Characterization of commercial and biological growth curves in the Segureña sheep breed

Abstract

Non-linear models were analysed to describe both the biological and commercial growth curves of the Segureña sheep, one of the most important Spanish breeds. We evaluated Brody, von Bertalanffy, Verhulst, logistic and Gompertz models, using historical data from the National Association of Segureña Sheep Breeders (ANCOS). These records were collected between 2000 and 2013, from a total of 129 610 weight observations ranging from birth to adulthood. The aim of this research was to establish the mathematical behaviour of body development throughout this breed's commercial life (birth to slaughter) and biological life (birth to adulthood); comparison between both slopes gives important information regarding the best time for slaughter, informs dietary advice according to animals' needs, permits economical predictions of productions and, by using the curve parameters as selection criteria, enables improvements in growth characteristics of the breed. Models were fitted according to the non-linear regression procedure of statistical package SPSS version19. Model parameters were estimated using the Levenberg-Marquardt algorithm. Candidate models were compared using the determinative coefficient, mean square error, number of iterations, Akaike information coefficient and biological coherence of the estimated parameters. The von Bertalanffy and logistic models were found to be best suited to the biological and commercial growth curves, respectively, for both sexes. The Brody equation was found to be unsuitable for studying the commercial growth curve. Differences between the parameters in both sexes indicate a strong impact of sexual dimorphism on growth. This can emphasize the value of the highest growth rate for females, indicating that they reach maturity earlier.Keywords: growth, models, sex, sheep, Zootechny ImplicationsNon-linear models can be an option to establish the mathematical behaviour of body development throughout the life of the Segureña sheep breed. These models require lower computational and faster convergence than other methods. Moreover, in genetic evaluation programmes with large data sets, non-linear models are more advantageous. The results showed a strong impact of sexual dimorphism on growth.

Genetic parameters of traits associated with the growth curve in Segureña sheep

“…In general, the logistic model presented a better general efficiency according to the mean deviation between the predicted and observed weight and the correlation between them (Table 3); this was previously shown by Lupi et al (2015). In both cases, the efficiency increased from P0 to P3.…”

“…In a previous study of the Segureña breed growth curve, it was concluded that the most suitable function to explain the evolution of weight from birth to slaughter age (80 days) in a general population was the logistic model (Lupi et al, 2015). Based on that study, we introduced this function into the present study.…”

“…However, live animals with high genetic values are also an important Spanish export. Segureña sheep are mainly exploited in extensive and semi-extensive conditions due to their excellent capacity for adaptation; they are also a component of the balanced ecosystems in the regions they inhabit, thereby making them a mainstay of environmental and social sustainability (Lupi et al, 2015).…”

Effects of some factors on growth of lambs and the determination of growth curve models

“…Parameter k represents the relative growth rate (rate of exponential growth). High values for this parameter shows animals with precocious maturity, whereas low values for parameter indicate a delayed maturity (Akbas, 1995;Lupi et al, 2015).…”

“…For an effective animal improvement, growth curve models can provide a contribution to estimate the adequate parameters for growth pattern and thus, these parameters estimated can be used in animal improvement and selection process (sireli, 2002;Bilgi ve Esenboga, 2003;Kor ve ark., 2006;Koncagül et al, 2013;Lupi et al, 2015;Makovický et al, 2017).…”