Description and Validation of the Moorepark Dairy System Model

Abstract

A stochastic budgetary simulation model of a dairy farm was developed to allow investigation of the effects of varying biological, technical, and physical processes on farm profitability. The model integrates animal inventory and valuation, milk supply, feed requirement, land and labor utilization, and economic analysis. A key model output is the estimated distribution of farm profitability, which is a function of total receipts from milk, calves, and cull cows less all variable and fixed costs (including an imputed cost for labor). An application of the model was demonstrated by modeling 2 calving patterns: a mean calving date of February 24 (S1) and a mean calving date of January 27 (S2). Monte Carlo simulation was used to determine the influence of variation in milk price, concentrate cost, and silage quality on farm profitability under each scenario. Model validation was conducted by comparing the results from the model against data collected from 21 commercial dairy farms. The net farm profit with S1 was 53,547 euros, and that with S2 was 51,687 euros; the annual EU milk quota was 468,000 kg, and farm size was 40 ha. Monte Carlo simulation showed that the S1 scenario was stochastically dominant over the S2 scenario. Sensitivity analyses showed that farm profit was most sensitive to changes in milk price. The partial coefficients of determination were 99.2, 0.7, and 0.1% for milk price, concentrate cost, and silage quality, respectively, in S1; the corresponding values in S2 were 97.6, 2.3, and 0.1%. Validations of the model showed that it could be used with confidence to study systems of milk production under Irish conditions.

Influence of age, body weight and body condition score before mating start date on the pubertal rate of maiden Holstein–Friesian heifers and implications for subsequent cow performance and profitability

“…The Moorepark dairy systems model (Shalloo et al, 2004), a stochastic budgetary simulation model, was used to simulate a representative farm integrating biological data from the current study with respect to each of the MSD BW categories. The model integrates animal inventory and valuation, milk production, feed requirements, land labour utilisation and an economic analysis.…”

e-Dairy: a dynamic and stochastic whole-farm model that predicts biophysical and economic performance of grazing dairy systems

“…Some of these models work at a herd level (Larcombe, 1990;Freer et al, 1997;Shalloo et al, 2004;Schils et al, 2007;Vayssiè res et al, 2009), whereas other models work at an individual animal level (Beukes et al, 2008;Bryant et al, 2010). These latter models account for genetic differences between cows, but they were designed to be used under specific conditions, that is, grass-based dairy systems and their environmental conditions under which the breeding values were estimated.…”

Modelling pastoral farm agro‐ecosystems: A review

“…LINCFaRM includes genetic variation in protein deposition, interplay between liveweight change and reproduction and specification of management events. Other models such as StockPol (Marshall et al 1991) (now known as FaRMaX), UDDER (Larcombe 1999) and Moorepark Dairy System Model (MDSM) (Shalloo et al 2004) were not reviewed as they do not model soil processes, predict pasture growth, and for the two former models, are largely used for decision support. However, these three models have detailed representation of farm economics, and in the case of FaRMaX and UDDER, optimisation capabilities, which can be used explore the effect on whole farm profit of system changes.…”