Using models to establish the financially optimum strategy for Irish dairy farms

Abstract

Determining the effect of a change in management on farm with differing characteristics is a significant challenge in the evaluation of dairy systems due to the interacting components of complex biological systems. In Ireland, milk production is increasing substantially following the abolition of the European Union milk quota regime in 2015. There are 2 main ways to increase the milk production on farm (within a fixed land base): either increase the number of animals (thus increasing the stocking rate) or increase the milk production per animal through increased feeding or increased lactation length. In this study, the effect of increased concentrate feeding or an increase in grazing intensity was simulated to determine the effect on the farm system and its economic performance. Four stocking rates (2.3, 2.6, 2.9, and 3.2 cow/ha) and 5 different concentrate supplementation strategies (0, 180, 360, 600, and 900 kg of dry matter/lactation) resulting in 20 different scenarios were evaluated across different milk, concentrate, and silage purchase prices. Each simulation was run across 10 yr of meteorological data, which had been recorded over the period 2004 to 2013. Three models-the Moorepark and St Gilles grass growth model, the pasture-based herd dynamic milk model, and the Moorepark dairy systems modelwere integrated and applied to simulate the different scenarios. Overall, this study has demonstrated that the most profitable scenario was a stocking rate of 2.6 cow/ha with a concentrate supplementation of 600 kg of dry matter/cow. The factor that had the greatest influence on profitability was variability of milk price.

Factors associated with profitability in pasture-based systems of milk production

“…During the period of milk quota restrictions, in order for farmers to maximize farm profit, they had to maximize profit per unit of product, typically achieved by producing milk in a least cost per unit of product format, generally from a predominantly pasture-based diet. In terms of individual farm management, the response rates of milk production to increased concentrate feeding and other purchased feeds are greatly influenced by several variables including pasture quality, pasture allowance, stocking rate, and dairy cow genetics (Roche et al, 2006;Ruelle et al, 2018). When pasture quality is poor or limiting DMI of the cow (or both), the response to concentrate will be increased in comparison to a cow being fed greater quality or quantity (or both) of pasture, thus affecting the levels of substitution (reduction in pasture intake when supplementary feeds are consumed by the cow; Bargo et al, 2003), combined with a maintenance requirement on a proportion of the consumed energy (Roche et al, 2009).…”

“…Although in a high milk price year it could be assumed increased supplementary feed usage would increase farm profitability, it has been reported that the key determinant here is the difference between milk price and feed costs, and not the price of milk or feed costs in a given year (Hansen et al, 2005). In reality it can be more difficult to manage higher input systems as there is a greater complexity of the overall system through more decision rules required on an ongoing basis, which requires higher levels of skill to manage (Ruelle et al, 2018).…”

Review: New considerations to refine breeding objectives of dairy cows for increasing robustness and sustainability of grass-based milk production systems

“…In support, Ramsbottom et al (2015) reported that the cost of the marginal milk produced from imported feeds was greater than the milk price received in systems utilising >500 kg DM/cow purchased feeds. Recent results from farm systems experiments in Ireland (Ruelle et al, 2018) and New Zealand Roche J. R., unpublished data) concur; the cost of marginal milk produced from inexpensive purchased feeds was greater than a moderate to good milk price, despite very good marginal milk production responses to the purchased feed.…”

Association between technical and economic performance indexes and dairy farm profitability

“…The herd profile and technological differences among the systems are possible explanations for this discrepancy. Furthermore, it has also been previously reported that variability of milk price has greatest influence on profitability (Ruelle et al, 2018). Hence, in an era of increased levels of milk price volatility (Hemme et al, 2014), producers require to maximize production efficiencies and, in particular, business resilience (Shadbolt, 2012).…”