Genetic evaluation of Alpine goats using different milk control intervals

The objective of this study was to compare the results of genetic evaluations by using different milk control intervals to reduce the cost of milk yield controls without harming the quality of genetic evaluation of the animals. We analyzed test day milk yield data from the Goat Sector of Universidade Federal de Viçosa. After editing and checking for errors in the database, there were 20,710 records of test day milk yield for the 667 first lactations of Alpine goats, constituting the complete file, with 7-day control intervals. Information on specific weeks was excluded from the complete file to create files with data on control intervals of 15, 21, and 28 days. The RENPED program was used to recode the pedigree and data files and correct pedigree errors; the WOMBAT program was used for genetic evaluations of the 4 files. The following comparison criteria of analysis results were used: logarithm of the function of the restricted maximum likelihood, length of the analyses in seconds, Pearson and Spearman correlations, and common elimination percentage among the areas below the regression curve of the genetic values of the animals. Overall, it is recommended that a 7-day interval among milk controls should be used in breeding programs and farms with a high technical level. Intervals of 14 and 21 days can achieve satisfactory results combined with a lower data collection cost for farms with an average-to-low technical level, less effective size, and genetic variability that depend on external genetic material for genetic improvement

Genetic and environmental factors that influence production and quality of milk of Alpine and Saanen goats

Data from 1279 lactations of 783 Alpine and Saanen goats of the herd of our university in Minas Gerais, Brazil, were used to study environmental effects on and to estimate genetic parameters for milk production until 270 days of lactation (MP270) and for production and percentages of fat (PFAT and %FAT), protein (PPROT and %PROT), lactose (PLACT and %LACT), and total dry extract (PEXTR and %EXTR). Environmental effects were estimated by a statistical model that included contemporary group effect, type of kidding, genetic grouping, and kidding order. A multi-trait animal model with animal and permanent environment random effects was used to estimate genetic parameters and the significant environmental effects (fixed). Contemporary group influenced all traits; genetic grouping did not influence %LACT; type of kidding did not influence PFAT, %PROT or %LACT, and kidding order did not influence %FAT or %EXTR. Heritability and repeatability estimates were, respectively, 0.19 and 0.37 (MP270); 0.10 and 0.20 (PFAT); 0.12 and 0.24 (PPROT); 0.15 and 0.27 (PLACT); 0.13 and 0.24 (PEXTR); 0.21 and 0.34 (%FAT); 0.39 and 0.44 (%PROT); 0.17 and 0.29 (%LACT); 0.31 and 0.47 (%EXTR). Estimates of genetic correlations among MP270 and production of milk constituents were positive and high, but correlations between MP270 and %FAT, MP270 and %PROT, MP270 and %ESTR were moderate and negative. These heritability estimates show that satisfactory genetic gains can be obtained by selection, especially for milk constituents

Estudo de características de produção de matrizes de corte por meio da análise de componentes principais Study of meat-type chickens production traits by principal components analysis

Avaliou-se o descarte de variáveis de produção, em análises de componentes principais, de três linhagens de matrizes de corte do Programa de Melhoramento Genético da Universidade Federal de Viçosa, utilizando informações de 270 aves, sendo 90 de cada linhagem. As características analisadas foram dias para postura do primeiro ovo (DPPO), taxa de postura da 22ª a 56ª semana (TP), peso médio individual na 32ª (PMI1), na 40ª (PMI2), na 48ª (PMI3), na 56ª (PMI4) e na 64ª semana (PMI5) e peso médio do ovo, obtido pela média da pesagem de três ovos na 32ª (PMO1), na 40ª (PMO2), na 48ª (PMO3), na 56ª (PMO4) e na 64ª semana (PMO5). Dos 12 componentes principais, sete apresentaram variância menor do que 0,7 (autovalor menor do que 0,7), sugerindo-se sete variáveis para descarte. As variáveis descartadas foram aquelas que apresentaram maiores coeficientes, em valor absoluto, a partir do último componente principal. Observou-se correlação linear simples e significativa entre as variáveis descartadas e as não descartadas, que indica redundância de variáveis, razão do descarte. Recomendam-se as variáveis: DPPO, TP, PM14, PMO1 e PMO4 para o estudo de características da produção de matrizes de frango de corte por meio da análise de componentes principais.<br>Records of 270 meat-type chickens from three lines, 90 of each one, were used to discard variables in a principal component analysis. Data were obtained from meat-type chicken lines of the genetic breeding program of the Universidade Federal de Viçosa. The following traits were evaluated: days at first egg (DFE), egg production rate (EPR) from 22nd to 56th week, body weights at 32nd (BW1), 40th (BW2), 48th (BW3), 56th (BW4), and 64th weeks of age (BW5), and average of three egg weights, at 32nd (EW1), 40th (EW2), 48th (EW3), 56th (EW4) and at 64th weeks (EW5). From the 12 principal components, seven showed variance lower than 0,7 (eigenvalue lower than 0,7), suggesting seven variables to be discarded. Variables which showed the highest coefficients, in absolute value, in the last principal component were discarded. Highly correlated variables with the smaller principal components variance explain a small part of the whole variation. In addition, discarded variables in function of the significant simple linear correlation with the nondiscorded variable, were considered redundants. The variables DFE, EPR, BW4, EW1, and EW4 are recommended for principal component analysis of broiler matrix

Precocidade sexual, eficiência reprodutiva e desempenho produtivo de matrizes jovens Nelore e cruzadas

RESUMO Com o objetivo de avaliar matrizes da raça Nelore (NE) e cruzadas 1/2 Angus + 1/2 Nelore (AN), 1/2 Caracu + 1/2 Nelore (CN) e 1/2 Senepol + 1/2 Caracu (SC) quanto à precocidade sexual em sistemas de recria a pasto, eficiência reprodutiva e desempenho produtivo das matrizes em cada grupo genético (GG), matrizes desses grupos foram produzidas por três safras. Foram avaliadas 40 matrizes AN, 37 CN, 51 NE e 43 SC. Para prenhez precoce, matrizes AN apresentaram taxa de prenhez de 92,2% contra 29,1% para CN, 22,6% para SC e 1,1% para NE. Na prenhez convencional, matrizes AN obtiveram 99,4%, 98,8% para CN, 84,4% para SC e 80,0% para NE. A reconcepção das matrizes AN foi 86,3%, 75,1% de CN, 49,6% de NE e 43,6% de SC. Matrizes AN tiveram menor média de idade ao primeiro parto em meses, 26,36±0,79, contra 31,33±0,86 para CN, 33,51±0,98 para SC e 38,08±0,74 para NE. Para peso ao desmame, crias three-cross das AN pesaram mais que as F1 das NE, por volta de 19%. Para relação de peso ao desmame, não houve diferenças estatísticas entre GG. Matrizes AN foram superiores às demais nos aspectos reprodutivos e produtivos, seguidas das matrizes CN

Identificação e modelagem da autocorrelação residual no ajuste do modelo de Wood às curvas de lactação de cabras Identification and modeling of residual autocorrelation in the adjustments of Wood’s model to lactation curves of goats

Objetivou-se com este trabalho apresentar uma metodologia de identificação e modelagem da autocorrelação residual considerando ajustes individuais do modelo de Wood às lactações de cabras leiteiras e também avaliar a influência de tal modelagem na qualidade do ajuste. O modelo de Wood foi ajustado individualmente às lactações, considerando três estruturas residuais. Na primeira, assumiu-se independência dos erros (EI) para todas as lactações, na segunda, assumiu-se a estrutura de erros autoregressivos de primeira ordem (AR1) para todas as lactações e, na terceira, nomeada por EI-AR1, foi utilizada a estrutura de erros AR1 somente para as lactações que apresentaram autocorrelação residual, segundo o teste de Durbin-Watson, e de EI para as demais. As três situações de ajuste foram comparadas pelos percentuais de convergência e pelas médias dos quadrados médios dos erros (QME) e dos coeficientes de determinação ajustados (R²aj). As médias dos QME e dos R²aj apresentaram valores semelhantes nas três situações de estrutura residual. No entanto, o modelo com estrutura EI-AR1 apresentou maior convergência, o que consiste em uma vantagem, já que permite que um maior número de animais seja avaliado quanto à sua curva de lactação. Portanto, em função da maior convergência obtida, o ajuste do modelo de Wood com a estrutura EI-AR1 consiste na opção mais indicada para grandes conjuntos de dados.<br>The objective of this research was to present a methodology for identification and modeling of residual autocorrelation considering individual adjustments of the Wood's model to lactation dairy goats and evaluate the influence of such modeling in the quality of adjustment. The Wood's model was adjusted individually for lactations in three different ways, the first have assumed independence of errors (IE) for all lactations, the second have assumed autoregressives first order errors (AR1) for all lactations and the third, named (IE-AR1), was used the AR1 errors structure only for lactations that showed residual autocorrelation according to Durbin-Watson test, and the IE errors structure for the other lactations. The three ways of adjustment were compared by the percentage of convergence and the average of the mean square errors (MSE) and coefficients of determination adjusted (R²adj). The average of MSE and R²aj were very similar in the three cases of residual structure. However, the model with IE-AR1 residual structure showed a higher rate of convergence, which is an advantage, as it allows a greater number of animals are evaluated for their lactation curve. Therefore, due to the increasing convergence obtained, the fit of the Wood's model with IE-AR1 residual structure is the option most suitable for large data sets