Fit of standard models of the lactation curve to weekly records of milk production of cows in a single herd

Olori, V E; Brotherstone, S.; Hill, William G.; McGuirk, Brian

doi:10.1016/s0301-6226(98)00194-8

Cited by 133 publications

(149 citation statements)

References 14 publications

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“…Results obtained in this study for individual lactations of standard length agree with previous reports for dairy cattle (Olori et al, 1999;Macciotta et al, 2005;Silvestre et al, 2006), with a better fit for polynomials (AS, LEG and SPL) compared with models with three parameters. No studies are currently available in the literature on fitting individual extended lactation curves.…”

Section: Resultssupporting

confidence: 90%

Analysis of lactation shapes in extended lactations

Steri

Dimauro

Canavesi³

et al. 2012

animal

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In order to describe the temporal evolution of milk yield (MY) and composition in extended lactations, 21 658 lactations of Italian Holstein cows were analyzed. Six empirical mathematical models currently used to fit 305 standard lactations (Wood, Wilmink, Legendre, Ali and Schaeffer, quadratic and cubic splines) and one function developed specifically for extended lactations (a modification of the Dijkstra model) were tested to identify a suitable function for describing patterns until 1000 days in milk (DIM).Comparison was performed on individual patterns and on average curves grouped according to parity (primiparous and multiparous) and lactation length (standard <305 days, and extended from 600 to 1000 days). For average patterns, polynomial models showed better fitting performances when compared with the three or four parameters models. However, LEG and spline regression, showed poor prediction ability at the extremes of the lactation trajectory. The Ali and Schaeffer polynomial and Dijkstra function were effective in modelling average curves for MY and protein percentage, whereas a reduced fitting ability was observed for fat percentage and somatic cell score. When individual patterns were fitted, polynomial models outperformed nonlinear functions. No detectable differences were observed between standard and extended patterns in the initial phase of lactation, with similar values of peak production and time at peak. A considerable difference in persistency was observed between 200 and 305 DIM. Such a difference resulted in an estimated difference between standard and extended cycle of about 7 and 9 kg/day for daily yield at 305 DIM and of 463 and 677 kg of cumulated milk production at 305 DIM for the first-and second-parity groups, respectively. For first and later lactation animals, peak yield estimates were nearly 31 and 38 kg, respectively, and occurred at around 65 and 40 days. The asymptotic level of production was around 9 kg for multiparous cows, whereas the estimate was negative for first parity.

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Section: Resultssupporting

confidence: 90%

Analysis of lactation shapes in extended lactations

Steri

Dimauro

Canavesi³

et al. 2012

animal

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“…Similar results related to the quality of fit to the milk record data and to the simplicity to the computational adjustment of the Wilmink function were also reported by Olori et al (1999) The values of the estimates of the variance components for the additive genetic (VGA), animal permanent environmental (VEP) and phenotypic effects (VP) are similar between the fitted function and tended to increase during lactation (Table 6 and Figure 2). The highest estimates of VGA and VPE were observed in the final third of the lactation curve (Table 6 and Figure 2).…”

Section: Resultssupporting

confidence: 83%

Adjustment of Lactation Curves of Holstein Cows from Herds of Minas Gerais, Brazil

Azevedo¹,

Gonçalves²,

Souza³

et al. 2018

JAS

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Random regression models (RRM) differ in terms of the functions used to describe the shape of lactation curves. The aim was to compare random regression models under different functions to describe the lactation curves from Holstein cows in herds of the state of Minas Gerais. A database of 28,118 production records was analyzed using the test-day records of 4,230 first parity cows from five herds. The Wilmink, Ali & Schaeffer and Legendre polynomial (orders 4, 5 and 6) functions were adjusted in RRM to model the mean production trend (fixed) and genetic and permanent environmental (random) effects. The residual variances were assumed to be constant throughout lactation. Analyses were performed using the AIREMLF90 program. Except for the model with the polynomial function of order 5, all models converged. The Wilmink function showed lower values for criteria based on the -2log (L), AIC and BIC. The model with the Legendre polynomial of order 6 showed lower residual variance. Heritability estimates were similar between functions, ranging from 0.07 to 0.18 and were higher from 215 days of lactation. From 155 days of lactation, genetic and permanent environmental correlations between successive controls are of high magnitude. The Wilmink function is the most suitable for the study of milk yields from primiparous Holstein cows. The selection of animals is possible from 155 days of lactation on. Permanent environmental effects have greater influence on the milk production at the end of lactation of primiparous cows and should be considered since they are important and may be cumulative throughout lactation.

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“…Comparing five models of the lactation curve, Olori et al (1999) found the WIL model to be best in predicting both the time (week 7) and yield (32.0 kg) at peak. They also examined the effect of the week of peak production on the goodness of fit of the models, and came to the conclusion that lactations peaking between 6 and 9 weeks were predicted more accurately than those peaking earlier or later.…”

Section: Discussionmentioning

confidence: 99%

“…Quinn et al (2005) used several models for analysis, including ALI, GUO and WIL, and estimated the peak at about week eight. It should be added that Olori et al (1999) and Quinn et al (2005) considered weekly yields; what is more, Olori et al (1999) used only data on heifers from one herd, kept under uniform feeding and management conditions. Macciotta et al (2005) suggested that three-parameter models such as the WIL function ensured a superior fit to data with a single curvature.…”

Section: Discussionmentioning

confidence: 99%