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Heterosis in the components of lactation curves of Girolando cows

Darlene dos Santos DaltroAnimal Science Department, Federal University of Rio Grande do Sul, Porto Alegre, Brazil; Correspondence[email protected]

http://orcid.org/0000-0003-2278-8129

Alessandro Haiduck PadilhaAnimal Science Department, Federal University of Rio Grande do Sul, Porto Alegre, Brazil;

Luís Telo da GamaFaculdade de Medicina Veterinária, Faculty of Veterinary Medicine, Technical University of Lisbon, Lisboa, Portugal;

http://orcid.org/0000-0003-3894-3488

Marcos Vinícius Gualberto Barbosa da SilvaEmbrapa Gado de Leite, Juiz de Fora, Brazil

http://orcid.org/0000-0001-5449-1413

João Claudio do Carmo PanettoEmbrapa Gado de Leite, Juiz de Fora, Brazil

Juliana Dementshuk MachadoAnimal Science Department, Federal University of Rio Grande do Sul, Porto Alegre, Brazil;

José Braccini NetoAnimal Science Department, Federal University of Rio Grande do Sul, Porto Alegre, Brazil;

http://orcid.org/0000-0003-2881-0235

Jaime Araujo CobuciAnimal Science Department, Federal University of Rio Grande do Sul, Porto Alegre, Brazil;

http://orcid.org/0000-0002-1414-4967

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Figures & data

Table 1. Description of the database.

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Table 2. Estimated parameters (mean ± SE) from different non-linear models, root mean square error (RMSE), Bayesian information criterion (BIC) and Akaike information criterion (AIC).

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Table 3. Estimated parameters (mean ± SE) from different linear models, root mean square error (RMSE), Bayesian information criterion (BIC) and Akaike information criterion (AIC).

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Figure 1. Trajectory of lactation curves estimated by 305-day milk yield from database (TMY), Wood’s linear model (WDlin), Ali and Schaeffer’s model (ASH), Wood’s non-linear model (WDnlin) and Wilmink’s (WL) model for 1/2H (A), 1/4H (B), 3/4H (C), 3/8H (D), 5/8H (E), 7/8 (F), G (G) and H (H) genetic groups.

Table 4. Average estimates of peak yield (PY), peak time (PT), persistency (P, P_2:1; P_3:1, and P_3:2) and 305-day milk yield (TMY) for different genetic groups estimated by linear and non-linear models.

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Table 5. Heterosis effect (mean ± SE) for Wood parameters (a, b and c), peak yield (PY), peak time (PT), persistency measures (P, P_2:1, P_3:1, and P_3:2) and 305-day milk yield (TMY) estimated by Wood’s non-linear model.

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Heterosis in the components of lactation curves of Girolando cows

Table 1. Description of the database.

Table 2. Estimated parameters (mean ± SE) from different non-linear models, root mean square error (RMSE), Bayesian information criterion (BIC) and Akaike information criterion (AIC).

Table 3. Estimated parameters (mean ± SE) from different linear models, root mean square error (RMSE), Bayesian information criterion (BIC) and Akaike information criterion (AIC).

Table 4. Average estimates of peak yield (PY), peak time (PT), persistency (P, P_2:1; P_3:1, and P_3:2) and 305-day milk yield (TMY) for different genetic groups estimated by linear and non-linear models.

Table 5. Heterosis effect (mean ± SE) for Wood parameters (a, b and c), peak yield (PY), peak time (PT), persistency measures (P, P_2:1, P_3:1, and P_3:2) and 305-day milk yield (TMY) estimated by Wood’s non-linear model.

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Heterosis in the components of lactation curves of Girolando cows

Figures & data

Table 1. Description of the database.

Table 2. Estimated parameters (mean ± SE) from different non-linear models, root mean square error (RMSE), Bayesian information criterion (BIC) and Akaike information criterion (AIC).

Table 3. Estimated parameters (mean ± SE) from different linear models, root mean square error (RMSE), Bayesian information criterion (BIC) and Akaike information criterion (AIC).

Table 4. Average estimates of peak yield (PY), peak time (PT), persistency (P, P2:1; P3:1, and P3:2) and 305-day milk yield (TMY) for different genetic groups estimated by linear and non-linear models.

Table 5. Heterosis effect (mean ± SE) for Wood parameters (a, b and c), peak yield (PY), peak time (PT), persistency measures (P, P2:1, P3:1, and P3:2) and 305-day milk yield (TMY) estimated by Wood’s non-linear model.

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Table 4. Average estimates of peak yield (PY), peak time (PT), persistency (P, P_2:1; P_3:1, and P_3:2) and 305-day milk yield (TMY) for different genetic groups estimated by linear and non-linear models.

Table 5. Heterosis effect (mean ± SE) for Wood parameters (a, b and c), peak yield (PY), peak time (PT), persistency measures (P, P_2:1, P_3:1, and P_3:2) and 305-day milk yield (TMY) estimated by Wood’s non-linear model.