Comparison Between Different Functions of the Lactation Curve | ||||
| The Egyptian Statistical Journal | ||||
| Article 7, Volume 40, Issue 1, June 1996, Page 93-104 PDF (1.28 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/esju.1996.314782 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Ahmed Kamal Ahmed Ali | ||||
| Department of Animal Production , College of Agriculture, King Saud University, Riyadh, Saudi Arabia | ||||
| Abstract | ||||
| Six mathematical functions; Wood, Mitscherlich* exponential, Michaelis-Menten* exponential, Logistic* exponential, Weibull* exponential and Multiphasic; were used to describe the lactation curve of the monthly test- day average of 12020 Holstein Fresian milk records in the Kingdom of Saudi Arabia. The fifteen monthly test- day averages were 10 fitted using nonlinear regression by the Gauss-Newton iterative method. Measures of Goodness of fit such as Autocorrelation, Durbin Watson statistic (DW), R2, and Mean square error were used to compare between different functions. Autocorrelation values ranged from .14 to .28 for all models. Durbin Watson statistic ranged from 1.062 to 2.785, R2 values being greater than .98. Mean square error was the lowest for triphasic function (MSE=.1) and the highest for Mitscherlich* exponential and Logistic* exponential (MSE = 7.792). The Triphasic function with nine parameters was the most accurate function for representing the lactation curve. However, Mitscherlich* Exponential, Logistic * Exponential and Monophasic functions displayed the poorest fit for the data. | ||||
| Keywords | ||||
| Gauss-Newton Iterative Method; Goodness of Fit; Lactation Curve; Mathematical Functions; Nonlinear Regression | ||||
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