Buffalos milk yield analysis using random regression models

Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed), daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genetic de Bubalinos (PROMEBUL) and from records of EMBRAPA Amazonia Oriental - EAO herd, located in Belem, Para, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre's polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve) and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre's polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.

Multi-trait and random regression mature weight heritability and breeding value estimates in Nelore cattle

Mature weight breeding values were estimated using a multi-trait animal model (MM) and a random regression animal model (RRM). Data consisted of 82 064 weight records from 8 145 animals, recorded from birth to eight years of age. Weights at standard ages were considered in the MM. All models included contemporary groups as fixed effects, and age of dam (linear and quadratic effects) and animal age as covariates. In the RRM, mean trends were modelled through a cubic regression on orthogonal polynomials of animal age and genetic maternal and direct and maternal permanent environmental effects were also included as random. Legendre polynomials of orders 4, 3, 6 and 3 were used for animal and maternal genetic and permanent environmental effects, respectively, considering five classes of residual variances. Mature weight (five years) direct heritability estimates were 0.35 (MM) and 0.38 (RRM). Rank correlation between sires' breeding values estimated by MM and RRM was 0.82. However, selecting the top 2% (12) or 10% (62) of the young sires based on the MM predicted breeding values, respectively 71% and 80% of the same sires would be selected if RRM estimates were used instead. The RRM modelled the changes in the (co)variances with age adequately and larger breeding value accuracies can be expected using this model. © South African Society for Animal Science.

Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data. © FUNPEC-RP.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

Genetic parameters for body weight in buffaloes (Bubalus bubalis) in Colombia using random regression models

The objective of this research was to estimate (co) variance functions and genetic parameters for body weight in Colombian buffalo populations using random regression models with Legendre polynomials. Data consisted of 34,738 weight records from birth to 900 days of age from 7815 buffaloes. Fixed effects in the model were contemporary group and parity order of the mother. Random effects were direct and maternal additive genetic, as well as animal and maternal permanent environmental effects. A cubic orthogonal Legendre polynomial was used to model the mean curve of the population. Eleven models with first to sixth order polynomials were used to describe additive genetic direct and maternal effects, and animal and maternal permanent environmental effects. The residual was modeled considering five variance classes. The best model included fourth and sixth order polynomials for direct additive genetic and animal permanent environmental effects, respectively, and third-order polynomials for maternal genetic and maternal permanent environmental effects. The direct heritability increased from birth until 120 days of age (0.32 +/- 0.05), decreasing thereafter until one year of age (0.18 +/- 0.04) and increased again, reaching 0.39 +/- 0.09, at the end of the evaluated period. The highest maternal heritability estimates (0.11 +/- 0.05), were obtained for weights around weaning age (weaning age range is between 8 and 9.5 months). Maternal genetic and maternal permanent environmental variances increased from birth until about one year of age, decreasing at later ages. Direct genetic correlations ranged from moderate (0.60 +/- 0.060) to high (0.99 +/- 0.001), maternal genetic correlations showed a similar range (0.41 +/- 0.401 and 0.99 +/- 0.003), and all of them decreased as time between weighings increased. Direct genetic correlations suggested that selecting buffalos for heavier weights at any age would increase weights from birth through 900 days of age. However, higher heritabilities for direct genetic weights effects after 600 days of age suggested that selection for these effects would be more effective if done during this age period. A greater response to selection for maternal ability would be expected if selection used maternal genetic predictions for weights near weaning. (C) 2013 Elsevier B.V. All rights reserved.

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

Random regression models using different functions to model milk flow in dairy cows

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multicollinearity and financial constraint in investment decisions: a bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Quality of life and satisfaction of patients wearing implant-supported fixed partial denture: a cross-sectional survey of patients from Aracatuba city, Brazil

ObjectivesThe aim of this study was to evaluate the quality of life and satisfaction of patients wearing implant-supported fixed partial dentures.Materials &methodsA total of 106 patients were selected and submitted to clinical examination and collection of the demographic data for evaluation of the implant-supported fixed dentures conditions. All participants agreed to answer to the Oral Health Impact Profile (OHIP-EDENT) questionnaire and another questionnaire about satisfaction with the implant-supported prostheses. The patients were classified into the following three groups for statistical analysis: patients wearing splinted implant-supported prosthesis (E), patients wearing single implant-supported prosthesis (U), and patients wearing single implant-supported prosthesis associated with splinted prosthesis (E+U). Kruskal-Wallis test was used to compare the answers between the groups, and a logistic regression model was measured to verify the relation between variables of the patients and the questionaries'items.ResultsThere were significant differences among groups (P=0.006) for discomfort during surgery itself of the satisfaction questionnaire. The marital status, groups, and hygiene condition were significant mainly for physical pain item.ConclusionsIt was concluded that the patients presented high level of satisfaction and quality of life for the most of the items evaluated as well as the groups showed similar results.

Random regression models for milk, fat and protein in Colombian Buffaloes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genotype x environment interaction for age at first calving, scrotal circumference, and yearling weight in Nellore cattle using reaction norms in multitrait random regression models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estimation of genetic parameters for partial egg production periods by means of random regression models

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Fertility Rates Following Fixed-Time Artificial Insemination in Dairy Heifers in a Practical Progesterone-Based Protocol

Background: In bovines, more efficient management practices are important for maximizing profitability. In order to increase the pregnancy rates in artificial insemination (AI) programs, several hormonal protocols were developed to synchronize the follicular wave and the moment of ovulation in beef and dairy cattle. In dairy cattle, detection of estrus can be difficult due to a number of factors including the incidence of silent estrus. Hormonal treatments designed to control both luteal and follicular function has permitting efficient synchronizations of time of ovulation. Thus, the AI can be performed in a large number of animals on a fixed schedule without the need for detection of estrus. Using these management techniques, the fixed-time artificial insemination (TAI) can overcome the problem of accurate estrus detection and help in reducing the incidence of repeat breeding. In addition, with TAI in cattle operations, it is possible to facilitate management practices and commercialization, and to reduce the time and semen wasting with animals inseminated at incorrect times. The investigation of practical and efficient TAI protocols is important for reducing the labor and animal handling of TAI in dairy cattle, as well as for increasing the profitability of the cattle management system. This study was carried out in order to investigate the effectiveness of TAI in dairy heifers treated with a practical progesterone-based protocol.Materials, Methods & Results: This experiment was conducted at the university farm located in southwestern Brazil, during May 2009. Thirty-nine cycling crossbred dairy heifers were employed in this study. All animals received a single intramuscular injection of estradiol benzoate and intravaginal progesterone releasing device in a random stage of the estrous cycle (Day 0). on day 7 the animals were treated with PGF2a analogue and on day 9 the device was removed. Forty-eight hours after the device removal (day 11) a synthetic analogue of GnRH was administered and the animals were fixed-time artificially inseminated at the time of GnRH injection. The inseminations were performed using four different batches from the same Holstein bull. Among the heifers that were synchronized (87.2%), 30.8% ovulated until 24 h after TAI and 56.4% ovulated between 24 and 32 h after TAI. The conception rate was 61.5%. No effects of ovulation time in conception rates were detected. The conception rate from heifers that ovulated until 24 h after TAI was 58.3% and from heifers that ovulated between 24 and 32 h after TAI was 77.3%. The mean of ovulatory follicle in heifers that ovulated until 24 h was 14.3 mm and in heifers that ovulated between 24 and 32 h was 11.9 mm.Discussion: Taking together, the findings of the present study, along with those of others, emphasize the concept that development of practical methods for TAI offers significant advantages to dairy producers if conception rates are close or greater to those obtained after breeding at detected estrus. Thus, the results of the present study reinforce the possibility of making dairy cattle production more cost-effective using TAI. In conclusion, with the progesterone-based TAI protocol of the present experiment all synchronized animals ovulated up to 32 h after GnRH+TAI and no effects of ovulation time related to conception rate was detected. The exogenous control of luteal and follicular development facilitated the reproductive management and animal handling. Also, inseminating the heifers at the moment of GnRH injection in a progesterone-based TAI protocol is a practical strategy and provided satisfactory results regarding ovulation and conception rates in dairy heifers.

Detection of bovine herpesvirus 5 (BoHV-5) in formalin-fixed, paraffin-embedded bovine brain by nested PCR in Colombian cattle

Fifteen cases of viral meningoencephalitis in Colombian cattle were tested by nested PCR analysis for the detection of bovine herpesvirus 5 (BoHV-5). All fatal cases had shown severe neurological signs and had occurred following natural outbreaks of the disease. The neurological infection was histologically characterized by mild to moderate inflammatory changes in the brain and cerebellum, including meningitis, mononuclear perivascular cuffing, gliosis, haemorrhage, and the presence of Gitter cells (macrophages) accompanying large areas of malacia. No intranuclear inclusion bodies were seen in any of the cases. Results from BoHV-5 molecular extraction analyses showed there were five positive cases thus confirming the presence of the virus in Colombia.