Genealogical data of Boer and Nubian goats in Mexico.

The pedigree file of the Boer and Nubian goat breeds in Mexico was constructed using the national database provided by the Asociación Mexicana de Criadores de Ganado Caprino de Registro. Field technicians routinely updated the goat national database by recording information from flocks participating in the performance-recording system. Information on animal identification number, parents, birth date, sex, breed, and farm of origin were used to undertake pedigree analyses using the ENDOG program (version 4.8). This paper presents a pedigree data file, tables and figures of characteristics of pedigree data, pedigree analyses, pedigree integrity, effective population size and genetic conservation index. The data can be used to estimate other population parameters, to monitor the genetic diversity of the Boer and Nubian goat breeds in Mexico, and also to design balanced breeding programs, maintaining genetic variation at reasonable levels and maximizing genetic progress in these populations.

Dataset on growth curves of Boer goats fitted by ten non-linear functions.

Data on the description of growth of female Boer goats from the Mexican national breeding flock are presented. Goat meat is highly appreciated for the preparation of traditional dishes of Mexican cuisine, and its demand is on the rise. Boer goats are of relatively recent arrival in Mexico and the size of the performance-recorded flock has been increasing steadily in the last ten years. Repeated measures of body weight at different ages from birth to adulthood of Boer goats are scarce. When available, such data can be used to describe the growth pattern and the meat production potential of goat meat breeds such as the Boer. This paper presents data on estimators of growth curve parameters, plots of average predicted growth curves, plots of residuals on age, and data on goodness of fit statistics of ten non-linear functions fitted to describe the growth curve of Boer goats.

Genotype by feeding system interaction in the genetic evaluation of Jersey cattle for milk yield.

Results of studies in dairy cattle about the magnitude of the genotype-environment interaction (GEI) are variable, depending on the definitions of genotype and environment. Therefore, the objective of this study was to determine the magnitude of the interaction of genotype and feeding system (confinement and grazing) in the Mexican genetic evaluation of Jersey cattle for milk yield. The number of lactations and animals in the pedigree used were 5122 and 18 432. An animal model and the MTDFREML program were used to estimate genetic parameters and predict genetic values of the animals. Bivariate analysis was carried out considering the performance of confined and grazing cows as two different traits. Three indicator variables were used to assess GEI: (i) magnitude of the genetic correlation coefficients, (ii) correlation between predicted breeding values and (iii) frequency of coincidence in the ranking of top sires. The magnitude of GEI depended on the choice of the indicator variable. The estimate of genetic correlation coefficient less than unity (0.76; P < 0.05) suggested the presence of biologically important GEI. The differences in phenotypic averages and variances between confinement and grazing systems seem to be the main causes for the genotype by environment interaction detected. However, the correlation coefficient between breeding values from confined and grazing animals (0.96) and the frequency of coincidence between breeding values of common sires within the top 100 in confinement and grazing (0.86) indicated low-to-moderate re-ranking of animals or top sires. In addition, the high correlations between predicted breeding values of Mexican genetic evaluation and the two environments (0.99 and 0.93 for confinement and grazing) indicated that for the two feeding systems, breeding values from national analyses could be safely used.

Inferring genetic parameters of lactation in Tropical Milking Criollo cattle with random regression test-day models.

This study inferred genetic and permanent environmental variation of milk yield in Tropical Milking Criollo cattle and compared 5 random regression test-day models using Wilmink's function and Legendre polynomials. Data consisted of 15,377 test-day records from 467 Tropical Milking Criollo cows that calved between 1974 and 2006 in the tropical lowlands of the Gulf Coast of Mexico and in southern Nicaragua. Estimated heritabilities of test-day milk yields ranged from 0.18 to 0.45, and repeatabilities ranged from 0.35 to 0.68 for the period spanning from 6 to 400 d in milk. Genetic correlation between days in milk 10 and 400 was around 0.50 but greater than 0.90 for most pairs of test days. The model that used first-order Legendre polynomials for additive genetic effects and second-order Legendre polynomials for permanent environmental effects gave the smallest residual variance and was also favored by the Akaike information criterion and likelihood ratio tests.

Comparison of threshold vs linear and animal vs sire models for predicting direct and maternal genetic effects on calving difficulty in beef cattle.

This study compared the accuracy of several models for obtaining genetic evaluations of calving difficulty. The models were univariate threshold animal (TAM), threshold sire-maternal grandsire (TSM), linear animal (LAM), and linear sire-maternal grandsire (LSM) models and bivariate threshold-linear animal (TLAM), threshold-linear sire-maternal grandsire (TLSM), linear-linear animal (LLAM), and linear-linear sire-maternal grandsire (LLSM) models for calving difficulty and birth weight. Data were obtained from the American Gelbvieh Association and included 84,420 first-parity records of both calving difficulty and birth weight. Calving difficulty scores were distributed as 73.4% in the first category (no assistance), 18.7% in the second, 6.3% in the third, and 1.6% in the fourth. Included in the animal models were fixed sex of calf by age of dam subclasses, random herd-year-season effects, and random animal direct and maternal breeding values. Sire-maternal grandsire models were similar to the animal models, with animal and maternal effects replaced by sire and maternal grandsire effects. Models were compared using a data splitting technique based on the correlation of estimated breeding values from two samples, with one-half of the calving difficulty records discarded randomly in the first sample and the remaining calving difficulty records discarded in the second sample. Reported correlations are averages of 10 replicates. The results obtained using animal models confirmed the slight advantage of TAM over LAM (0.69 vs 0.63) and TLAM over LLAM (0.90 vs 0.86). Bivariate analyses greatly improved the accuracy of genetic prediction of direct effects on calving difficulty relative to univariate analyses. Similar ranking of the models was found for maternal effects, but smaller correlations were obtained for bivariate models. For sire-maternal grandsire models, no differences between sire or maternal grandsire correlations were observed for TLSM compared to LLSM, and small differences were observed between TSM and LSM. The threshold model offered advantages over the linear model in animal models but not in sire-maternal grandsire models. For genetic evaluation of calving difficulty in beef cattle, the threshold-linear animal model seems to be the best choice for predicting both direct and maternal effects.

Potential accuracy of genetic evaluation for calving difficulty with incomplete data on calving difficulty and/or birth weight using a bivariate threshold-linear animal model.

The purpose of this study was to evaluate the potential loss of accuracy in direct and maternal predicted breeding values (PBV) for calving difficulty (CD) with different levels of missing records of CD and/or birth weight (BW), using a bivariate threshold-linear animal model. Data obtained from the American Gelbvieh Association included 84,420 first-parity records with both CD and BW available. The final pedigree file included 178,858 animals. The model included fixed calf-sex-dam-age, random herd-year-season, and animal direct and maternal effects. Different levels of missing observations for CD and BW were obtained by randomly deleting 0, 25, 50, 75, and 100% of records for both traits in various combinations. Correlation estimates between PBV for CD obtained with complete and incomplete data were used to measure the changes in PBV for different levels of missing records. Reported correlations are means of three replicates. The results suggest that the information on direct and maternal PBV provided by CD records is more reliable than the information provided by BW records. The difference was especially large when a high proportion of CD records were missing. Correlations above 0.96 and 0.95 for direct and maternal PBV, respectively, when missing 25% or 0% of the CD or BW records suggest that small changes would be predicted with a low proportion incomplete data. For genetic prediction of popular sires (with > 100 pogeny), a higher proportion of missing records could be tolerated. The results suggest that the bivariate threshold-linear animal model is useful for routine genetic evaluation of CD with incomplete field data.