Use of Danish National Somatic Cell Count Data to Assess the Need for Dry-Off Treatment in Holstein Dairy Cattle.

In Denmark, PCR testing of dairy cattle is commonly used to select animals for the antibacterial treatment of intramammary infection (IMI) during the dry-off period. IMI is associated with a high somatic cell count (SCC), routinely recorded for milk quality control for most commercial dairy herds. This study aimed to compare SCC curves over the lactation among dairy cows with positive vs. negative PCR test results for four major IMI pathogens. Data from 133,877 PCR-tested Holstein cows from 1364 Danish conventional dairy herds were used to fit a nonlinear mixed-effects model using a modified four-parameter Wilmink function. We stratified the data into first, second, third or fourth and later parity and fitted Wilmink curves to all SCC observations between 6 and 305 days in milk. The PCR tests were taken before dry-off at the end of the lactation to investigate which animals qualified for selective dry cow therapy. A PCR Ct-value of 37 and below was used to determine if an animal was PCR positive for any of the following IMI pathogens: Staphylococcus aureus, Streptococcus agalactiae, Str. dysgalactiae and Str. uberis. Our findings showed that mean SCC curve fits were higher for PCR-positive animals in all four parity groups and across lactations. The use of SCC data fitted to the entire lactation for multiple lactations enabled quantification of overall differences in SCC curves between cattle with and without detected IMI, adjusted for parity group and stage of lactation. These findings are relevant to the use of SCC to support treatment decisions.

Optimal value for the exponential term of Wilmink's function according to current Holstein lactation curves in Japan.

We compared values of Wilmink's exponential term to describe the lactation curves of Holstein cows in Japan. Data were a total of 100,971,798 test-day records from the first through fifth parities during 1991 through 2018. The lactation curve model used fourth-order Legendre polynomials and Wilmink's exponential term. In total, 810 analyses were executed to compare six values (-0.02, -0.03, …, -0.07) for the exponential term to select the one that yielded the smallest root mean square error. For all parities, daily milk yield and lactation persistency increased consistently and peak lactation days occurred later from year to year. For the years evaluated, the optimal exponential term was -0.05 for first and second parities, -0.04 for third parity, and -0.03 for fourth and fifth parities. The change in the exponential parameter with increasing year was related to delays in peak lactation.

Modelling Extended Lactations in Polish Holstein-Friesian Cows.

The objectives of this study were (1) to examine different shapes of lactation curves for milk, fat, protein and lactose yields and urea content in milk fitted by the Wilmink function using the test-day (TD) records and (2) to find the function that best describes test-day records beyond 305 days in milk (DIM) for Polish Holstein-Friesian cows. The data were 6,955,768 TD records from the 702,830 first six lactations of 284,193 Polish Holstein-Friesian cows. Cows calved in 19,102 herds between 2001 and 2018. The following functions were fitted to TD data from each lactation: (1) Wilmink model fitted to the whole lactation, (2) Wilmink model fitted to TD records from 5 to 305 DIM and linear function fitted to TD records from 306 to 400 DIM, (3) Wilmink model fitted to TD records from 5 to 305 DIM and squared function fitted to TD records from 306 to 400 DIM. The present study showed that urea content in milk was modelled slightly worse than other milk traits. The results suggested that the course of lactation could be successfully modelled by a nonlinear model, for example, the Wilmink function, for up to 305 DIM, and by the linear or squared function afterwards.

Estimation of genetic parameters for test-day milk yield in Girolando cows using a random regression model / [Estimação de parâmetros genéticos para produção de leite no dia do teste em vacas da raça Girolando utilizando modelo de regressão aleatória]

The objective of this study was to estimate the components of variance and genetic parameters of test-day milk yield in first lactation Girolando cows, using a random regression model. A total of 126,892 test-day milk yield (TDMY) records of 15,351 first-parity Holstein, Gyr, and Girolando breed cows were used, obtained from the Associação Brasileira dos Criadores de Girolando. To estimate the components of (co) variance, the additive genetic functions and permanent environmental covariance were estimated by random regression in three functions: Wilmink, Legendre Polynomials (third order) and Linear spline Polynomials (three knots). The Legendre polynomial function showed better fit quality. The genetic and permanent environment variances for TDMY ranged from 2.67 to 5.14 and from 9.31 to 12.04, respectively. Heritability estimates gradually increased from the beginning (0.13) to mid-lactation (0.19). The genetic correlations between the days of the control ranged from 0.37 to 1.00. The correlations of permanent environment followed the same trend as genetic correlations. The use of Legendre polynomials via random regression model can be considered as a good tool for estimating genetic parameters for test-day milk yield records.(AU)

O objetivo deste estudo foi estimar os componentes de variância e os parâmetros genéticos da produção de leite no dia do teste (TDMY) em vacas Girolando de primeira lactação, usando modelo de regressão aleatória. Foram utilizados 126.892 registros de produção de leite no dia controle de 15.351 vacas primíparas das raças Holandesa, Gir e Girolando, obtidas na Associação Brasileira dos Criadores de Girolando. Para estimar os componentes de (co) variância, as funções genéticas aditivas e de covariância ambiental permanente foram estimadas por regressão aleatória em três funções: Wilmink, polinômios de Legendre (terceira ordem) e polinômios splines lineares (três nós). A função polinomial de Legendre apresentou melhor qualidade de ajuste. As variâncias genéticas e de ambiente permanente para produção de leite no dia do controle variaram de 2,67 a 5,14 e de 9,31 a 12,04, respectivamente. As estimativas de herdabilidade aumentaram gradativamente do início (0,13) para o meio da lactação (0,19). As correlações genéticas entre os dias do controle variaram de 0,37 a 1,00. As correlações de ambiente permanente seguiram a mesma tendência das correlações genéticas. A utilização dos polinômios de Legendre via modelos de regressão aleatória pode ser considerada como uma boa ferramenta para estimação de parâmetros genéticos da produção de leite no dia do teste.(AU)

Random regression models using different functions to estimate genetic parameters for milk production in Holstein Friesians / Modelos de regressão aleatória usando diferentes funções para estimar parâmetros genéticos para produção de leite na raça Holandesa

ABSTRACT: The objective of this study was to compare the functions of Wilmink and Ali and Schaeffer with Legendre polynomials in random regression models using heterogeneous residual variances for modeling genetic parameters during the first lactation in the Holstein Friesian breed. Five thousand eight hundred and eighty biweekly records of test-day milk production were used. The models included the fixed effects of group of contemporaries and cow age at calving as covariable. Statistical criteria indicated that the WF.33_HE2, LEG.33_HE2, and LEG.55_HE4 functions best described the changes in the variances that occur throughout lactation. Heritability estimates using WF.33_HE2 and LEG.33_HE2 models were similar, ranging from 0.31 to 0.50. The LEG.55_HE4 model diverged from these models, with higher estimates at the beginning of lactation and lower estimates after the 16th fortnight. The LEG55_HE4, among the three better models indicated by the index, is the one with highest number of parameters (14 vs 34) and resulted in lower estimation of residual variance at the beginning and at the end of lactation, but overestimated heritability in the first fortnight and presented a greater difficulty to model genetic and permanent environment correlations among controls. Random regression models that used the Wilmink and Legendre polynomials functions with two residual variance classes appropriately described the genetic variation during lactation of Holstein Friesians reared in Rio Grande do Sul.

RESUMO: Objetivou-se comparar as funções de Wilmink e Ali e Schaeffer com polinômios de Legendre em modelos de regressão aleatória, utilizando variâncias residuais heterogêneas, para modelar parâmetros genéticos ao longo da primeira lactação na raça Holandesa. Foram utilizados cinco mil oitocentos e oitenta registros quinzenais de produção de leite no dia do controle. Os modelos incluíram os efeitos fixos de grupo de contemporâneos e a idade da vaca ao parto como covariável. Os critérios estatísticos apontaram as funções WF.33_HE2, LEG.33_HE2 e a LEG.55_HE4 como as melhores em descrever as mudanças nas variâncias que ocorrem ao longo da lactação. As herdabilidades estimadas pelos modelos WF.33_HE2 e LEG.33_HE2 foram semelhantes, variando de 0,31 a 0,50. O LEG.55_HE4 divergiu destes, no início da lactação, com estimativas superiores e, a partir da 16ª quinzena, com estimativas inferiores. O LEG55_HE4, entre os três melhores modelos indicados pelo índice, é o mais parametrizado (14 vs 34) e resultou em menores estimativas de variância residual no início e no final da lactação, mas superestimou a herdabilidade na primeira quinzena e apresentou maior dificuldade em modelar as correlações genéticas e de ambiente permanente entre os controles. Os modelos de regressão aleatória que usaram a função de Wilmink e Polinômios de Legendre com duas classes de variâncias residuais descreveram adequadamente a variação genética ao longo da lactação de vacas da raça Holandesa, criadas no Rio Grande do Sul.