Genetic modelling of daily milk yield using orthogonal polynomials and parametric curves

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Genetic evaluation of dairy bulls for energy balance traits using random regression (2001, methodology): “The error variance for milk yield in the first three classes is substantially higher than in the later part of early lactation and does not approach values reported from other studies until day 10 (Olori et al., 1999; Brotherstone et al., 2000).”
The mathematical description of lactation curves in dairy cattle (2011, background): “Moreover, it can be easy linearized by setting the k parameter to a suitable fixed value (Brotherstone et al., 2000) and its parameters still maintain a relationship with lactation curve shape.”
Random regressions to model phenotypic variation in monthly weights of Australian beef cows (2000, background): “While we son (1999) and Brotherstone et al. (2000). are ultimately interested in a genetic analysis, as a Other traits of prime interest in livestock pro- first step, only phenotypic animal effects and growth duction which are measured over time and for which curves are considered. a simple…”