Growth curves and nutritional requirements for maintenance of asymptotic weight of Nellore cattle

Arruda, Rosana Moreira da Silva de; Souza, Júlio César de; Jardim, Rodrigo José Delgado; Filho, Paulo Bahiense Ferraz; Silva, Luiz Otavio Campos

doi:10.5935/1806-6690.20180078

Cited by 3 publications

(3 citation statements)

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“…Overall, the R 2 adj were equivalent and showed considerably high and similar values between the four models evaluated, in both sexes. The models had a satisfactory performance in estimating the growth curve parameters, agreeing with results presented by other authors in beef cattle (GONÇALVES et al, 2011;ARRUDA et al, 2018). Considering the RMSE, MAD, AIC, and BIC, the Brody model obtained the lowest values, which indicates that, among the models used in this study, this was the best and most suitable to explain the growth pattern of Polled Nellore males and females.…”

Section: Resultssupporting

confidence: 90%

Fit and genetic parameters of the growth curve of Polled Nellore cattle

Evangelista

Oliveira

Cavalcante

et al. 2022

Rev. bras. saúde prod. anim.

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This study was undertaken to compare different non-linear models for fitting growth curves of Polled Nellore animals as well as to estimate genetic parameters for the components of the growth curve. The study involved body weight-age data of 6,717 Polled Nellore cattle from birth to 650 days of age, which belonged to the Brazilian Association of Zebu Breeders (ABCZ), corresponding to the period from 1980 to 2011. Four non-linear models (Brody, Bertalanffy, Logistic, and Gompertz) were fitted and compared by the adjusted coefficient of determination (R2adj), mean absolute deviation of residuals (MAD), root mean square error (RMSE), Akaike information criterion (AIC), and Bayesian information criterion (BIC). To estimate the genetic parameters and genetic values of asymptotic weight (A), integration constant (B), and maturation rate (K), the Bayesian inference method was adopted. The Brody model showed the lowest values of MAD, RMSE, AIC, and BIC and the highest R2adj. Heritability estimates for parameters A, B, and K were 0.11, 0.16, and 0.30, respectively, whereas genetic correlations were 0.01 (A-B), -0.91 (A-K), and 0.24 (B-K). The Brody model provided the best fit. The K parameter shows enough genetic variability for selection in the herd. Heavier animals in adulthood tend to exhibit lower growth rates. Despite the low heritability estimate of parameter A, there were genetic gains, indicating that selection is being efficient on asymptotic weight.

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Section: Resultssupporting

confidence: 90%

Fit and genetic parameters of the growth curve of Polled Nellore cattle

Evangelista

Oliveira

Cavalcante

et al. 2022

Rev. bras. saúde prod. anim.

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“…Differences in growth curves and body weight composition between the sexes can be explained by hormonal differences such as androgenic effects (e.g., testosterone) ( Young and Bass, 1984 ; Mangwiro et al, 2013 ). In the Nellore breed, there is little difference between male growth and female growth before weaning, but this difference becomes more pronounced with age ( Malhado et al, 2009 ; Arruda et al, 2018 ). This could explain the observed differences in the incidence of FLM in males and females ( Figure 1 ).…”

Section: Discussionmentioning

confidence: 99%

“…Frontiers in Genetics frontiersin.org difference becomes more pronounced with age (Malhado et al, 2009;Arruda et al, 2018). This could explain the observed differences in the incidence of FLM in males and females (Figure 1).…”

Section: Figurementioning

confidence: 94%

Feet and legs malformation in Nellore cattle: genetic analysis and prioritization of GWAS results

Silva,

Gondro,

Fonseca

et al. 2023

Front. Genet.

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Beef cattle affected by feet and legs malformations (FLM) cannot perform their productive and reproductive functions satisfactorily, resulting in significant economic losses. Accelerated weight gain in young animals due to increased fat deposition can lead to ligaments, tendon and joint strain and promote gene expression patterns that lead to changes in the normal architecture of the feet and legs. The possible correlated response in the FLM due to yearling weight (YW) selection suggest that this second trait could be used as an indirect selection criterion. Therefore, FLM breeding values and the genetic correlation between FLM and yearling weight (YW) were estimated for 295,031 Nellore animals by fitting a linear-threshold model in a Bayesian approach. A genome-wide association study was performed to identify genomic windows and positional candidate genes associated with FLM. The effects of single nucleotide polymorphisms (SNPs) on FLM phenotypes (affected or unaffected) were estimated using the weighted single-step genomic BLUP method, based on genotypes of 12,537 animals for 461,057 SNPs. Twelve non-overlapping windows of 20 adjacent SNPs explaining more than 1% of the additive genetic variance were selected for candidate gene annotation. Functional and gene prioritization analysis of candidate genes identified six genes (ATG7, EXT1, ITGA1, PPARD, SCUBE3, and SHOX) that may play a role in FLM expression due to their known role in skeletal muscle development, aberrant bone growth, lipid metabolism, intramuscular fat deposition and skeletogenesis. Identifying genes linked to foot and leg malformations enables selective breeding for healthier herds by reducing the occurrence of these conditions. Genetic markers can be used to develop tests that identify carriers of these mutations, assisting breeders in making informed breeding decisions to minimize the incidence of malformations in future generations, resulting in greater productivity and animal welfare.

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