimated using annual apical growth of seedlings surviving in the end of the study as the dependent variable and type of site, rainfall, initial seedling height and age as explanatory ones. A quantile regression model using all the data available was estimated for each year of study, taking into account only initial height and site type as well as a logistic regression model of survival. The findings indicate that the growth of Greek fir seedlings depends on May rainfall mediated by soil clay content, which in turn depends on bedrock, which is consistent with the “inverse texture hypothesis”. Sites with low soil clay content were always more beneficial for survival, which was stronger affected by summer–autumn rainfall. In both contexts, drought stress due to soil clay content fades with increasing age. Sites that were not fir dominated prior to fire proved unsuitable also for planting fir seedlings. A minor part of the observed variability could be associated with the initial height of seedlings, especially for seedlings showing high rates of apical growth.

scholarly journals Analysis of longitudinal data of Nellore cattle from performance test at pasture using random regression model

SpringerPlus ◽  
2012 ◽  
Vol 1 (1) ◽  
Author(s):  
Fernando Brito Lopes ◽  
Cláudio Ulhôa Magnabosco ◽  
Fernanda Paulini ◽  
Marcelo Corrêa da Silva ◽  
Eliane Sayuri Miyagi ◽  
...  
Keyword(s):  
Longitudinal Data ◽  
Regression Model ◽  
Performance Test ◽  
Random Regression ◽  
Random Regression Model ◽  
Nellore Cattle
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