Multiple trait and random regression models using linear splines for genetic evaluation of multiple breed populations.

This study aimed to verify if random regression models using linear splines (RRMLS) are suitable for identifying genetic parameters in multiple-breed populations and also to investigate whether an interaction exists between the breeding value (BV) of sires and their progeny breed group. Ten populations were simulated by crossing 2 breeds with distinct genetic variance and nonzero segregation variance. To obtain the genetic parameters, 2 models were used: a multiple-trait model (MULT), in which the trait was considered distinct when evaluated in each group (1/2P1 + 1/2P2, 5/8P1 + 3/8P2, and 3/4P1 + 1/4P2), and a RRMLS with the spline polynomial knots adjusted to these same groups. The genetic parameters estimated through MULT and RRMLS did not differ from the simulated values. The correlations between BV (simulated and estimated) of animals were high and varied from 0.74 to 0.76, which indicates the efficiency of using MULT and RRMLS for predicting BV. Using field data, the traits age at first calving (AFC), first lactation length (LL), and 305-d milk yield (MY-305) from a multiple-breed population of Holstein-Gyr cattle were analyzed. The BV of animals were modeled through RRMLS with 3, 5, and 7 knots, distributed in accordance with the fraction of Holstein breed in each progeny breed group. It was verified that RRMLS with 7 knots for adjusting mean trajectories and genetic effects, with homogeneous residual variance, best fit AFC and LL. For MY-305, the best fit for mean trajectory and genetic effects was the RRMLS with 5 knots and with homogeneous residual variance. The posterior means of heritability varied from 0.21 to 0.48, 0.21 to 0.38, and 0.10 to 0.33 for AFC, LL, and MY-305, respectively. Estimates from genetic parameters obtained by using RRMLS with field data showed that this model is a useful tool for genetic evaluations of populations formed by a great number of breed groups. An interaction occurred between the BV of sires and their progeny breed group, and the genetic parameters for AFC, LL, and MY-305 traits from a multiple-breed population depend on breed composition of the progeny from which the evaluations are based.

Modelos para avaliação genética da produção de leite no dia do controle nas três primeiras lactações / Models for genetic evaluation of milk yield on the day of control in the three first lactations

Objetivou-se verificar se a utilização do modelo autorregressivo (MAR) é adequada para obtenção de parâmetros genéticos para produção de leite no dia do controle (PLDC) de bovinos leiteiros da raça Gir. Foram analisados 125.191 registros de produções diárias, nas três primeiras lactações, por meio dos modelos de repetibilidade (MREP) e MAR. No MREP, foi considerado o efeito de ambiente de curto prazo; no MAR, foi considerado, também, o efeito de ambiente de longo prazo. Os modelos foram comparados por meio do logaritmo da função de máxima verossimilhança (−2logL) . A herdabilidade estimada pelo MREP foi 0,18; no caso do MAR, as estimativas para primeira, segunda e terceira lactações foram 0,32, 0,28 e 0,26, respectivamente. A estimativa de autocorrelação dos componentes de variância de longo prazo foi próxima de zero, e as de curto prazo foram de alta magnitude para primeira (0,79), segunda (0,79) e terceira (0,81) lactações. Logo, a influência do ambiente de curto prazo dentro de cada lactação não é a mesma. O valor de −2logL mais próximo de zero foi obtido para o MAR (-294.884,7778) em relação ao MREP (-329.266,4810). Assim, o MAR é adequado para obtenção de estimativas de parâmetros genéticos para PLDC nas três primeiras lactações de bovinos leiteiros.(AU)

Aimed to verify if the autoregressive model (MAR) is adequate to obtain genetic parameters for Gyr dairy cattle milk yield on the test day in the three first lactations. Analysis was performed on 125,191 records of daily production of 9,242 cows using repeatability model (MREP) and MAR. On MREP, a long-term environment was considered, on MAR, the short-term environment was also taken into consideration. The models were compared by logarithm of the maximum likelihood function (−2logL) . The heritability estimated using the MREP model was 0.18, while the heritability estimated by MAR for first, second, and third lactations were 0.32, 0.28 and 0.26, respectively. The autocorrelation estimates of the components of long-term variance were close to zero, and those of the short-term were of high magnitude for first (0.79), second (0.79) and third (0.81) lactations. Therefore, the influence of the short-term environment within each lactation is not the same. The value of −2logL closer to zero was obtained for MAR (-294,884.7778) in relation to MREP (-329,266.4810). Thus, MAR is suitable for obtaining genetic parameters estimates for PLDC in the first three lactations of dairy cattle.(AU)