Evaluation of a Whole-Farm Model for Pasture-Based Dairy Systems

Abstract

In the temperate climate of New Zealand, animals can be grazed outdoors all year round. The pasture is supplemented with conserved feed, with the amount being determined by seasonal pasture growth, genetics of the herd, and stocking rate. The large number of factors that affect production makes it impractical and expensive to use field trials to explore all the farm system options. A model of an in situ-grazed pasture system has been developed to provide a tool for developing and testing novel farm systems; for example, different levels of bought-in supplements and different levels of nitrogen fertilizer application, to maintain sustainability or environmental integrity and profitability. It consists of a software framework that links climate information, on a daily basis, with dynamic, mechanistic component-models for pasture growth and animal metabolism, as well as management policies. A unique feature is that the component models were developed and published by other groups, and are retained in their original software language. The aim of this study was to compare the model, called the whole-farm model (WFM) with a farm trial that was conducted over 3 yr and in which data were collected specifically for evaluating the WFM. Data were used from the first year to develop the WFM and data from the second and third year to evaluate the model. The model predicted annual pasture production, end-of-season cow liveweight, cow body condition score, and pasture cover across season with relative prediction error <20%. Milk yield and milksolids (fat + protein) were overpredicted by approximately 30% even though both annual and monthly pasture and supplement intake were predicted with acceptable accuracy, suggesting that the metabolic conversion of feed to fat, protein, and lactose in the mammary gland needs to be refined. Because feed growth and intake predictions were acceptable, economic predictions can be made using the WFM, with an adjustment for milk yield, to test different management policies, alterations in climate, or the use of genetically improved animals, pastures, or crops.

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

“…The accuracy of prediction was moderate for LW and BCS, when considering the CCC (Table 1). These levels of accuracy of prediction for DM intake and milk yield are similar or higher than those reported for other models for grazing dairy systems, such as Farmax Dairy Pro (Bryant et al, 2010), GrazeIn (Delagarde et al, 2011) and the WFM (Beukes et al, 2008). However, it is important to notice that the validation of the model was conducted for annual outputs, and the accuracy of the model for short-term predictions (weekly or monthly basis) remains to be tested.…”

“…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.…”

Description and evaluation of the Farmax Dairy Pro decision support model

“…Nevertheless, for milksolids production per cow per day, Beukes et al (2008) reported MPEs ranging from 0.23 to 0.52 using the Whole Farm Model, compared with 0.14 to 0.21 in the present evaluation. The Whole Farm Model was more accurate at predicting cow condition score, with an MPE of 0.01 to 0.06 compared with 0.05 to 0.11 in the present evaluation.…”

Simulating forage crop production in a northern climate with the Integrated Farm System Model

“…Such an approach can be achieved using models that simulate the economic and environmental implications of practices at the farm scale. Recent years have seen the development of several farm-scale models, such as DairyWise in the Netherlands (Schils et al 2007), WFM (Whole-Farm Model) in New Zealand (Wastney et al 2002;Beukes et al 2008), GAMEDE (Global Activity Model for Evaluating the sustainability of Dairy Enterprises) in France (Vayssie`res et al 2009a, b), and the Integrated Farm System Model (IFSM) in the United States (Rotz et al 2014). However, the ability of these models to simulate crop production in northern regions with boreal and hemiboreal climates (Ko¨ppen climate classification; Peel et al 2007), such as eastern Canada, which are characterized by short growing seasons (mid-April to mid-September on average) and long periods of soil freezing and snow cover, needs to be verified.…”