'One size fits all'? Ð The relationship between the value of genetic traits and the farm system

The wide use of artificial insemination by dairy farmers has facilitated the development of a multi-billion dollar international market in animal genetics. In the major western dairy producing nations, each country has developed a single index to rank bulls, based on the value of traits they are expected to pass on to their offspring. One of the assumptions behind these indexes is that there is a positive linear relationship between profit (and welfare) with increases in a particular trait, regardless of the farm system. In this paper, it is shown, with examples, that the assumption of linearity is false. More importantly, it is shown that for a combination of reasons, including risk aversion, constraints and other issues, the optimal direction of genetic improvement for New Zealand dairy farmers on an individual and industry level could be quite different. Alternatives to the Òone size fits allÓ index are described.

Choosing the best forage species for a dairy farm: The Whole-farm approach

Although a handful of forage species such as perennial ryegrass are predominant, there are a wide range of forage species that can be grown in sub tropical and temperate regions in Australia as dairy pastures. These species have differing seasonal yields, nutrient quality and water use efficiency characteristics, as demonstrated in a large study evaluating 30 species University of Sydney in New South Wales, Australia. Some species can be grazed, while others require mechanical harvesting that incurs a further cost. Previous comparisons of species that relied on yields of dry matter per unit of some input (typically land or water) cannot 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 model. Linear programming was used to find the most profitable mix of forage species for an irrigated dairy farm in an irrigation region of New South Wales, Australia. It was concluded that a typical farmer facing the prevailing milk and purchased feed prices with average milk production per cow would find a mix of species including large proportions of perennial ryegrass (Lolium perenne) and prairie grass (Bromus willdenowii) was most profitable. The result was robust to changes in seasonal milk pricing and moving from year round to seasonal calving patterns.Dairy, Forage, Whole-farm, Linear programming

Quantitative analysis of behaviour of grazing dairy cows

This research thesis describes the quantitative analysis of behaviour of grazing dairy cows in terms of sward height (SH) in combination with the length of the grazing session (grazing duration, GD), the time of allocation of fresh pasture and the type of carbohydrate supplement offered. A review of the literature (Chapter 2) identified that there was limited information on the combined affects of SH and GD on behaviour, herbage dry matter intake (DMI) and intake rate (IR) of dairy cows grazing sub-tropical pastures and how these interact to influence sward structure. Also, there was limited information on how SH x GD, time of allocation of fresh pasture and type of carbohydrate supplement offered affects the temporal patterns of behaviour and the subsequent time-dependent probabilities. In this current study, 2 levels of SH (10 and 13cm) and 5 levels of GD (1, 2, 4, 8 and 15h) were used to quantify the effects of SH and GD on dairy cow grazing behaviour, IR and herbage DMI. Sward height significantly (P70% of their total herbage DMI within the first 4h GD. Quantification of the sward profiles after each SH x GD combination showed that dairy cows grazing kikuyu using the management described in this current study did not graze at random. ... The results from this current thesis highlight the factors that either encourage or discourage grazing by dairy cows and should also help to improve decision tools used for pasture rotation, supplementary feeding and stocking density

"One size fits all"? - The relationship between the value of genetic traits and the farm system

The wide use of artificial insemination by dairy farmers has facilitated the development of a multi-billion dollar international market in animal genetics. In the major western dairy producing nations, each country has developed a single index to rank bulls, based on the value of traits they are expected to pass on to their offspring. One of the assumptions behind these indexes is that there is a positive linear relationship between profit (and welfare) with increases in a particular trait, regardless of the farm system. In this paper, it is shown, with examples, that the assumption of linearity is false. More importantly, it is shown that for a combination of reasons, including risk aversion, constraints and other issues, the optimal direction of genetic improvement for New Zealand dairy farmers on an individual and industry level could be quite different. Alternatives to the “one size fits all” index are described

Choosing the best forage species for a dairy farm: The whole-farm approach

Although a handful of forage species such as perennial ryegrass are predominant, there are a wide range of forage species that can be grown in sub tropical and temperate regions in Australia as dairy pastures. These species have differing seasonal yields, nutrient quality and water use efficiency characteristics, as demonstrated in a large study evaluating 30 species University of Sydney in New South Wales, Australia. Some species can be grazed, while others require mechanical harvesting that incurs a further cost. Previous comparisons of species that relied on yields of dry matter per unit of some input (typically land or water) cannot 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 model. Linear programming was used to find the most profitable mix of forage species for an irrigated dairy farm in an irrigation region of New South Wales, Australia. It was concluded that a typical farmer facing the prevailing milk and purchased feed prices with average milk production per cow would find a mix of species including large proportions of perennial ryegrass (Lolium perenne) and prairie grass (Bromus willdenowii) was most profitable. The result was robust to changes in seasonal milk pricing and moving from year round to seasonal calving patterns

An Economic Evaluation of the FutureDairy Complementary Forage Rotation System - Using Cost Budgeting

The complementary forage rotation (CFR) aims to achieve high levels of home-grown forage to complement high performance dairy pastures. Variable cost budgets indicate that total variable costs for CFR are similar to those of a well managed, high input pasture, approximately $110/t dry matter (DM) utilised (range being from$97 to $118 and from$98 to $128/t DM for CFR and Pasture treatments, respectively). The similar costs of forage production indicate that the potential of pasture production and utilisation should be fully exploited before CFR is considered, and CFR has potential to replace more expensive feeds such as concentrates. When concentrate was partially replaced by growing CFR, and including associated infrastructure costs, CFR had to occupy an area of more than 10 per cent of the dairy area of a modelled farm, when CFR occupied 20 per cent of the dairy area there was a 10 per cent reduction in feed costs. Stochastic budgeting was applied to examine fertiliser price risk and yield risk. Under fertiliser price variability the average cost of pasture was$121/t utilised DM and a maximum cost of $149/t DM, and the cost of CFR fodder was$112 and $123/t DM, respectively, due to the 2.3 times higher efficiency of use of nitrogen for the former than for the latter. Including forage yield variability, using minimum (~60 per cent less yield than target), most likely (~25 per cent less yield than target) and maximum (target yield) yield distributions, the CFR had a higher average cost of forage than the high input pasture system, being$139/t DM and $133/t DM respectively. The likelihood of reducing pasture utilisation for a ‘good’ pasture manager would be much lower than the risk of having a yield reduction in one or more of the CFR crops, was and reflected in the pasture system having a minimum yield only 33 per cent less than the target yield of 18 t DM/ha in the simulations undertaken. The risk analysis including both price and yield risk simultaneously, indicate that the average variable cost of CFR forage is similar to well managed, high input pasture

An Economic Evaluation of the FutureDairy Complementary Forage Rotation System - Using Cost Budgeting

The complementary forage rotation (CFR) aims to achieve high levels of home-grown forage to complement high performance dairy pastures. Variable cost budgets indicate that total variable costs for CFR are similar to those of a well managed, high input pasture, approximately $110/t dry matter (DM) utilised (range being from$97 to $118 and from$98 to $128/t DM for CFR and Pasture treatments, respectively). The similar costs of forage production indicate that the potential of pasture production and utilisation should be fully exploited before CFR is considered, and CFR has potential to replace more expensive feeds such as concentrates. When concentrate was partially replaced by growing CFR, and including associated infrastructure costs, CFR had to occupy an area of more than 10 per cent of the dairy area of a modelled farm, when CFR occupied 20 per cent of the dairy area there was a 10 per cent reduction in feed costs. Stochastic budgeting was applied to examine fertiliser price risk and yield risk. Under fertiliser price variability the average cost of pasture was$121/t utilised DM and a maximum cost of $149/t DM, and the cost of CFR fodder was$112 and $123/t DM, respectively, due to the 2.3 times higher efficiency of use of nitrogen for the former than for the latter. Including forage yield variability, using minimum (~60 per cent less yield than target), most likely (~25 per cent less yield than target) and maximum (target yield) yield distributions, the CFR had a higher average cost of forage than the high input pasture system, being$139/t DM and $133/t DM respectively. The likelihood of reducing pasture utilisation for a ‘good’ pasture manager would be much lower than the risk of having a yield reduction in one or more of the CFR crops, was and reflected in the pasture system having a minimum yield only 33 per cent less than the target yield of 18 t DM/ha in the simulations undertaken. The risk analysis including both price and yield risk simultaneously, indicate that the average variable cost of CFR forage is similar to well managed, high input pasture

An Economic Evaluation of the FutureDairy Complementary Forage Rotation System – Using Whole Farm Budgeting

A complementary forage rotation (CFR) aims to achieve high levels of home-grown forage to complement high performance dairy pastures. An economic evaluation of the CFR technology is undertaken by combining biophysical modelling with preliminary results from farm trials conducted at the University of Sydney’s Corstorphine Dairy. This data is applied to steady state whole farm budgets to compare four alternate or progressive scenarios that might be considered by farmers looking at the potential to increase farm productivity through their feeding system beyond a base farm scenario. A base scenario of a relatively well managed dairy farm in NSW, with 140 ha of milking area, stocked at 2.4 cows/ha, utilises about 12 t DM/ha/year under irrigation and produces more than 16,000 L/ha/year from 6,900 L/cow, achieves 0.9 per cent return on assets. A system with improved pasture management over the base scenario, utilising 15.6 t DM/ha/year and 1.3 t DM/cow/lactation of concentrates to achieve 6,900 L/cow obtains 3.4 per cent return on assets. A production system where pasture and supplement (concentrates) are emphasised achieves 6 per cent return on assets (3.7 cows/ha, 9,000L/cow and 2.3 t DM/cow/lactation concentrates). In comparison the CFS system obtains a return on total assets of 8 to 12 per cent, based upon actual or targeted (best case) forage yield results, respectively. The CFS-based farm business becomes relatively more profitable when scenarios with increased cost of fertiliser, water and especially grain are examined. A production system incorporating the complementary forage rotation (CFS) has the potential to be profitable. However, these analyses are based upon a steady state situation, after the implementation of the systems on farm, and implementation costs associated with adopting the technology on individual farms should be considered