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| Henao-Velásquez,Andrés F.; Múnera-Bedoya,Oscar David; Herrera,Ana Cristina; Agudelo-Trujillo,Jorge H.; Cerón-Muñoz,Mario Fernando. |
| The objective of this study was to evaluate lactose and milk urea nitrogen (MUN) in milk from Holstein cows and their relationship with days in milk (DIM), milk yield, milk fat, milk protein, and somatic cell count (SCC). A total of 1,034 records corresponding to morning and afternoon milkings of 148 Holstein cows were used. Records were taken from 16 herds located in the Northern and Eastern dairy regions of Antioquia (Colombia). The curves were fitted using a generalized additive mixed model with smoothed estimates to find the best smoothing intensity factors involved in MUN and lactose concentration. Regarding MUN, the contemporary group effect was highly significant, but the parity effect was not significant. The DIM, lactose and milk fat smoothed... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Dairy cattle; Generalized additive model; Milk metabolites; Milk yield. |
| Ano: 2014 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982014000900479 |
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| Galeano-Vasco,Luis Fernando; Cerón-Muñoz,Mario Fernando; Narváez-Solarte,William. |
| In this study, the Von Bertalanffy, Richards, Gompertz, Brody, and Logistics non-linear mixed regression models were compared for their ability to estimate the growth curve in commercial laying hens. Data were obtained from 100 Lohmann LSL layers. The animals were identified and then weighed weekly from day 20 after hatch until they were 553 days of age. All the nonlinear models used were transformed into mixed models by the inclusion of random parameters. Accuracy of the models was determined by the Akaike and Bayesian information criteria (AIC and BIC, respectively), and the correlation values. According to AIC, BIC, and correlation values, the best fit for modeling the growth curve of the birds was obtained with Gompertz, followed by Richards, and then... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Chickens; Mathematical models; Poultry; Regression analysis; Weight gain. |
| Ano: 2014 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982014001100573 |
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