Modelling growth curve in Moghani sheep: comparison of non-linear mixed growth models and estimation of genetic relationship between growth curve parameters

In order to describe the growth curves in Iranian Moghani sheep, five non-linear mixed mathematical equations (Brody, Negative exponential, Logistic, Gompertz and von Bertalanffy) were compared. After selecting the best-fitted model based on purely statistical criteria, variance components and genet...

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Veröffentlicht in:The Journal of agricultural science 2017-09, Vol.155 (7), p.1150-1159
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description In order to describe the growth curves in Iranian Moghani sheep, five non-linear mixed mathematical equations (Brody, Negative exponential, Logistic, Gompertz and von Bertalanffy) were compared. After selecting the best-fitted model based on purely statistical criteria, variance components and genetic parameters for growth curve characteristics were estimated. The data set and pedigree information used in the current study were obtained from the breeding station of Moghani sheep and included 7905 weight records of 1581 lambs from birth to 400 days of age between the years 1994 and 2012 inclusive. Each model was fitted to body weight records for all lambs, males, females, single and twin lambs using the NLMIXED procedure in SAS and the parameters were estimated. Animal was considered as subject in the models. The non-linear mixed models were examined for goodness of fit using Akaike's information criterion (AIC) and residual variance. Marginal posterior distribution of genetic parameters and variance components were estimated using the Threshold Model programme. The Gibbs sampler was run for 1 000 000 rounds and the first 200 000 rounds were discarded as a burn-in period. Logistic model provided the best fit of growth curve in males, females, singles, twins and all lambs due to the lower values of AIC and residual variance compared with other models. Posterior mean estimates of direct heritabilities for asymptotic weight (A), initial animal weight (B) and maturation rate (K) parameters of Logistic model were 0·21, 0·24 and 0·29, respectively. Also, posterior mean estimates of maternal heritabilities for A, B and K were 0·27, 0·24 and 0·19, respectively. Estimate of correlation between direct and maternal genetic effects for A, B and K parameters were −0·33, −0·69 and −0·51, respectively. Estimates of direct genetic correlation between A–B, A–K and B–K were positive and equal to 0·19, 0·07 and 0·28, respectively. Also, maternal genetic correlations between A–B, A–K and B–K were positive and equal to 0·43, 0·34 and 0·55, respectively. In general, evaluation of different growth equations used in the current study indicated the potential of the non-linear functions to fit body weight records of Moghani sheep. Also, the results of the current study showed that improvement of growth curve parameters of Moghani sheep could be possible in selection programmes. Therefore, development of an optimal selection strategy to achieve a desired shape of growth curve through
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After selecting the best-fitted model based on purely statistical criteria, variance components and genetic parameters for growth curve characteristics were estimated. The data set and pedigree information used in the current study were obtained from the breeding station of Moghani sheep and included 7905 weight records of 1581 lambs from birth to 400 days of age between the years 1994 and 2012 inclusive. Each model was fitted to body weight records for all lambs, males, females, single and twin lambs using the NLMIXED procedure in SAS and the parameters were estimated. Animal was considered as subject in the models. The non-linear mixed models were examined for goodness of fit using Akaike's information criterion (AIC) and residual variance. Marginal posterior distribution of genetic parameters and variance components were estimated using the Threshold Model programme. The Gibbs sampler was run for 1 000 000 rounds and the first 200 000 rounds were discarded as a burn-in period. Logistic model provided the best fit of growth curve in males, females, singles, twins and all lambs due to the lower values of AIC and residual variance compared with other models. Posterior mean estimates of direct heritabilities for asymptotic weight (A), initial animal weight (B) and maturation rate (K) parameters of Logistic model were 0·21, 0·24 and 0·29, respectively. Also, posterior mean estimates of maternal heritabilities for A, B and K were 0·27, 0·24 and 0·19, respectively. Estimate of correlation between direct and maternal genetic effects for A, B and K parameters were −0·33, −0·69 and −0·51, respectively. Estimates of direct genetic correlation between A–B, A–K and B–K were positive and equal to 0·19, 0·07 and 0·28, respectively. Also, maternal genetic correlations between A–B, A–K and B–K were positive and equal to 0·43, 0·34 and 0·55, respectively. In general, evaluation of different growth equations used in the current study indicated the potential of the non-linear functions to fit body weight records of Moghani sheep. Also, the results of the current study showed that improvement of growth curve parameters of Moghani sheep could be possible in selection programmes. Therefore, development of an optimal selection strategy to achieve a desired shape of growth curve through changing genetically the parameters of model would be very important.</description><identifier>ISSN: 0021-8596</identifier><identifier>EISSN: 1469-5146</identifier><identifier>DOI: 10.1017/S0021859617000326</identifier><language>eng</language><publisher>Cambridge, UK: Cambridge University Press</publisher><subject>Animal breeding ; Animal populations ; Animal Research Papers ; Body weight ; Breeding of animals ; Burn-in ; Correlation ; Estimates ; Females ; Functions (mathematics) ; Genetic effects ; Genetic relationship ; Goodness of fit ; Growth curves ; Males ; Mathematical analysis ; Mathematical models ; Maturation ; Nonlinear equations ; Order parameters ; Parameter estimation ; Pedigree ; Population genetics ; Sheep ; Twins ; Variance</subject><ispartof>The Journal of agricultural science, 2017-09, Vol.155 (7), p.1150-1159</ispartof><rights>Copyright © Cambridge University Press 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c317t-f3992515bca4a928c6a154c45f0396a6696cabe16ae8a0c0a9dabb79f17849163</citedby><cites>FETCH-LOGICAL-c317t-f3992515bca4a928c6a154c45f0396a6696cabe16ae8a0c0a9dabb79f17849163</cites><orcidid>0000-0001-9458-5860</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S0021859617000326/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>164,314,777,781,27905,27906,55609</link.rule.ids></links><search><creatorcontrib>GHAVI HOSSEIN-ZADEH, N.</creatorcontrib><title>Modelling growth curve in Moghani sheep: comparison of non-linear mixed growth models and estimation of genetic relationship between growth curve parameters</title><title>The Journal of agricultural science</title><addtitle>J. Agric. Sci</addtitle><description>In order to describe the growth curves in Iranian Moghani sheep, five non-linear mixed mathematical equations (Brody, Negative exponential, Logistic, Gompertz and von Bertalanffy) were compared. After selecting the best-fitted model based on purely statistical criteria, variance components and genetic parameters for growth curve characteristics were estimated. The data set and pedigree information used in the current study were obtained from the breeding station of Moghani sheep and included 7905 weight records of 1581 lambs from birth to 400 days of age between the years 1994 and 2012 inclusive. Each model was fitted to body weight records for all lambs, males, females, single and twin lambs using the NLMIXED procedure in SAS and the parameters were estimated. Animal was considered as subject in the models. The non-linear mixed models were examined for goodness of fit using Akaike's information criterion (AIC) and residual variance. Marginal posterior distribution of genetic parameters and variance components were estimated using the Threshold Model programme. The Gibbs sampler was run for 1 000 000 rounds and the first 200 000 rounds were discarded as a burn-in period. Logistic model provided the best fit of growth curve in males, females, singles, twins and all lambs due to the lower values of AIC and residual variance compared with other models. Posterior mean estimates of direct heritabilities for asymptotic weight (A), initial animal weight (B) and maturation rate (K) parameters of Logistic model were 0·21, 0·24 and 0·29, respectively. Also, posterior mean estimates of maternal heritabilities for A, B and K were 0·27, 0·24 and 0·19, respectively. Estimate of correlation between direct and maternal genetic effects for A, B and K parameters were −0·33, −0·69 and −0·51, respectively. Estimates of direct genetic correlation between A–B, A–K and B–K were positive and equal to 0·19, 0·07 and 0·28, respectively. Also, maternal genetic correlations between A–B, A–K and B–K were positive and equal to 0·43, 0·34 and 0·55, respectively. In general, evaluation of different growth equations used in the current study indicated the potential of the non-linear functions to fit body weight records of Moghani sheep. Also, the results of the current study showed that improvement of growth curve parameters of Moghani sheep could be possible in selection programmes. 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Agric. Sci</addtitle><date>2017-09</date><risdate>2017</risdate><volume>155</volume><issue>7</issue><spage>1150</spage><epage>1159</epage><pages>1150-1159</pages><issn>0021-8596</issn><eissn>1469-5146</eissn><abstract>In order to describe the growth curves in Iranian Moghani sheep, five non-linear mixed mathematical equations (Brody, Negative exponential, Logistic, Gompertz and von Bertalanffy) were compared. After selecting the best-fitted model based on purely statistical criteria, variance components and genetic parameters for growth curve characteristics were estimated. The data set and pedigree information used in the current study were obtained from the breeding station of Moghani sheep and included 7905 weight records of 1581 lambs from birth to 400 days of age between the years 1994 and 2012 inclusive. Each model was fitted to body weight records for all lambs, males, females, single and twin lambs using the NLMIXED procedure in SAS and the parameters were estimated. Animal was considered as subject in the models. The non-linear mixed models were examined for goodness of fit using Akaike's information criterion (AIC) and residual variance. Marginal posterior distribution of genetic parameters and variance components were estimated using the Threshold Model programme. The Gibbs sampler was run for 1 000 000 rounds and the first 200 000 rounds were discarded as a burn-in period. Logistic model provided the best fit of growth curve in males, females, singles, twins and all lambs due to the lower values of AIC and residual variance compared with other models. Posterior mean estimates of direct heritabilities for asymptotic weight (A), initial animal weight (B) and maturation rate (K) parameters of Logistic model were 0·21, 0·24 and 0·29, respectively. Also, posterior mean estimates of maternal heritabilities for A, B and K were 0·27, 0·24 and 0·19, respectively. Estimate of correlation between direct and maternal genetic effects for A, B and K parameters were −0·33, −0·69 and −0·51, respectively. Estimates of direct genetic correlation between A–B, A–K and B–K were positive and equal to 0·19, 0·07 and 0·28, respectively. Also, maternal genetic correlations between A–B, A–K and B–K were positive and equal to 0·43, 0·34 and 0·55, respectively. In general, evaluation of different growth equations used in the current study indicated the potential of the non-linear functions to fit body weight records of Moghani sheep. Also, the results of the current study showed that improvement of growth curve parameters of Moghani sheep could be possible in selection programmes. Therefore, development of an optimal selection strategy to achieve a desired shape of growth curve through changing genetically the parameters of model would be very important.</abstract><cop>Cambridge, UK</cop><pub>Cambridge University Press</pub><doi>10.1017/S0021859617000326</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-9458-5860</orcidid></addata></record>
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1469-5146
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source Cambridge University Press Journals Complete
subjects Animal breeding
Animal populations
Animal Research Papers
Body weight
Breeding of animals
Burn-in
Correlation
Estimates
Females
Functions (mathematics)
Genetic effects
Genetic relationship
Goodness of fit
Growth curves
Males
Mathematical analysis
Mathematical models
Maturation
Nonlinear equations
Order parameters
Parameter estimation
Pedigree
Population genetics
Sheep
Twins
Variance
title Modelling growth curve in Moghani sheep: comparison of non-linear mixed growth models and estimation of genetic relationship between growth curve parameters
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