A management model that helps increase profit on Western Australian Dairy Farms

Olney, G R; Kirk, G. J.

doi:10.1016/0308-521x(89)90035-8

Cited by 10 publications

(4 citation statements)

References 5 publications

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“…Linear programming has previously been used in grazing-based dairy models, although they have tended to focus on issues other than forage choice, with simpler approaches to animal nutrition. For example, Olney and Kirk (1989) examined strategic issues important to Western Australian dairy farms such as stocking rate, beef activities, hay production, and grain usage. Batterham et al (1993) examined the strategic issues facing New South Wales (NSW) dairy farmers, including milk quota choice, pasture combinations, and fodder conservation.…”

Section: Modeling Approachmentioning

confidence: 99%

Optimal Choice of Dairy Forages in Eastern Australia

Neal

Fulkerson

2007

Journal of Dairy Science

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Although several forage species such as perennial ryegrass are predominant, there is a wide range of forage species that could be grown in subtropical and temperate regions in Australia as dairy pastures. These species have differing seasonal patterns of growth, nutrient quality, and water-use efficiency, as demonstrated in a large experiment evaluating over 30 species at the University of Sydney (Camden, New South Wales, Australia). Some species can be grazed, whereas others require mechanical harvesting, which incurs a further cost. Previous comparisons of species that relied on yield of dry matter per unit of some input (typically land or water) did not simultaneously take into account the season in which forage is produced, or other factors related to the costs of production and delivery to the cows. To effectively compare the profitability of individual species, or combinations of species, requires the use of a whole-farm, multiperiod model. Linear programming was used to find the most profitable mix of forage species for an irrigated dairy farm in a warm temperate irrigation region of New South Wales, Australia. It was concluded that for a typical farmer facing the prevailing milk and purchased feed prices with average milk production per cow, the most profitable mix of species would include a large proportion of perennial ryegrass (Lolium perenne) and prairie grass (Bromus willdenowii). The result was robust to changes in seasonal milk pricing and a move from year-round to a more seasonal calving pattern.

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Section: Modeling Approachmentioning

confidence: 99%

Optimal Choice of Dairy Forages in Eastern Australia

Neal

Fulkerson

2007

Journal of Dairy Science

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“…Dynamic programming has been used to successfully determine the optimal scheduling of irrigation applications to homogeneous cropping areas [4]. Optimal mixtures of ration formulations for dairy cattle have been determined for a number of situations via linear programming [23], with this approach being extended to a whole-farm dairying system by also incorporating pasture and fodder conservation feeds [46]. The optimal harvesting schedules (both spatial and temporal) of forestry systems is also a much-reported discipline, and includes solution by linear and mixed-integer programming approaches [34,51].…”

Section: Agricultural Systems Models -Proceduresmentioning

confidence: 99%

“…Linear programming has been successfully used to optimize the formulation of feed rations in Australia [23], but this only considers one dimension of the overall problem. This approach was also used to evaluate the effects of herd size, calving pattern, the area of pasture and fodder crops, and fodder conservation strategy in Western Australia [46]. A general simulation model of a dairy farm, incorporating most of the critical management options, was developed for Victoria [31].…”

Section: Comparative Studies Using Dairy Farm Modelsmentioning

confidence: 99%

Untitled

Mayer¹,

Belward²,

Burrage³

1998

Annals of Operations Research

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Agricultural systems vary widely in terms of scale, scope and purpose. Managers of these real-world systems are typically faced with a multitude of alternative management options and strategies, and are turning more towards simulation models in an attempt to evaluate these and identify the optimal combination. From a modelling perspective, agricultural systems present a range of problems which need to be addressed, and these are outlined with examples. General conclusions are drawn on which of the available methodologies are most likely to be successful for users.

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“…Most research of grazing systems undertaken with MP models has involved the application of linear programming (LP) models in which pasture growth and digestibility are constant in each feed period (Olney and Kirk, 1989;Berentsen and Giesen, 1994;Stott et al, 2005;Anderson and Ridler, 2010). Nevertheless, the implications of seasonal pasture growth and spatial diversity in management have been considered (Berentsen et al, 2000).…”

Section: Introductionmentioning

confidence: 99%