Determination of the best nonlinear function and genetic parameter estimates of early growth in Romane lambs

Document Type : Original Research Article (Regular Paper)


1 Department of Animal Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

2 Animal science, Faculty of Agriculture

3 GenPhySE, INRAE, Université de Toulouse, INPT, ENVT, F 31326 Castanet Tolosan, France


The objectives of this study were a) to compare growth functions for describing the early growth curve of Romane sheep based on weighing records, b) to estimate the heritability of the growth curve parameters, and c) to estimate genetic parameters for 90-days-old bodyweight utilizing the data of earlier age. The raw data included 662 lambs (316 males and 346 females) bred at the Romane Sheep Research Center, INRAE, France. The studied trait was the bodyweight of lambs at birth, 15, 21, 35, 60, and 90 days of age. The number of measurements was approximately six for each animal. Dataset after mining consisted of 3261 weight records of 574 lambs. We applied four non-linear growth functions, including Gompertz, Brody, Logistic, and Richard. The goodness of fit of the included models were compared using the Akaike information criterion (AIC), coefficient of determination (R2) and residual mean square (MSE). Predicting abilities of the included models were evaluated by comparing the predicted and observed phenotypes until 90 days of age. Genetic parameters of the non-linear functions were obtained using a specific two steps approach; in first step, the parameters of the different functions were estimated, and in the second, the parameters were considered as observations and we analyzed them using a multiple trait animal models. Residual mean square and R2 for the models of Brody, Gompertz, Logistic and Richards were 106.71 and 0.37, 4.79 and 0.94, 7.41 and 0.88, and 9.04 and 0.88, respectively. The Logistic function had the smallest AIC and MSE values, and also had the highest R2 value, indicating the best fit. The estimated heritability of the parameters in the logistic function were low (ranging from 0.007 to 0.017). In our study, the correlation between BV90 and BV35 was 0.5419 with a confidence interval of 0.469 - 0.608. Since BV90 and BV35 have a positive genetic correlation, BV35 could be used to select the lambs for best growth until the slaughter age of Romane using the Logistic model


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