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Objetivou-se por meio deste trabalho relatar uma atividade desenvolvida com os cães da Associação de Resgate e Cuidado Animal - ARCA em Janaúba-MG por alunos do curso de Zootecnia da Universidade Estadual de Montes Claros (UNIMONTES) , visando proporcionar melhor bem-estar dos animais resgatados. A Associação de Resgate e Cuidado Animal de Janaúba foi criada no ano de 2011 por um pequeno grupo de protetores com o intuito de desenvolver ações em defesa dos animais. Por meio da intermediação de uma das docentes da UNIMONTES, que também é protetora da ARCA, foi proposto aos alunos uma atividade dentro da disciplina de Criação de Cães e Gatos, do curso de Zootecnia, objetivando a participação dos discentes em caminhadas semanais com os cães da presente Associação. As caminhadas foram realizadas entre os anos de 2016 e 2017, contando com a participação de 27 alunos. As atividades de convivência desenvolvidas entre os acadêmicos e os animais resgatados da ARCA proporcionaram melhoria do bem-estar físico e emocional dos cães do abrigo, bem como despertou atitudes de compaixão, respeito, senso de responsabilidade e dever nos alunos para com os animais abandonados.

The objective of this work was to report an activity developed with the dogs of the Association of Animal Rescue and Care - ARCA in Janaúba-MG by students of the Animal Science course at the State University of Montes Claros (UNIMONTES), aiming to provide better of the rescued animals. The Janaúba Animal Rescue and Care Association was created in 2011 by a small group of protectors in order to develop actions in defense of animals. Through the intermediation of one of the teachers at UNIMONTES, who is also the protector of ARCA, an activity was proposed to students within the discipline of Breeding Dogs and Cats, of the Zootechnics course, aiming at the participation of students in weekly walks with dogs of this Association. The walks were carried out between the years 2016 and 2017, with the participation of 27 students. The coexistence activities developed between the academics and the animals rescued from ARCA provided an improvement in the physical and emotional well-being of the shelter dogs, as well as aroused attitudes of compassion, respect, sense of responsibility and duty in the students towards the abandoned animals.

The objective was to study the stress level in dogs during grooming services in a pet shop. A total of 55 grooming services carried out in a pet shop in the city of Janaúba, MG, were evaluated and divided into four categories according to sex and body weight. The flowchart of the grooming process contained six steps that began with the transportation of dogs to the pet shop and finished with their return to the place of origin. Behavioral, physiological, and blood component evaluations were performed at different steps of the process. Changes in dog behavior and physiological parameters were observed primarily upon arrival at the pet shop and during drying. Employee characteristics also influenced dogs’ behaviors. However, dogs were able to thermoregulate and maintain the homeostasis of leukocytes, glucose and cortisol in the blood.

Records of 234 lactations from F1 Holstein x Gyr daughters of proven bulls were used in this study for the evaluation of productive and reproductive characteristics of cows. Data were collected from a private farm located in the municipality of Santo Antônio do Monte, MG, Brazil. The objective of this study was to evaluate the effects of Holstein bull's PTA milk (predicted transmitting ability) calving year, season, and parity on the productive and reproductive characteristics of F! cows. The productive characteristics analyzed were total milk production (TMP), average daily production (ADP), days in milk (DIM), and milk yield per day of calving interval (MYDCI). The studied reproductive characteristics were service interval (SI), calving interval (CI), and gestation length (GL). The results were subjected to statistical analysis and means for significant effects were compared using Duncan's test at a significance level of 5%. F1 animals efficiently expressed their genetic potential for milk production with an average total milk production of 7842.61 kg and average daily production of 24.53 kg. Means for days in milk, milk yield per day of calving interval, service interval, calving interval, and gestation length were 322.52 days, 20.73 kg, 106.0 days, 383.23 days, and 276.18 days, respectively. Properly managed F1 Holstein x Gyr daughters of proven bulls fed a balanced diet efficiently expressed their genetic potential for milk production without adverse effects on reproduction. Moreover, Holstein x Gyr cows should be selected based on parents' PTA for milk traits and other factors such as environmental conditions and management.

Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that genetic gain for body weight can be achieved by selection. Also, selection for body weight at 42 days of age can be maintained as a selection criterion.

Seleção para características do crescimento pode ser feita após ajustadas funções de crescimento para todos os animais sob seleção. Porém, a curva de crescimento de fêmeas é influenciada pelas gestações e lactações subsequentes. Neste trabalho, métodos são descritos para selecionar uma função que ajuste a curva de crescimento de fêmeas bovinas considerando-se os efeitos de variação de peso corporal devido a gestação e a lactação. Foram utilizados dados provenientes do Instituto Agronômico do Paraná, constituindo-se de 15.271 observações de pesos de 103 fêmeas, sendo 43 Nelore, 10 F1 Guzerá x Nelore, 29 F1 Red Angus x Nelore, 5 F1 Marchigiana x Nelore e 16 F1 Simental x Nelore. Comparou-se o ajuste das funções de Brody, Gompertz, Logística, Von Bertalanffy e Michaelis-Menten reparametrizada (MMr) aos efeitos do ganho de peso em função da idade, sendo adicionado a todas as funções o ganho de peso durante a gestação e a perda de peso na lactação de fêmeas da raça Nelore e Cruzadas. Ao ajustar as funções, observou-se um Coeficiente de Determinação Múltiplo Ajustado variando entre 0,7552 e 0,9267. Observou-se o menor Quadrado Médio do Resíduo e o Desvio Médio Absoluto para a função de MMr. Para descrição da curva de crescimento em função da idade das fêmeas, deve ser ajustada a função de MMr. Selection for growth characteristics can be done after fitting growth functions for all breeding animals. However, in the female population the growth curve is influenced by gestation and subsequent lactations. In this work methods are described to select a function that fits a growth curve of bovine females considering the varying effects of body weight due to gestation and lactation. Data from the Paraná Agronomic Institute (IAPAR) were used consisting of 15.271 weight observations of 103 females distributed as 43 Nelore, 10 F1 Guzerá x Nelore, 29 F1 Red Angus x Nelore, 5 F1 Marchigiana x Nelore and 16 F1 Simental x Nelore. The function adjustment of Brody, Gompertz, Logística, Von Bertalanffy and Michaelis-Menten reparametrized MMr were compared to the effects of weight gain as a function of age, adding to all functions the weight gain during gestation and the weight loss in the lactation of Nelore and crossbreed females. It was observed an Adjusted Coefficient of Multiple Determination varying from 0.7552 to 0.9267. Lower Residue Mean Square and Absolute Mean Deviation were observed for the MMr function. The MMr function must be adjusted in order to describe the growth curve as a function of the female age.

Random regression models (RRM) differ in terms of the functions used to describe the shape of lactation curves. The aim was to compare random regression models under different functions to describe the lactation curves from Holstein cows in herds of the state of Minas Gerais. A database of 28,118 production records was analyzed using the test-day records of 4,230 first parity cows from five herds. The Wilmink, Ali & Schaeffer and Legendre polynomial (orders 4, 5 and 6) functions were adjusted in RRM to model the mean production trend (fixed) and genetic and permanent environmental (random) effects. The residual variances were assumed to be constant throughout lactation. Analyses were performed using the AIREMLF90 program. Except for the model with the polynomial function of order 5, all models converged. The Wilmink function showed lower values for criteria based on the -2log (L), AIC and BIC. The model with the Legendre polynomial of order 6 showed lower residual variance. Heritability estimates were similar between functions, ranging from 0.07 to 0.18 and were higher from 215 days of lactation. From 155 days of lactation, genetic and permanent environmental correlations between successive controls are of high magnitude. The Wilmink function is the most suitable for the study of milk yields from primiparous Holstein cows. The selection of animals is possible from 155 days of lactation on. Permanent environmental effects have greater influence on the milk production at the end of lactation of primiparous cows and should be considered since they are important and may be cumulative throughout lactation.

Information about genetic parameters is essential for selection decisions and genetic evaluation. These estimates are population specific; however, there are few studies with dairy cattle populations reared under tropical and sub-tropical conditions. Thus, the aim was to obtain estimates of heritability and genetic correlations for milk yield and quality traits using pedigree and genomic information from a Holstein population maintained in a tropical environment. Phenotypic records (nA‚Â =A‚Â 36A‚Â 457) of 4203 cows as well as the genotypes for 57A‚Â 368 single nucleotide polymorphisms from 755 of these cows were used. Covariance components were estimated using the restricted maximum likelihood method under a mixed animal model, considering a pedigree-based relationship matrix or a combined pedigree-genomic matrix. High heritabilities (around 0.30) were estimated for lactose and protein content in milk whereas moderate values (between 0.19 and 0.26) were obtained for percentages of fat, saturated fatty acids and palmitic acid in milk. Genetic correlations ranging from -0.38 to -0.13 were determined between milk yield and composition traits. The smaller estimates compared to other similar studies can be due to poor environmental conditions, which may reduce genetic variability. These results highlight the importance in using genetic parameters estimated in the population under evaluation for selection decisions.

Considering the milk fatty acid influence on human health, the aim of this study was to compare gas chromatography (GC) and Fourier transform infrared (FTIR) spectroscopy for the determination of these compounds. Fatty acid content (g/100 g of fat) were obtained by both methods and compared through Pearson’s correlation, linear Bayesian regression, and the Bland–Altman method. Despite the high correlations between the measurements ( r = 0.60–0.92), the regression coefficient values indicated higher measures for palmitic acid, oleic acid, unsaturated and monounsaturated fatty acids and lower values for stearic acid, saturated and polyunsaturated fatty acids estimated by GC in comparison to FTIR results. This inequality was confirmed in the Bland–Altman test, with an average bias varying from −8.65 to 6.91 g/100 g of fat. However, the inclusion of 94% of the samples into the concordance limits suggested that the variability of the differences between the methods was constant throughout the range of measurement. Therefore, despite the inequality between the estimates, the methods displayed the same pattern of milk fat composition, allowing similar conclusions about the milk samples under evaluation.

Durante as últimas décadas, o melhoramento genético em bovinos leiteiros no Brasil baseou-se somente na importação de material genético, resultando em ganhos genéticos de pequena magnitude para as características de interesse econômico. Dessa forma, existe a necessidade eminente de avaliações genéticas dos animais sob condições nacionais de ambiente, de maneira a se prover um aumento na produção de leite aliado à qualidade. Neste contexto, o conhecimento sobre a composição do leite é de extrema importância para o entendimento de como alguns fatores ambientais e, principalmente genéticos podem influenciar no aumento dos conteúdos de proteína (PROT), gordura (GOR) e ácidos graxos (AG) benéficos e na redução da contagem de células somáticas, visando a melhoria da qualidade nutricional deste produto. Diante disso, o objetivo desse trabalho foi predizer os teores de AG de interesse usando regressão linear bayesiana, bem como estimar componentes de variância, coeficientes de herdabilidade e comparar modelos de diferentes ordens de ajuste por meio de funções polinomiais de Legendre, sob modelos de regressão aleatória. Amostras de leite foram submetidas a análises de cromatografia gasosa e espectrometria em infravermelho médio para determinação dos ácidos graxos. A comparação dos resultados obtidos por ambos os métodos foi realizada por meio da correlação de Pearson, análise de Bland-Altman e regressão linear bayesiana e, posteriormente, equações de predição foram desenvolvidas para os ácidos graxos mirístico (C14:0) e linoléico conjugado (CLA), a partir de regressões lineares simples e múltipla bayesiana considerando-se prioris nãoinformativas e informativas. Polinômios ortogonais de Legendre de 1ª a 6ª ordens foram utilizados para o ajuste das regressões aleatórias das características. A predição dos AG por meio da aplicação da regressão linear foi viável, com erros de predição variando entre 0,01 e 4,84g por 100g de gordura para o C14:0 e 0,002 e 1,85 por 100g de gordura para o CLA, sendo neste caso os menores erros de predição obtidos quando adotada a regressão múltipla com priori não informativa. Os modelos que melhor se ajustaram para GOR, PROT, C16:0, C18:0, C18:1c9, CLA, saturados (SAT), insaturados (INSAT), monoinsaturados (MONO) e poliinsaturados (POLI) foi o de 1ª ordem, e para escore de célula somática (ESC) e C14:0 o de 2ª ordem. As estimativas de herdabilidade obtidas variaram de 0,08 a 0,11 para GOR; 0,28 a 0,35 para PROT; 0,03 a 0,22 para ECS; 0,12 a 0,31 para C16:0; 0,08 a 0,14 para C18:0; 0,24 a 0,43 para C14:0; 0,07 a 0,17 para C18:1c9; 0,13 a 0,39 para CLA; 0,14 a 0,31 para SAT; 0,04 a 0,14 para INSAT; 0,04 a 0,13 para MONO; 0,09 a 0,20 para POLI e 0,12 para PROD, nos modelos que melhor se ajustaram. Concluise que melhorias na qualidade nutricional do leite podem ser obtidas por meio da inclusão das características produtivas e do perfil de ácidos graxos em programas de seleção genética. During the last decades, genetic improvement in dairy cattle in Brazil was based only on the importation of genetic material, resulting in small genetic gains for economic interest traits. There is a perceived need for genetic evaluation under national environment conditions to provide an increase in milk production allied to quality. In this context, the knowledge of the milk composition is very important for understanding how certain environmental factors and especially genetic factors may influence the increase in protein content (PROT), fat (FAT), beneficial fatty acids (FA) and in reducing somatic cell count, aiming to improve the nutritional quality of this product. The aim of this study was to predict the levels of interest FA using Bayesian linear regression and estimate the components of variance, coefficients of heritability and compare models with different orders of adjustment by Legendre polynomials functions, in random regression models. Milk samples were subjected to gas chromatography analysis and mid-infrared spectrometry for the determination of fatty acids. The comparison of the results obtained by both methods was performed using Pearson\'s correlation, Bland-Altman analysis and Bayesian linear regression, subsequently, prediction equations were developed for the fatty acids myristic (C14:0) and conjugated linoleic (CLA) from simple linear regressions and multiple Bayesian considering non-informative and informative priors. Legendre orthogonal polynomials from 1st to 6th orders were used to fit the random regression of the traits. That was viable the prediction of FA by applying the linear regression with prediction errors ranging from 0.01 to 4.84 g per 100 g of fat for C14:0 and 0.002 to 1.85 per 100 g of fat for CLA, in this case the smaller prediction errors obtained when adopted the multiple regression with non-informative priori. The models that best fit for FAT, PROT, C16:0, C18:0, C18:1C9, CLA, saturated (SAT), unsaturated (UNSAT), monounsaturated (MONO) and polyunsaturated (POLY) was the one of 1st order and for somatic cell scores (SCS) and C14:0 the one of 2nd order. The estimates of heritability ranged from 0.08 to 0.11 for FAT; 0.28 to 0.35 for PROT; 0.03 to 0.22 for SCS; 0.12 to 0.31 for C16:0; 0.08 to 0.14 for C18:0; 0.24 to 0.43 for C14:0; 0.07 to 0.17 for C18:1C9; 0.13 to 0.39 for CLA; 0.14 to 0.31 for SAT; 0.04 to 0.14 for UNSAT; 0.04 to 0.13 for MONO, 0.09 to 0.20 for POLY and 0.12 for PROD, in the models that best fit. We conclude that improvements in the nutritional quality of milk can be obtained through the inclusion of productive traits and fatty acid profile in genetic selection programs.

Foram utilizados 1.129 animais, 298 F1 e 831 F2 para gordura intramuscular (GIM, %) e ganho de peso (GP, g/dia) e 324 F1 e 805 F2 para espessura de toucinho (ET, mm), obtidos por meio do cruzamento de suínos machos da raça Meishan e fêmeas Large White e Landrace. Os animais foram genotipados para marcadores moleculares cobrindo todo o genoma. Foram estudados os cromossomos 1, 2, 4, 5, 6, 7, 13, 14 e19 para ET e GIM e os cromossomos 1, 2, 4, 6, 7, 8, 13, 17 e19 para GP entre 25 e 90 kg de peso vivo (PV). Análises de QTL usando metodologia Bayesiana foram aplicadas mediante o modelo genético estatístico combinando os efeitos Poligênico Infinito (MPI), Poligênico Finito (MPF) e de QTL. Os sumários dos parâmetros estimados foram baseados nas distribuições marginais a posteriori obtidas por Cadeia de Markov, algoritmo de Monte Carlo (MCMC). De modo geral, por meio dos resultados, foi possível evidenciar um QTL para ET, independentemente da priori estudada. Não foi possível detectar QTL para as características GIM e GP com a aplicação desta metodologia, o que pode estar relacionado aos marcadores não-informativos ou à ausência de QTL segregando nos cromossomos estudados. Há vantagens em analisar dados experimentais ajustando modelos genéticos combinados e não considerando unicamente o modelo poligênico ou o oligogênico. As análises ilustraram a utilidade e aplicabilidade do método Bayesiano no qual foram utilizados modelos finitos. Genome scan was used to identify chromosomal regions and genes that control quantitative trait loci (QTL) of economic importance using 1129 animals from F1 and F2 populations obtained from crosses between Meishan and commercial Dutch breeds (Large White and Landrace). Animals were genotyped for molecular markers covering the entire genome. The chromosomes 1, 2, 4, 5, 6, 7, 13, 14 and 19 were studied for intramuscular fat (IMF, %) and backfat thickness (BT, mm) and the chromosomes 1, 2, 4, 6, 7, 8, 13, 17 and 19 for body weight gain (BWG, g/day) from 25 to 90 kg of live weight. QTL analyses using Bayesian methodology were applied to genetic model combining the marker-linked QTL, Finite Polygenic (FPM) and Infinite Polygenic (IPM) effects. The summaries of estimated parameters were based on Marginal posterior distributions obtained by Markov chain Monte Carlo (MCMC) methods. In general, the results indicated one QTL for BT, independent of the prior. It was not possible to detect QTL for IMF or BWG probably due to non-informative markers or to the absence of QTL segregating in the studied chromosomes. This study suggested the advantage of using a combination of genetic models to analyze experimental data instead of fitting only the polygenic or the oligogenic model.