» Articles » PMID: 22916941

Comparative Evaluation of a New Lactation Curve Model for Pasture-based Holstein-Friesian Dairy Cows

Overview
Journal J Dairy Sci
Date 2012 Aug 25
PMID 22916941
Citations 5
Authors
Affiliations
Soon will be listed here.
Abstract

Fourteen lactation models were fitted to average and individual cow lactation data from pasture-based dairy systems in the Australian states of Victoria and Tasmania. The models included a new "log-quadratic" model, and a major objective was to evaluate and compare the performance of this model with the other models. Nine empirical and 5 mechanistic models were first fitted to average test-day milk yield of Holstein-Friesian dairy cows using the nonlinear procedure in SAS. Two additional semiparametric models were fitted using a linear model in ASReml. To investigate the influence of days to first test-day and the number of test-days, 5 of the best-fitting models were then fitted to individual cow lactation data. Model goodness of fit was evaluated using criteria such as the residual mean square, the distribution of residuals, the correlation between actual and predicted values, and the Wald-Wolfowitz runs test. Goodness of fit was similar in all but one of the models in terms of fitting average lactation but they differed in their ability to predict individual lactations. In particular, the widely used incomplete gamma model most displayed this failing. The new log-quadratic model was robust in fitting average and individual lactations, and was less affected by sampled data and more parsimonious in having only 3 parameters, each of which lends itself to biological interpretation.

Citing Articles

Managerial factors affecting milking-abilities of Holstein cattle under intensive production system in Egypt.

Faid-Allah E, Mourad R, Saddick E, Eldahshan E Trop Anim Health Prod. 2025; 57(1):23.

PMID: 39797939 PMC: 11724796. DOI: 10.1007/s11250-024-04271-w.


A Machine Learning Framework Based on Extreme Gradient Boosting to Predict the Occurrence and Development of Infectious Diseases in Laying Hen Farms, Taking H9N2 as an Example.

Liu Y, Zhuang Y, Yu L, Li Q, Zhao C, Meng R Animals (Basel). 2023; 13(9).

PMID: 37174531 PMC: 10177545. DOI: 10.3390/ani13091494.


The Potentialities of Machine Learning for Cow-Specific Milking: Automatically Setting Variables in Milking Machines.

Wang J, Lovarelli D, Rota N, Shen M, Lu M, Guarino M Animals (Basel). 2022; 12(13).

PMID: 35804513 PMC: 9265131. DOI: 10.3390/ani12131614.


A new standard model for milk yield in dairy cows based on udder physiology at the milking-session level.

Gasqui P, Trommenschlager J Sci Rep. 2017; 7(1):8897.

PMID: 28827751 PMC: 5567198. DOI: 10.1038/s41598-017-09322-x.


Models to Estimate Lactation Curves of Milk Yield and Somatic Cell Count in Dairy Cows at the Herd Level for the Use in Simulations and Predictive Models.

Graesboll K, Kirkeby C, Nielsen S, Halasa T, Toft N, Christiansen L Front Vet Sci. 2017; 3:115.

PMID: 28066776 PMC: 5165235. DOI: 10.3389/fvets.2016.00115.