Modelling lactation curves of dairy cows is important for improved feed management and breeding decisions. The objectives of this study were to compare measures of lactation persistency obtained from the modelling of lactation curves for daily yields of milk, fat and protein using a nonlinear random regression model in dairy cows milked once a day under grazing conditions. A total of 1,955 monthly herd-test records of milk, fat and protein from 55 Holstein-Friesian (F), 64 Jersey (J), and 123 F×J crossbreds of different lactations were used to obtain lactation curves for each cow using a random regression model with the Wood function. Three measures of persistency were calculated based on ratios of yields and compared with persistency calculated based on parameters of the Wood function. Jersey cows in lactation 3 had the greatest persistency for all persistency measures. In first-lactation cows, there were no significant breed differences in persistency. Persistency measures were strongly correlated with each other (r≥0.97; P<0.001). The conclusion from this study is that parameters of the lactation curve (peak yield, day of peak and persistency) can be precisely estimated using the random regression model with the Wood function. Keywords: modelling; lactation curve; persistency; once-a-day milking

H, Jiang, RE Hickson, OT Woods, M Morandeau, JL Burke, M Correa-Luna, DJ Donaghy, and N Lopez-villalobos

Proceedings of the New Zealand Society of Animal Production, Volume 80, Online, 131-136, 2020
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