Study of the Lactation Curve in Dairy Cattle on Farms in Central Mexico

Abstract

Accurate knowledge of lactation curves has an important relevance to management and research of dairy production systems. A number of equations have been proposed to describe the lactation curve, the most widely applied being the gamma equation. The objective of this work was to compare and evaluate candidate functions for their predictive ability in describing lactation curves from central Mexican dairy cows reared under 2 contrasting management systems. Five equations were considered: Gaines (exponential decay), Wood (gamma equation), Rook (Michaelis-Menten xexponential), and 2 more mechanistic ones (Dijkstra and Pollott). A database consisting of 701 and 1283 records of cows in small-scale and intensive systems, respectively, was used in the analysis. Before analysis, the database was divided into 6 groups representing first, second, and third and higher parity cows in both systems. In all cases except second and above parity cows in small-scale systems, all models improved on the Gaines equation. The Wood equation explained much of the variation, but its parameters do not have direct biological interpretation. Although the Rook equation fitted the data well, some of the parameter estimates were not significant. The Dijkstra equation consistently gave better predictions, and its parameters were usually statistically significant and lend themselves to physiological interpretation. As such, the differences between systems and parity could be explained due to variations in theoretical initial milk production at parturition, specific rates of secretory cell proliferation and death, and rate of decay, all of which are parameters in the model. The Pollott equation, although containing the most biology, was found to be over-parameterized and resulted in nonsignificant parameter estimates. For central Mexican dairy cows, the Dijkstra equation was the best option to use in describing the lactation curve.

Selection of models of lactation curves to use in milk production simulation systems

“…The model by Dijkstra et al (1993) showed higher estimates of the peak day than those of the other models, in all the subgroups. A similar result was reported by Val-Arreola et al (2004). Therefore, it is possible that the model by Dijkstra et al (1993) is more suitable to represent lactations whose peak day occurs on a day farther from the beginning of lactation (Figure 3).…”

“…In absolute values the model by Dijkstra et al (1993) showed a better adjustment than the others in all the goodness of fit measurements. Val-Arreola et al (2004) also observed the better adjustment of the model by Dijkstra et al (1993) over the models by Brody et al (1923), Wood (1967), Rook et al (1993) and by Pollott (2000) for lactations of animals on more technological farms. The model by Dijkstra et al (1993) showed a higher percentage of convergence in the high production subgroups than the low and medium production subgroups.…”

“…After classification, the data were ranked according to the lactation number, into first, second, third or greater, as reported by Val-Arreola et al (2004) and Dematawewa et al (2007). This procedure resulted in the formation of nine subgroups: L1 = low production and 1st lactation number; L2 = low production and 2nd lactation number; L3 = low production and 3rd or greater lactation number; M1 = medium production and 1st lactation number; M2 = medium production and 2nd lactation number; M3 = medium production and 3rd or greater lactation number; H1 = high production and 1st lactation number; H2 = high production and 2nd lactation number; and H3 = medium production and 3rd or greater lactation number.…”

Analysis of feeding strategies for small-scale dairy systems in central Mexico using linear programming

“…Similarly, the energy requirements for milk production reflect the shape of the lactation curve. The lactation curve of the dairy cow was represented using the equation of Dijkstra et al (1997) which was found to be the most appropriate equation for cows reared under small-scale systems in central Mexico (Val-Arreola et al, 2004a).…”

The utility of sensor technology to support reproductive management on dairy farms

“…Previous comparisons of production curves indicated that the Dijkstra curve provided the most accurate estimates of peak milk yield and time of peak milk yield and that smaller models are preferable (Dematawewa, et al, 2007, Val-Arreola, et al, 2004. The Dijkstra curve was chosen as the production curve to model milk yield, based on the BIC in the current study and previous findings.…”