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The aim of this study was to assess the most important risk factors that influence productive life (PL) and to estimate genetic parameters for PL using a Weibull proportional hazards model in two Spanish dairy goat breeds belonging to different production systems. The dataset consisted of 70,695 and 49,176 lactation records of Florida and Payoya females, respectively, collected over the last two decades. A total of 6,227 (24.21%) Florida and 3,452 (20.42%) Payoya females had censored information. The pedigree included a total of 56,901 animals for Florida and 59,957 for Payoya. The effects included in the model for both breeds were the age at first kidding and the herd-year-season of birth of the doe as time-independent effects; and the age at kidding, the herd-year-season of kidding, the within-herd class of milk production deviation and the combination between the lactation number and the duration of lactation as time-dependent effects. Estimation of genetic parameters was made using a Weibull proportional hazards model using Survival Kit V6.0 software. The results from the Weibull animal models gave estimates of additive genetic variances of 0.99 ± 0.0003 and 0.156 ± 0.021, which corresponds to a heritability of 0.43 ± 0.025 and 0.11 ± 0.021 for Florida and Payoya, respectively. The magnitude of heritability obtained for PL suggests that a substantial response to selection may be expected for longevity, especially in the Florida breed. These results may contribute to the development of a routine genetic evaluation to improve PL in Spanish dairy goat breeds.

Genetic parameters of litter size (LS) and number of kids born alive (NBA) were estimated across parities in Florida and Payoya goat breeds using a threshold random regression model (RRM). We analysed the reproductive records for the Florida and Payoya breeds separately, and a total of 130.849 and 67.478 reproductive records from the first to the seventh parities from Florida and Payoya, respectively, were included in the analysis. Random regressions on Legendre polynomials of standardised parity were included for permanent environmental and additive genetic effects. We based our estimation of all the covariance components on Bayesian inference under categorical distribution and considered heterogeneous residual variances in the model. The estimates of heritabilities ranged from null to 0.37 for LS and from 0.02 to 0.20 for NBA, while the repeatability estimates were between 0.008–0.60 and 0.03–0.44 for LS and NBA, respectively. Phenotypic correlations within-trait along parities ranged widely from −0.31 to 0.97, while the genetic correlations within-trait through parities showed a wider range and magnitude of values, from −0.98 to 0.99 for LS and from −0.72 to 0.99 for NBA. The estimates of genetic correlations between LS and NBA in the different parities were positive in the first two parities and negative in the later ones. Due to the noticeable changes in variance and the incomplete genetic correlations, the use of a random regression model to analyse LS and NBA is recommended in goat breeds.HIGHLIGHTS A bivariate threshold random regression model has been used for the first time to estimate genetic parameters of litter size and number of kids born alive across parities in Spanish goat breeds. The evolution of genetic parameters along parities is different between Florida and Payoya that have different production systems, being more intensive in the case of the Florida breed. Estimates of variance were not constant across parities for both traits and breeds. Genetic correlations within-trait across parities were different from unity. Thus, LS and NBA should be treated as different traits in successive parities. Given that the estimates of variance and covariances are not constant across parities for both traits and breeds, the use of RRM is highly recommended.

This study aimed to estimate genetic parameters of reproductive efficiency over a wide age range of females using a random regression model (RRM) in Spanish goat breeds. A total of 138,139 and 64,638 reproductive records from the first to the sixth parities from Florida and Payoya, respectively, were included in the analysis. Random regressions on Legendre polynomials of standardised age were included for permanent environmental and additive genetic effects. Estimation of the covariance components was based on the Bayesian inference using the GIBBS3F90 software. Differences among genetic variance components for reproductive efficiency were observed over the animal’s lifetime. The estimates of heritabilities were moderate, ranging from 0.21 to 0.32 for Florida and from 0.25 to 0.35 for Payoya, while the fractions of phenotypic variance explained by the permanent environmental effect were high, varying between 0.45–0.68 and 0.58–0.71 for Florida and Payoya, respectively. The correlations for permanent environmental effect over age ranged from 0.37 to 0.99, while the genetic correlations between the different ages varied from 0.36 to 0.98 for Florida and from 0.80 to 0.99 for Payoya. The results from this study support the validity of using an RRM to genetically analyse reproductive efficiency in Spanish dairy goats following the changes in variances and the genetic correlations different from unity over the animal’s lifetime. Moreover, reproductive efficiency is a highly heritable trait that is expressed early in a female’s life, and it could be used as a precocious selection criterion to improve female fertility in Spanish dairy goats.Highlights Reproductive efficiency (RE) has been proposed as a trait to improve female fertility in dairy goats. RE was genetically analysed using an RRM over a range of ages in females from the Florida and Payoya breeds raised under different production systems. Variance components for RE were not constant over age, while the genetic correlations between RE in the different ages were different from unity. The use of RRM for RE is therefore justified in both goat breeds.