scholarly journals Systematic factors and individual variation affecting litter size of Boer and Jawarandu goat cross

2021 ◽  
Vol 902 (1) ◽  
pp. 012009
Author(s):  
N K Agustin ◽  
T Nugroho ◽  
R Setiaji ◽  
S Prastowo ◽  
N Widyas
Keyword(s):  
Maximum Likelihood ◽  
Linear Model ◽  
Litter Size ◽  
Individual Variation ◽  
Mixed Model ◽  
Restricted Maximum Likelihood ◽  
Individual Data ◽  
Individual Variations ◽  
The Individual ◽  
Boer Goats

Abstract We studied the systematic factors and individual variation affecting litter size in the crossbreds between Boer and Jawarandu goat. The data were obtained from the records of litter size of Boerja goats from 2012 to 2015. The systematic factors consisted of season and year of birth, doe breeds and the kid’s sex; along with individual data including pedigree, date of birth, and parental breeds. The data consisted of 107 Boer does, 687 Jawarandu does, and 495 Boerja does with a total of 3804 kids. A linear model was developed to account the effect of systematic factors on litter size of Boerja goats. Later, a mixed model was solved with Restricted Maximum Likelihood (REML) method to estimate the individual variations on litter size. The results showed that litter size trait in goat was influenced by doe breed (P<0.05). Individual variation of this trait was also high (46%). Based on this research, it can be concluded that litter size of Boer goats and their crosses were affected by the doe’s breed with high individual variation. Doe’s selection is potential to improve liter size in goat crossbred population in the future.

scholarly journals The effect of individual variation on litter weight in Boer and Jawarandu goat crossbreed

2021 ◽  
Vol 902 (1) ◽  
pp. 012014
Author(s):  
E P Wardani ◽  
T Nugroho ◽  
R Setiaji ◽  
S Prastowo ◽  
N Widyas
Keyword(s):  
Reproductive Performance ◽  
Individual Variation ◽  
Mixed Model ◽  
Individual Identity ◽  
Season Of Birth ◽  
High Genetic Diversity ◽  
Mixed Model Analysis ◽  
Litter Weight ◽  
Individual Variations ◽  
The Individual

Abstract This study aims to determine the effect of individual variations on litter weight in Boer and Jawarandu goat crossbreed in CV. Kambing Burja (farm), East Java. Records from 2012 to 2015 consisted of breed of does, date of birth, litter size and birth weight of kids; along with individual identity, season and year of birth were obtained. There were 107 Boer, 687 Jawarandu, and 495 Boerja does with a total of 3804 kids in the records. Data analysis was conducted using Analysis of Variance (ANOVA) incorporating the factors of season of birth (rainy and dry season) and doe’s breed (Boer, Jawarandu, and Boerja F1). Mixed model analysis using Restricted Maximum Likelihood (REML) method was used to estimate the individual variations. The results showed that both doe’s breed and season of birth had a significant effect (p<0.05) on litter weight; while the individual variations contributed 36.28% to the total variance. We concluded that the individual variation of litter weight was considerably high which reflects high genetic diversity within each breed. Hence, selection to improve the reproductive performance of these goats is highly possible.

Asymptotic Optimality of Restricted Maximum Likelihood Estimates for the Mixed Model

1979 ◽  
Vol 28 (1-4) ◽  
pp. 125-142 ◽  
Author(s):  
Kalyan Das
Keyword(s):  
Maximum Likelihood ◽  
Conceptual Design ◽  
Analysis Of Variance ◽  
Variance Components ◽  
Mixed Model ◽  
Asymptotic Optimality ◽  
Restricted Maximum Likelihood ◽  
Maximum Likelihood Estimates ◽  
Asymptotically Normal ◽  
Reasonable Sense

In this paper we study the asymptotic optimality of the restricted maximum likelihood estimates of variance components in the mixed model of analysis of variance. Using conceptual design sequences of Miller (1977), under slightly stronger conditions, we show that the restricted maximum likelihood estimates are not only asymptotically normal, but also asymptotically equivalent to the maximum likelihood estimates in a reasonable sense.

subject k(i) gets formulation R, ε if response Y is from formulation T and ε if response Y is from formulation R. The means of T and R are then µ and µ , respectively. Then Var[s ] = σ , the between-subject variance for T , Var[s ] = σ , the between-subject variance for R, Var[s ] = σ , the subject-by-formulation interaction variance, Cov[s ] = ρσ σBR = σ , Var[ε ] = σ and Var[ε ] = σ . Further, we assume that all ε’s are pairwise independent, both within and between subjects. For the special case [ of equal group sizes (n Var[µˆ ] = [ σ − 2σ + ] (σ +σ )/2 /N = σ + (σ )/2 /N where N = 4n. The variances and interactions needed to assess IBE can easily be ob-tained by fitting an appropriate mixed model using proc mixed in SAS. The necessary SAS code for our example will be given below. However, before doing that we need some preliminary results. Using the SAS code we will obtain estimates σˆ , ωˆ , σˆ and σˆ , where ω is the between-subject covariance of R and T, and was earlier denoted by σ . These are normally distributed in the limit with a variance-covariance matrix appropriate to the structure of the fitted model. The model is fitted using REML (restricted maximum likelihood, see Section 6.3 of Chapter 6) and this can be done with SAS proc mixed with the REML option. In addition we fit an unstructured covariance structure using the type =UN option in proc mixed. The estimates of the vari-

2003 ◽  
pp. 366-366
Keyword(s):  
Maximum Likelihood ◽  
Covariance Matrix ◽  
Mixed Model ◽  
Covariance Structure ◽  
Restricted Maximum Likelihood ◽  
Preliminary Results ◽  
Equal Group ◽  
The Subject ◽  
Special Case ◽  
Interaction Variance

Estimation of genotypic correlation and heritability of apricot traits, using restricted maximum likelihood in repeated measures data

2016 ◽  
Vol 96 (3) ◽  
pp. 439-447 ◽  
Author(s):  
Ahmad Ismaili ◽  
Farhad Karami ◽  
Omidali Akbarpour ◽  
Abdolhossein Rezaei Nejad
Keyword(s):  
Maximum Likelihood ◽  
Repeated Measures ◽  
Mixed Model ◽  
Covariance Structure ◽  
Restricted Maximum Likelihood ◽  
Environment Interaction ◽  
Genotypic Correlation ◽  
Model Based ◽  
Repeated Measures Data ◽  
Heritability Estimation

In estimation of genetic parameters in perennial tree species on the basis of analysis of variance (ANOVA), heterogeneity of years and genotype × environment interaction for data sets during the juvenility to maturity life period is ignored. Therefore, a linear mixed model based on restricted maximum likelihood (REML) approximation for modeling of covariance structure of longitudinal data can improve our ability to analyze repeated measures data. In the present research, a modeling of variance-covariance structure by mixed model based on the REML approach has been used for characteristics of 26 apricot genotypes recorded during three years. Fitting unstructured covariance (UN) models for all traits indicated a great heterogeneity of variances among repeated years and the trends of response variables in the genotypes (except for RWC) was due to imperfect correlation of subjects measured in different years. Based on the same structure, positive correlations were estimated among fruit set, potassium content, and yield of pistil in repetitive years, and most traits showed high heritability estimation. To our knowledge, this is the first report in plant that genotypic correlation and heritability and their standard errors are estimated in a repeated measures data over years using REML approximation.

scholarly journals Genetic Analysis of Fitness Traits of Kashmir Merino Sheep at Organized Farms of Kashmir

2021 ◽  
Author(s):  
Mubashir Ali Rather ◽  
Ambreen Hamadani ◽  
Tariq Ahmad Malik ◽  
Imran Bashir ◽  
Ishfaq Ahmad
Keyword(s):  
Maximum Likelihood ◽  
Sex Ratio ◽  
Litter Size ◽  
Genetic Factors ◽  
Mixed Model ◽  
Reproductive Efficiency ◽  
Sheep Breeding ◽  
Merino Sheep ◽  
Fitness Traits ◽  
Estimate Number

Background: Fitness traits include measures of reproductive efficiency of sheep. The improvement in reproductive efficiency has significant impact on overall economy of sheep. Methods: Data spanning over 21 years (1997-2017) were collected from two sheep breeding farm and analyzed with mixed model least-squares maximum likelihood (LSMLMW) computer (PC-2) programme designed by Harvey (1990) to estimate number of lambs born per ewe (NLBE), number of lambs weaned per ewe (NLWE), litter size (LS) and sex ratio (SR) of Kashmir Merino sheep. Result: Overall estimates of 3.56±0.11, 3.20±0.10, 48.32±0.04 and 1.06±0.01 for number of lambs born per ewe (NLBE), number of lambs weaned per ewe (NLWE), litter size (LS) and sex ratio (SR), respectively were observed in the present study. The period of birth had significant (p less than 0.05) effect on NLBE and NLEE. The effect of sire was highly significant on all the traits under study whereas effect of all the non-genetic factors considered had non-significant effect on LS and SR.

Relationships between ovulation rate, prenatal survival and litter size in French Large White pigs

1996 ◽  
Vol 63 (1) ◽  
pp. 143-148 ◽  
Author(s):  
A. Blasco ◽  
J. Gogué ◽  
J. P. Bidanel
Keyword(s):  
Litter Size ◽  
Individual Variation ◽  
Negative Relationship ◽  
Ovulation Rate ◽  
White Population ◽  
Large White ◽  
High Positive Correlation ◽  
The Individual ◽  
The Right ◽  
The Relationship

AbstractThe relationship between total number born (TNB), ovulation rate (CL) and prenatal survival was analysed in a French Large White population. The left ovary had a significantly (P < 0·01) higher ovulation rate (7·9) than the right ovary (6·9). Prenatal survival showed an ovum wastage of 35 or 37% depending on whether referred to total number born or number born alive. No differences between parities were found in these traits. There was a negative relationship between ovulation rate at both sides (v = −0·34). There was a negative relationship between CL and prenatal survival (r = −0·37), a low correlation between CL and TNB (i = 0·19), and a high positive correlation between prenatal survival and TNB (i = 0·82). Litter size showed a quadratic relationship with ovulation rate, and the individual variation for each class of ovulation rate was found to be high. The relationship between prenatal survival and ovulation rate was found to be linear, and a high individual variation for each class of litter size was also found. The relationships between prenatal survival and litter size were quadratic, but depended much less on individual variation.

Sign in / Sign up

Export Citation Format

Share Document