The current modern time brings knowledge that help streamline the efforts of breeders and interfere with the originally untouchable action, fertilization. Genetics and reproduction have become the main interest of biotechnological research. It was develop and operating implementation of biotechnological methods such as artificial insemination, embryo transfer, longterm cryopreservation of semen or sexsorting semen, which became the impetus the topic of this thesis. Milk production performance of cattle is the property caused by a plethora of internal and external influences. Recent interest in professional public switched to other options affecting the milk yield, which is the sex of the calf. The aim of this study, processed in following up on the research GRANT QJ1510139 National information system of genetic evaluation of livestock, was to verify the influence of the sex of the calf on the milk yield of the mothers in our conditions. From previous studies (Hinde et al., 2014; Grasboll et al., 2015), arose the hypothesis, that gender affects the milk yield. To evaluate the two files have been used the measured data from the 1995-2015 with data on the sex of the calf and milk yields of the holstein dairy cattle in the control days provided by ČMSCH, a.s. From raw data has been created file of cows with three lactations, while each breeding had registered at least 3 control days on lactation. Abnormal data, wrong control days and sires with low number of daughters were eliminated as well. After editing the file contained 4.7 million milk yields from 197 thousends cows. Thesis worked with model based test-day access. Average daily milk yield in the file was 27.29 kg. In the method of least squares for 10 models were used the following effects: HTD (herd test day), Pohl (the effect of gender), Porl (effect of lactation), Skup (group) (for first lactation created by age of calving, calving period, service period and year of calving, for second and third lactations is the intervening period used instead of the age of the calving). Fixed regression the Legendre polynomial (LP) was used with 4 parameters. Milk yield fitted using LP showed normal shape of the lactation curve. According to the approved models is the effect of the sex of the calf on milk yield of the mother of the calf statistically insignificant. Having bulls increase productivity of milk yield about 0.07 kg/day which is about 21 kg per lactation. Genetic parameters were not examined due to the insignificance of the effect.

In this study the possibility to change to test-day models for genetic evaluation of production traits and somatic cell score of South African dairy breeds (i.e. Ayrshires, Guernseys, Holsteins and Jerseys) was investigated. Fixed Regression BLUP Animal Models were therefore developed, using test-day records of the first three lactations as repeated measures of the same trait. Milk, butterfat and protein yields were included in multitrait evaluations. A permanent environmental effect was fitted across lactations. Heritabilities estimated were comparable with other yield and somatic cell score estimates obtained from test-day models. Breeding values of qualifying sires were presented to INTERBULL for participation in the March 2005 test-runs. Genetic correlations between South Africa and other participating countries compared well with those amongst other countries, participating in these international evaluations. Trend validation tests were successful for all traits and breeds except for somatic cell score of the Guernsey breed, due to insufficient data for this trait. South Africa is now participating in routine INTERBULL evaluations in order to obtain MACE (multiple across country evaluation) breeding values, using this methodology. Further refinement of the model was tested, i.e. inclusion of a fixed calving year effect in the model and pre-adjusting records for heterogeneous variances due to days in milk and parity. This was investigated for the Jersey breed and recommended for implementation in the other South African breeds. South Africa’s methodology is now more comparable to that of the leading dairy producing countries of the world. / Thesis (PhD (Animal and Wildlife Sciences))--University of Pretoria, 2007. / Animal and Wildlife Sciences / unrestricted

Foram utilizados 263.390 registros de produção de leite do dia do controle (PDC) de 32.448 primeiras lactações de vacas da raça Holandesa obtidas no período de 1991 a 2001 para estimar componentes de variância e parâmetros genéticos, usando diferentes modelos estatísticos e a metodologia REML. Compararam-se as estimativas de valores genético (EVG) dos modelos de repetibilidade (MR) e de regressão aleatória (MRA) com às do modelo para as produções da lactação (P305). Nos MRA utilizaram-se duas curvas para descrever a trajetória da lactação: a polinomial logarítmica de Ali e Schaeffer (AS) e a exponencial de Wilmink (W), sob duas formas: a padrão e com uma modificação para reduzir a amplitude das covariáveis e contornar problemas de convergência (W Ú ). No ajuste da curva AS considerou-se heterogeneidade de variâncias residuais (VR) entre classes de dias em lactação (cDEL). A estimativa de herdabilidade para as P305 (0,27) foi menor do que àquelas para as PDC obtidas com MR, incluindo ou não a curva AS como sub modelo (0,30 e 0,43, repectivamente). As herdabilidades para as PDC por análises uni-caráter (0,22-0,36) e bi-caráter (0,23-0,33) foram menores no início e fim da lactação. As correlações genéticas entre produções de controles consecutivos foram superiores às estimadas entre controles do ínicio e do fim da lactação. As estimativas de herdabilidade por MRA com as curva AS (0,29-0,42) e W Ú (0,33-0,40) foram semelhantes, mas aquelas estimadas com a curva W (0,25-0,65) foram maiores do que as estimadas com as outras curvas pricipalmente no fim da lactação. Com os MRA as correlações genéticas foram próximas da unidade entre produções de controles consecutivos, mas reduziram com o aumento do intervalo entre controles. As estimativas de VR entre cDEL foram muito semelhantes variando de 4,15 a 5,11 para a curvas AS. Os desvios padrão (DP) para as EVG para produção de leite dos touros foram semelhantes entre os modelos AS, W Ú e MR. Entretando, os DP para as EVG foram maiores nos modelos para PDC do que no modelo a P305. As correlações entre as EVG para touros com o modelo P305 e os demais modelos aumentaram com o aumento no número de filhas e variaram de 0,66 (P305-W) a 0,92 (P305-AS e P305- W Ú ). As estimativas de tendência genética foram maiores para os MRA e menores para o MR se comparadas à estimativa obtida pelo modelo para P305. As estimativas de herdabilidade superiores para as PDC e as altas correlações (0,86-0,99) entre estas e a P305 indicam um potêncial de uso das PDC nas avaliações genéticas. Correlações genéticas heterogêneas (0,64-1,00) entre as PDC, medidas ao longo da lactação, não confimam a suposição de que elas são medidas repetidas do mesmo caráter. O MRA com a curva AS e VR homogênea foi o de melhor ajuste entre os avaliados, mas o modelo W Ú resultou em estimativas de herdabilidade mais estáveis ao longo da lactação. Na comparação dos resultados dos modelos conclui-se que o MRA com a curva AS e homonogeneidade de VR é a melhor alternativa, dentre as estudadas, para avaliação genética para produção de leite de gado Holandês no Brasil. / Covariance components and genetic parameters for milk yield from 263,390 test-day records of 32,448 first lactation Holstein cows were estimated using animal models by REML. Test-day repeatability (RM) and random regression (RR) models were compared to a 305-d lactation model (P305) to estimate breeding values. Random regression involved the five-parameter logarithmic Ali and Schaeffer function (AS) and the three-parameter exponential Wilmink function in standard (W) and modified (W*, to reduce the range of covariates and avoid convergence problems) form to model the shape of the lactation curve. Heterogeneous error variance (EV) for classes of days in milk (cDIM) was considered in adjusting the AS function. Heritability for milk yield by P305 (0.27) was smaller than those estimated for daily milk yield by RM including or not including a logarithmic sub-model (0.30 and 0.43, respectively). Heritability estimates for univariate (0.22-0.36) and bivariate models (0.23-0.33) for test-day milk yields were smallest during early and late lactation. Genetic correlations were higher for daily milk yield between consecutive test-days than between test-days at the beginning and end of lactation. Heritability estimates for AS (0.29-0.42) and W* (0.33-0.40) RR models were similar, but heritability estimates obtained for W (0.25-0.65) were higher than those estimated by other functions, particularly at the end of lactation. Genetic correlations between daily milk yield on consecutive test-days were close to unity, but they decreased with an increase of the interval between test-days. Estimates of EV for cDIM were quite similar, rating from 4.15 to 5.11 for the AS function. Standard deviations (SD) of bulls’s EBVs for milk yield were similar for AS, W* models and RM. However, SD of EBVs for bulls and cows were larger for test-day models than for P305 and for bulls they differed by -33.64 to 321.95 from the P305 depending on progeny number. SD of EBVs for bulls and cows for the W model were the largest ones. Correlation between EBVs among P305 and the other models for bulls increased as progeny number increased and ranged from 0.66 (W-P305) to 0.92 (AS-P305, W*-P305). Genetic trends were larger for RR models and smaller for RM than for P305. Larger heritability estimates for test-day models and large genetic correlations between test-day and lactation milk yields (0.86-0.99) indicated a potential use of test-day records in genetic evaluations. Heterogeneous genetic correlations (0.64-1.00) for test-day milk yields across lactation did not support the assumption that test-day records are repeated measures of the same trait. The AS homogeneous EV model was the most parsimonious and the best fit among those evaluated, but the W* model resulted in more stable heritability estimates for daily milk yield across lactation. RR models provide more information than the RM and describe the shape of the lactation curve from which EBVs for persistency can be derived. These results indicated AS as an alternative model for genetic evaluation for milk yield using test-day records of Holstein cattle in Brazil.

Made available in DSpace on 2014-06-11T19:26:06Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-04-29Bitstream added on 2014-06-13T18:54:01Z : No. of bitstreams: 1 santos_dja_me_jabo.pdf: 949817 bytes, checksum: 99fe4837bb2182ae9951f9ef2a71f250 (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Parâmetros genéticos para a produção de leite no dia do controle (PLDC) de primeiras lactações de vacas da raça Guzerá foram estimados utilizando modelo multicaracterísticas de dimensão finita (TMDO) e modelos de regressão aleatória (MRA). A produção acumulada em 305 dias (P305), duração da lactação (DL) e persistência da lactação (PS) também foram analisadas. Para o TMDO, foram analisadas as PLDC juntamente com a P305 e a DL, considerando como aleatórios, o efeito genético aditivo e o residual e, como fixo, o grupo de contemporâneos e a covariável idade da vaca ao parto. Para os MRA, foram considerados como aleatório, o efeito genético aditivo, de ambiente permanente e residual e como efeito fixo, o grupo de contemporâneos, os efeitos linear e quadrático da covariável idade ao parto e a curva média da população. Para os MRA foram consideradas as funções de ajuste de Wilmink (WL), Ali & Schaeffer (AS), uma combinação entre a função de Wilmink com polinômios ortogonais de Legendre (LM), polinômios ortogonais de Legendre (LEG) e funções B-spline (BS). Os efeitos aleatórios genético aditivo e de ambiente permanente foram modelados por meio destas funções, bem como a curva média da população, com a exceção dos modelos ajustados por funções BS que tiveram a curva média ajustada por polinômio de Legendre ou pela função de Ali & Schaeffer. O resíduo foi ajustado considerando variância homogênea ou em classes heterogêneas de variância residual. O modelo empregando funções BS cúbica com número de coeficientes de regressão aleatória igual cinco tanto para efeito genético aditivo como de ambiente permanente com a curva média modelada pela função de Ali & Schaeffer e resíduo ajustado por seis classes variância residual foi o mais adequado. Entretanto, os melhores MRA para cada função de ajuste, não apresentaram diferenças para... / Genetic parameters for milk production in the test day model (PLDC) for Guzerat dams’ first lactations were estimated by multitrait finite model (TMDO) and random regression models (MRA). The cumulative production at 305 days (P305), lactation length (DL) and lactation persistency (PS) were also analyzed. For TMDO, the PLDC were analyzed together with P305 and DL, considering the additive genetic effect and residual effect as random effects , the contemporary group as a fixed effect, and the age of dam at calving as a covariate. For MRA, additive genetic effect, permanent environmental effect and residual effect were considered as random effects and the contemporary group, the linear and quadratic covariate of age at calving and the average curve of the population as fixed effects. Also for the MRA, the Wilmink (WL) and the Ali & Schaeffer (AS) adjustment functions, a combination of the Wilmink function with Legendre orthogonal polynomials (LM), Legendre orthogonal polynomials (LEG) and B-spline functions (BS) were considered. The random additive genetic and permanent environmental effects were modeled by means of these functions, as well as the population average curve , with the exception of the adjusted models by the BS functions that had the average curve adjusted by the Legendre polynomial or by the Ali & Schaeffer function. The residual error was adjusted considering homogeneous variance or heterogeneous classes of residual variance. The model using cubic BS functions with random regression coefficient numbers equal to five for additive genetic effect as well as for permanent environmental with average curve modeled by the Ali & Schaeffer function and residual error adjusted for six classes of residual variance was the more appropriate. However, the best MRA for each adjustment function presented no differences in the estimates of genetic parameters and for order correlation ... (Complete abstract click electronic access below)

Made available in DSpace on 2014-06-11T19:32:15Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-02-26Bitstream added on 2014-06-13T20:03:29Z : No. of bitstreams: 1 bignardi_ab_dr_jabo.pdf: 1324029 bytes, checksum: eefcd7697892e45dbbe5b9ff67fbe3ce (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Parâmetros genéticos para a produção de leite no dia do controle (PLDC) de primeiras lactações de vacas da raça Holandesa foram estimados utilizando os modelos multicaracterísticas e modelos de regressão aleatória (MRA). Para os modelos multicaracterísticas foram analisados 15.896 controles mensais de produção de leite de 1.820 primeiras lactações de vacas da raça Holandesa. As análises foram realizadas por meio de sete modelos: multicaracterísticas padrão, três modelos de posto reduzido ajustando os primeiros 2,3 e 4 componentes principais genéticos e três modelos utilizando análise de fatores com 2,3 e 4 fatores. Para todos os modelos foram considerados os efeitos aleatórios genético aditivo e residual, e os efeitos sistemáticos do grupo de contemporâneo e da idade da vaca ao parto (efeito linear e quadrática) e do número de dias em lactação (efeito linear). A matriz de (co)variâncias residual, para todos os modelos, foi assumida ter posto completo. Os resultados indicam que somente dois componentes principais são requeridos para modelar a estrutura de (co)variâncias genéticas entre as produções de leite no dia do controle. Além disso, o modelo de posto reduzido diminui consideravelmente o número de parâmetros, sem reduzir a qualidade de ajuste. Para os MRA foram analisados 152.145 controles semanais de produção de leite de 7.317 primeiras lactações de vacas da raça Holandesa, provenientes de rebanhos da região Sudeste do Brasil. As produções de leite no dia do controle (PLDC) foram consideradas em 44 classes semanais de dia em lactação. Os grupos de contemporâneos foram definidos como rebanho-ano-semana do controle compondo 2.539 classes e, contendo, no mínimo, seis animais. O modelo utilizado incluiu os efeitos aleatórios genético aditivo direto, de ambiente permanente e o residual. Foram considerados como efeitos fixos, o grupo de... / Genetic parameters for first lactation test-day milk yields of Holstein cattle were estimated using multivariate and random regression models (RRM). For multivariate model a total of 15,896 individual monthly test-day milk yields (10 test-days), from 1,820 complete first lactations of Holstein cattle. A standard multivariate analysis, reduced rank analyses fitting the first 2, 3 and 4 genetic principal components, and analyses that fitted a factor analytic structure considering 2, 3 and 4 factors, were carried out. All models included also fixed effects of the contemporary groups, age of cow (linear and quadratic effects) and days in milk (linear effect). The residual covariance matrix was assumed to have full rank throughout. The results indicate that only two principal components are required to model the genetic covariance structure among the test-days milk yield. Furthermore, reduced rank model allows decreasing the number of parameter without reducing the goodness of fit considerably. For RRM A total of 152,145 weekly test-day milk yield records from 7,317 first lactations of Holstein cows distributed across 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of days in milk (DIM). The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM, and additive genetic and permanent environmental effects were estimated using B-splines. Residual variances were modeled by step function with 6 variance classes. Although all the model selection criteria utilized indicated the model employing cubic B-splines to both random effects, with 6 knots, a more parsimonious model ... (Complete abstract click electronic access below)

Resumo: Parâmetros genéticos para a produção de leite no dia do controle (PLDC) de primeiras lactações de vacas da raça Holandesa foram estimados utilizando os modelos multicaracterísticas e modelos de regressão aleatória (MRA). Para os modelos multicaracterísticas foram analisados 15.896 controles mensais de produção de leite de 1.820 primeiras lactações de vacas da raça Holandesa. As análises foram realizadas por meio de sete modelos: multicaracterísticas padrão, três modelos de posto reduzido ajustando os primeiros 2,3 e 4 componentes principais genéticos e três modelos utilizando análise de fatores com 2,3 e 4 fatores. Para todos os modelos foram considerados os efeitos aleatórios genético aditivo e residual, e os efeitos sistemáticos do grupo de contemporâneo e da idade da vaca ao parto (efeito linear e quadrática) e do número de dias em lactação (efeito linear). A matriz de (co)variâncias residual, para todos os modelos, foi assumida ter posto completo. Os resultados indicam que somente dois componentes principais são requeridos para modelar a estrutura de (co)variâncias genéticas entre as produções de leite no dia do controle. Além disso, o modelo de posto reduzido diminui consideravelmente o número de parâmetros, sem reduzir a qualidade de ajuste. Para os MRA foram analisados 152.145 controles semanais de produção de leite de 7.317 primeiras lactações de vacas da raça Holandesa, provenientes de rebanhos da região Sudeste do Brasil. As produções de leite no dia do controle (PLDC) foram consideradas em 44 classes semanais de dia em lactação. Os grupos de contemporâneos foram definidos como rebanho-ano-semana do controle compondo 2.539 classes e, contendo, no mínimo, seis animais. O modelo utilizado incluiu os efeitos aleatórios genético aditivo direto, de ambiente permanente e o residual. Foram considerados como efeitos fixos, o grupo de ... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Genetic parameters for first lactation test-day milk yields of Holstein cattle were estimated using multivariate and random regression models (RRM). For multivariate model a total of 15,896 individual monthly test-day milk yields (10 test-days), from 1,820 complete first lactations of Holstein cattle. A standard multivariate analysis, reduced rank analyses fitting the first 2, 3 and 4 genetic principal components, and analyses that fitted a factor analytic structure considering 2, 3 and 4 factors, were carried out. All models included also fixed effects of the contemporary groups, age of cow (linear and quadratic effects) and days in milk (linear effect). The residual covariance matrix was assumed to have full rank throughout. The results indicate that only two principal components are required to model the genetic covariance structure among the test-days milk yield. Furthermore, reduced rank model allows decreasing the number of parameter without reducing the goodness of fit considerably. For RRM A total of 152,145 weekly test-day milk yield records from 7,317 first lactations of Holstein cows distributed across 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of days in milk (DIM). The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM, and additive genetic and permanent environmental effects were estimated using B-splines. Residual variances were modeled by step function with 6 variance classes. Although all the model selection criteria utilized indicated the model employing cubic B-splines to both random effects, with 6 knots, a more parsimonious model ... (Complete abstract click electronic access below) / Orientador: Lucia Galvão de Albuquerque / Coorientador: Lenira El Faro Zadra / Coorientador: Roberto Augusto de Almeida Torres Júnior / Banca: Fabyano Fonseca e Silva / Banca: Maria Eugênia Zerlotti Mercadante / Banca: Humberto Tonhati / Banca: Henrique Nunes de Oliveira / Doutor

Foram utilizados 263.390 registros de produção de leite do dia do controle (PDC) de 32.448 primeiras lactações de vacas da raça Holandesa obtidas no período de 1991 a 2001 para estimar componentes de variância e parâmetros genéticos, usando diferentes modelos estatísticos e a metodologia REML. Compararam-se as estimativas de valores genético (EVG) dos modelos de repetibilidade (MR) e de regressão aleatória (MRA) com às do modelo para as produções da lactação (P305). Nos MRA utilizaram-se duas curvas para descrever a trajetória da lactação: a polinomial logarítmica de Ali e Schaeffer (AS) e a exponencial de Wilmink (W), sob duas formas: a padrão e com uma modificação para reduzir a amplitude das covariáveis e contornar problemas de convergência (W Ú ). No ajuste da curva AS considerou-se heterogeneidade de variâncias residuais (VR) entre classes de dias em lactação (cDEL). A estimativa de herdabilidade para as P305 (0,27) foi menor do que àquelas para as PDC obtidas com MR, incluindo ou não a curva AS como sub modelo (0,30 e 0,43, repectivamente). As herdabilidades para as PDC por análises uni-caráter (0,22-0,36) e bi-caráter (0,23-0,33) foram menores no início e fim da lactação. As correlações genéticas entre produções de controles consecutivos foram superiores às estimadas entre controles do ínicio e do fim da lactação. As estimativas de herdabilidade por MRA com as curva AS (0,29-0,42) e W Ú (0,33-0,40) foram semelhantes, mas aquelas estimadas com a curva W (0,25-0,65) foram maiores do que as estimadas com as outras curvas pricipalmente no fim da lactação. Com os MRA as correlações genéticas foram próximas da unidade entre produções de controles consecutivos, mas reduziram com o aumento do intervalo entre controles. As estimativas de VR entre cDEL foram muito semelhantes variando de 4,15 a 5,11 para a curvas AS. Os desvios padrão (DP) para as EVG para produção de leite dos touros foram semelhantes entre os modelos AS, W Ú e MR. Entretando, os DP para as EVG foram maiores nos modelos para PDC do que no modelo a P305. As correlações entre as EVG para touros com o modelo P305 e os demais modelos aumentaram com o aumento no número de filhas e variaram de 0,66 (P305-W) a 0,92 (P305-AS e P305- W Ú ). As estimativas de tendência genética foram maiores para os MRA e menores para o MR se comparadas à estimativa obtida pelo modelo para P305. As estimativas de herdabilidade superiores para as PDC e as altas correlações (0,86-0,99) entre estas e a P305 indicam um potêncial de uso das PDC nas avaliações genéticas. Correlações genéticas heterogêneas (0,64-1,00) entre as PDC, medidas ao longo da lactação, não confimam a suposição de que elas são medidas repetidas do mesmo caráter. O MRA com a curva AS e VR homogênea foi o de melhor ajuste entre os avaliados, mas o modelo W Ú resultou em estimativas de herdabilidade mais estáveis ao longo da lactação. Na comparação dos resultados dos modelos conclui-se que o MRA com a curva AS e homonogeneidade de VR é a melhor alternativa, dentre as estudadas, para avaliação genética para produção de leite de gado Holandês no Brasil. / Covariance components and genetic parameters for milk yield from 263,390 test-day records of 32,448 first lactation Holstein cows were estimated using animal models by REML. Test-day repeatability (RM) and random regression (RR) models were compared to a 305-d lactation model (P305) to estimate breeding values. Random regression involved the five-parameter logarithmic Ali and Schaeffer function (AS) and the three-parameter exponential Wilmink function in standard (W) and modified (W*, to reduce the range of covariates and avoid convergence problems) form to model the shape of the lactation curve. Heterogeneous error variance (EV) for classes of days in milk (cDIM) was considered in adjusting the AS function. Heritability for milk yield by P305 (0.27) was smaller than those estimated for daily milk yield by RM including or not including a logarithmic sub-model (0.30 and 0.43, respectively). Heritability estimates for univariate (0.22-0.36) and bivariate models (0.23-0.33) for test-day milk yields were smallest during early and late lactation. Genetic correlations were higher for daily milk yield between consecutive test-days than between test-days at the beginning and end of lactation. Heritability estimates for AS (0.29-0.42) and W* (0.33-0.40) RR models were similar, but heritability estimates obtained for W (0.25-0.65) were higher than those estimated by other functions, particularly at the end of lactation. Genetic correlations between daily milk yield on consecutive test-days were close to unity, but they decreased with an increase of the interval between test-days. Estimates of EV for cDIM were quite similar, rating from 4.15 to 5.11 for the AS function. Standard deviations (SD) of bulls’s EBVs for milk yield were similar for AS, W* models and RM. However, SD of EBVs for bulls and cows were larger for test-day models than for P305 and for bulls they differed by -33.64 to 321.95 from the P305 depending on progeny number. SD of EBVs for bulls and cows for the W model were the largest ones. Correlation between EBVs among P305 and the other models for bulls increased as progeny number increased and ranged from 0.66 (W-P305) to 0.92 (AS-P305, W*-P305). Genetic trends were larger for RR models and smaller for RM than for P305. Larger heritability estimates for test-day models and large genetic correlations between test-day and lactation milk yields (0.86-0.99) indicated a potential use of test-day records in genetic evaluations. Heterogeneous genetic correlations (0.64-1.00) for test-day milk yields across lactation did not support the assumption that test-day records are repeated measures of the same trait. The AS homogeneous EV model was the most parsimonious and the best fit among those evaluated, but the W* model resulted in more stable heritability estimates for daily milk yield across lactation. RR models provide more information than the RM and describe the shape of the lactation curve from which EBVs for persistency can be derived. These results indicated AS as an alternative model for genetic evaluation for milk yield using test-day records of Holstein cattle in Brazil.

Resumo: Parâmetros genéticos para a produção de leite no dia do controle (PLDC) de primeiras lactações de vacas da raça Guzerá foram estimados utilizando modelo multicaracterísticas de dimensão finita (TMDO) e modelos de regressão aleatória (MRA). A produção acumulada em 305 dias (P305), duração da lactação (DL) e persistência da lactação (PS) também foram analisadas. Para o TMDO, foram analisadas as PLDC juntamente com a P305 e a DL, considerando como aleatórios, o efeito genético aditivo e o residual e, como fixo, o grupo de contemporâneos e a covariável idade da vaca ao parto. Para os MRA, foram considerados como aleatório, o efeito genético aditivo, de ambiente permanente e residual e como efeito fixo, o grupo de contemporâneos, os efeitos linear e quadrático da covariável idade ao parto e a curva média da população. Para os MRA foram consideradas as funções de ajuste de Wilmink (WL), Ali & Schaeffer (AS), uma combinação entre a função de Wilmink com polinômios ortogonais de Legendre (LM), polinômios ortogonais de Legendre (LEG) e funções B-spline (BS). Os efeitos aleatórios genético aditivo e de ambiente permanente foram modelados por meio destas funções, bem como a curva média da população, com a exceção dos modelos ajustados por funções BS que tiveram a curva média ajustada por polinômio de Legendre ou pela função de Ali & Schaeffer. O resíduo foi ajustado considerando variância homogênea ou em classes heterogêneas de variância residual. O modelo empregando funções BS cúbica com número de coeficientes de regressão aleatória igual cinco tanto para efeito genético aditivo como de ambiente permanente com a curva média modelada pela função de Ali & Schaeffer e resíduo ajustado por seis classes variância residual foi o mais adequado. Entretanto, os melhores MRA para cada função de ajuste, não apresentaram diferenças para ... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Genetic parameters for milk production in the test day model (PLDC) for Guzerat dams' first lactations were estimated by multitrait finite model (TMDO) and random regression models (MRA). The cumulative production at 305 days (P305), lactation length (DL) and lactation persistency (PS) were also analyzed. For TMDO, the PLDC were analyzed together with P305 and DL, considering the additive genetic effect and residual effect as random effects , the contemporary group as a fixed effect, and the age of dam at calving as a covariate. For MRA, additive genetic effect, permanent environmental effect and residual effect were considered as random effects and the contemporary group, the linear and quadratic covariate of age at calving and the average curve of the population as fixed effects. Also for the MRA, the Wilmink (WL) and the Ali & Schaeffer (AS) adjustment functions, a combination of the Wilmink function with Legendre orthogonal polynomials (LM), Legendre orthogonal polynomials (LEG) and B-spline functions (BS) were considered. The random additive genetic and permanent environmental effects were modeled by means of these functions, as well as the population average curve , with the exception of the adjusted models by the BS functions that had the average curve adjusted by the Legendre polynomial or by the Ali & Schaeffer function. The residual error was adjusted considering homogeneous variance or heterogeneous classes of residual variance. The model using cubic BS functions with random regression coefficient numbers equal to five for additive genetic effect as well as for permanent environmental with average curve modeled by the Ali & Schaeffer function and residual error adjusted for six classes of residual variance was the more appropriate. However, the best MRA for each adjustment function presented no differences in the estimates of genetic parameters and for order correlation ... (Complete abstract click electronic access below) / Orientador: Humberto Tonhati / Coorientador: Maria Gabriela Campolina Diniz Peixoto / Banca: Lenir El Faro Zadra / Banca: Fernando Sebastián Baldi Rey / Mestre

La France présente une grande diversité de conditions pédoclimatiques et par conséquent des systèmes d'élevage très variés. Pourtant, les schémas de sélection actuels en bovins laitiers considèrent que les meilleurs reproducteurs sont les mêmes quel que soit le type de système d'élevage, c'est-à-dire qu'il n'existe pas d'interactions Génotype*Milieu. L'objectif de cette thèse est de mesurer les interactions Génotype*Milieu en France sur les caractères laitiers et fonctionnels dans les 3 races bovines laitières principales (Normande, Montbéliarde, Holstein).Un point crucial dans ce type d'étude est la façon de définir le milieu. L'innovation de cette thèse est l'utilisation des profils Troupeau-Jour de Contrôle. Ce sont des coproduits du modèle génétique basé sur les contrôles élémentaires. Ils reflètent la production permise par la conduite de troupeau au cours du temps. Ils présentent l'avantage d'être disponibles à partir des bases de données nationales et d'être uniquement le reflet de la conduite, contrairement à d'autres définitions qui mêlent effet génétique et effet d'environnement au sein de la définition du milieu ou qui se focalisent sur certains points précis de la conduite sans prendre en compte son effet global. La description des profils Troupeau-Jour de Contrôle de plus de 15000 élevages normands, montbéliards et holsteins par des méthodes de lissage de séries temporelles, d'analyses factorielles et de classification a permis de créer 2 définitions du milieu en vue de l'étude des interactions Génotype*Milieu : des milieux définis comme des groupes d'élevages aux conduites distinctes ou un milieu défini comme un continuum à travers une ou des variables synthétiques.L'importance des interactions Génotype*Milieu a été estimées à partir de 2 types de modèles : un modèle multicaractères qui valorise la définition du milieu sous forme de groupes d'élevages et un modèle de norme de réaction qui valorise, quant à lui, le milieu défini comme un continuum. Les avancées méthodologiques proposées dans cette thèse concernent les modèles de normes de réaction. Des approches permettant de prendre en compte plusieurs variables d'environnement au sein d'un même modèle et de les résumer au sein d'une matrice génétique de rang réduit sont mises en avant.Aucun reclassement n'a été mis en évidence : les meilleurs reproducteurs sont les mêmes quel que soit le système d'élevage. Les schémas des sélections actuels sont donc performants. Il existe tout de même une interaction Génotype*Milieu significative sous forme d'effet d'échelle : la variabilité des valeurs génétiques des animaux est plus importante dans les systèmes d'élevage plus intensifs. Cet effet d'échelle ne sera pas pris en compte dans les modèles d'évaluation génétique, en revanche, il est possible d'imaginer un indicateur utilisable sur le terrain pour mesurer les écarts de performances, dus à cet effet, auxquels il faut s'attendre. / Because of the diversity of pedoclimatic conditions in France, dairy farms have very diversified herd management systems. For this reason, some breeders question the efficiency of the existing breeding schemes for their own management system. To overcome these concerns, a genotype by environment interaction study at the French national level has been considered necessary. The aim of this thesis is to assess the presence of genotype by environment interactions in Normande, Montbéliarde and Holstein breeds for production and functional traits.A tricky point in genotype by environment interaction studies is the environmentdefinition. The innovation of this thesis deals with the use of Herd-Test Day profiles.They are co-products of the French test day model. They reflect the production dueto herd management over time. They are available in national databases and only reflect herd management effect contrary to other definitions in which there is a confusion between genetic and environmental effects in the environment definition or which focus on specific features of the herd management without taking into account its global effect. Herd Test Day profiles of more than 15,000 herds have been studied through time series smoothing, factor analysis and clustering methods. It led to 2 definitions of the environment for the genotype by environment interaction study : environments defined as herd groups or one to several environmental gradients.Genotype by environment interactions were assessed with 2 models : the multitrait model and the reaction norm model. The first one uses herd groups as definition of the environment whereas reaction norm model considers the environment as a gradient. Several methodological improvements have been suggested for reaction norm models : taking into account several environmental gradients in a reaction norm model and summarizing them through a reduced rank genetic matrix.No reranking has been shown : the best parents are the same whatever the herd management system. Consequently, current breeding schemes are relevant. However, a scale effect exists : the variability of animal breeding values is higher in intensive herds. Genetic models will not account for this scale effect. However, a tool useful for breeders could indicate the deviation between expected performances and actual performances due to this scale effect.

Hedi HAMMAMI (2009). Genotype by Environment Interaction for Production Traits of Holsteins Using Two Countries as Model: Luxembourg and Tunisia (Doctoral thesis). Gembloux, Belgium, Gembloux Agricultural University, 170 p., 30 tabl., 16 fig. Summary. Under globalization, breeding organizations are selecting animals and exchanging germplasm across various environments. Ignoring genotype by environment interaction (G x E) may affect the efficiency of breeding strategies and limit outcomes from cooperation between breeding programs. Quantifying the effectiveness of indirect selection and effects of G x E for different breeds is therefore necessary. The objective of this thesis was to evaluate the magnitude of G x E for milk yield using Luxembourg and Tunisian Holstein populations. In fact, these two countries rely considerably on importation of superior genes from diverse origins for their breeding programs. This study needed records on both the genotype and the environment. In the first part of this thesis, genetic ties between the two populations were studied. Additive relationships and genetic similarity were important and genetic links have been strengthened with time which allowed the analysis of the phenotypic expression of daughters of common sires under each of these tow production environments. In the second part, genetic parameters for production traits of Tunisian Holsteins were estimated by a test-day random regression model (RRTD). Heritability estimates for 305-d milk, fat and protein yields were low to moderate (0.12 to 0.18) suspecting difficulties of high-producing cows to express their potential under limiting production conditions. In the third part, G x E for milk yield and persistency were investigated using character state models, where milk yield in each country was considered as a separate trait, and where the country border delimitation was designed as an environmental character state. A RRTD sire model was applied and was extended to a RRTD animal model. Significant G x E was detected for milk yield and persistency by both models. Large differences in genetic and permanent environmental variances between the two countries were observed. Genetic correlations for 305-d milk yield and persistency between Luxembourg and Tunisian Holsteins were 0.50 and 0.43 (sire model) and 0.60 and 0.36 (animal model). Moreover, low rank correlations obtained between estimated breeding values of common sires translate a significant re-ranking between the two environments. At the end of this thesis, a herd management (HM) parameter reflecting feeding and management intensity was defined. Three HM levels were identified in each country and G x E was investigated within- and across-environments. Significant G x E was detected between the Tunisian HM levels, whereas, only heterogeneous genetic variance for milk yield with limited re-ranking of sires across the three Luxembourg environments was observed. Overall, this thesis shows that under constraining environmental effects, selection for adaptive traits among economically valuable traits under their specific conditions is needed for low-input systems. When satisfactory feeding resources, management and husbandry practices are available, high degree environmental sensitivity is desired and the use of a high yielding breed may be encouraged.