Precision sheep production: how within-flock selection lifts Merino profit

Why the question mattered#

Most Merino flocks are still run and improved the way they have been for generations. Maiden ewes and wethers enter the flock after visual classing, whole age groups leave together, and the genetic composition of the flock is largely set by which rams are bought in, usually from studs. Atkins and Richards describe this as flock-level management, where every animal in a class is treated the same way at minimum cost.

The paper sets out to test whether that approach still serves the industry well, given the pressure to raise productivity and hold terms of trade against competing industries. Drawing on earlier work by Rowe and Atkins, the authors argue that managing and selecting individual animals according to measured performance, rather than managing the flock as a block, offers a faster route to higher productivity and profit. They call this approach precision sheep production, and the report sets out to put numbers on what it might deliver.

The analysis also examines ram selection on its own, since the choice of ram is the dominant lever most producers already use to improve their flocks. The authors treat better ram selection and precision management as complementary strategies rather than alternatives, and test both separately and combined across the three enterprise types chosen to represent much of the Merino industry's spread of production systems.

How the modelling was built#

Rather than running a new flock trial, the paper builds and applies a set of linked production models developed by the authors and colleagues, including Selection Assist, a Flock Structure tool, a Terminal Flock Calculator, an OFFM (objective fibre measurement) Calculator, a Wether Calculator, a tool called Simultaneous Assortment, and a Ram Value Calculator. These tools track fleece weight, fibre diameter and body weight across every age group of ewes and wethers over a twenty-year horizon, using known genetic and phenotypic parameters and age effects drawn from earlier Merino studies, including unpublished Trangie data.

Three enterprise scenarios were modelled: a specialist fine wool flock of 2000 breeding ewes plus 1000 adult wethers at 18.5 micron, a medium wool flock of 3000 breeding ewes at 20.5 micron with no wethers, and a dual purpose flock of 2500 purebred breeding ewes plus 500 ewes joined to terminal sires at 22 micron. For each, the model compared basic genetics (average industry rates of gain), enhanced genetics (rams selected using Sheep Genetics breeding values and a selection index matched to the enterprise), and a precision production system layered on top of either genetic strategy.

Costs were built in for each option, including labour at $24 per hour, measurement equipment, contractor services and data handling, with three identification methods compared: visual tags, RFID with on-farm drafting, and RFID with a contractor. All financial outcomes are expressed as gross margin per Dry Sheep Equivalent, discounted to a Net Present Value using an annual discount rate of 5 percent, which the authors describe as reflecting a social rather than an alternative investment rate.

What the fine wool scenario showed#

In the fine wool flock, starting gross margin was $26.21 per DSE. Ram selection alone added $3.55 per DSE under basic genetics and $7.32 under enhanced genetics. Adding precision production lifted the gain to $11.93 under basic genetics and $16.04 under enhanced genetics, against additional annual costs of $1.18 to $3.31 per DSE depending on the strategy. Over ten years profit rose by 21 percent from enhanced genetics alone, 28 percent from precision production, and 49 percent from the two combined.

Most of the precision production gain came from flock selection: keeping higher value ewes and wethers and culling the less valuable animals, described by the authors as current generation improvement. Clip preparation using measured fibre diameter and optimising the flock's age structure added smaller gains, but both easily covered their modest costs. Discounted profit in year ten reached $42,100 for enhanced genetics plus precision production against $17,800 for enhanced genetics alone, and the Net Present Value of the cumulative gain from precision production over ten years was estimated at $178,000, with investment costs recovered within two to three years.

Production changes mirrored the financial ones. Fibre diameter in adult ewes fell from 18.5 micron at the start to 17.2 micron under enhanced genetics plus precision production, with the authors noting the effect on current adult animals was considerably larger than the slower genetic effect visible in hoggets.

Medium wool and meat plus wool results#

The medium wool flock, with a starting gross margin of $22.23 per DSE, showed a similar pattern at a slightly lower scale: ram selection alone added $1.62 to $3.87 per DSE depending on genetic strategy, while ram selection plus precision production added $6.64 to $10.43. Precision production on its own contributed a 24 percent increase in profit over ten years, and discounted profit in year ten reached $22,600 in Net Present Value. Here, selling surplus animals as Merino lambs once they reached 48kg, identified through weight recording, made a substantial contribution alongside flock selection and clip preparation.

The meat plus wool flock, starting at $23.24 per DSE, showed the smallest contribution from ram genetics of the three systems but the largest relative role for precision production. Precision production added a 16 percent increase in profit over ten years, with discounted year ten profit of $15,200 in Net Present Value. Gains here came from allocating ewes to wool or meat production streams based on measured performance rather than age, from marketing lambs against weight specifications, and from identifying crossbred lambs likely to miss carcase targets early enough to manage them differently.

How much weight these figures can bear#

Across all three systems, the headline conclusion is that increases in profit of 28 percent, 24 percent and 16 percent, for fine wool, medium wool and dual purpose flocks respectively, are achievable through precision production alone, and that combining it with enhanced genetics could lift total profit gains to between 26 and 49 percent across scenarios. The authors frame this against an industry-wide productivity gain of 0.6 percent a year, suggesting a move to 3 to 5 percent annual gain would put sheep production on a competitive footing with cropping and cattle.

These are modelled outcomes, not results measured on a commercial flock over ten real years. The model draws on parameters from earlier published studies and unpublished data, and on market prices averaged over five years, so its accuracy rests on how well those inputs reflect conditions a given producer actually faces. We would treat the relative ranking of strategies, and the broad message that flock-level selection adds meaningfully to ram-based genetic gain, as the most robust takeaway, rather than treating any single dollar figure as a guarantee for an individual property.

Connecting precision sheep production to the broader literature#

The report positions precision sheep production as building on, rather than replacing, standard ram selection through Sheep Genetics breeding values and selection indexes. It also draws on a line of earlier work by the same authors and collaborators on fibre diameter measurement for clip preparation, optimal wether management, and tools for assorting animals between wool and meat production, citing Morley on measured fleece trait selection and Richards and Atkins on highly selected wether flocks as examples of these components already being applied on their own elsewhere in the literature.

The authors argue that treating selection of replacements, flock structure, and clip or carcase targeting as one integrated system, rather than as separate decisions made in isolation, is what produces the larger combined gains shown in the three scenarios. This framing echoes the paper's description of its own three-part strategy, where basic genetics, enhanced genetics and precision production were deliberately tested both alone and layered together rather than treated as competing options.

What it suggests for flock management#

For producers already buying rams through Sheep Genetics breeding values, the paper's modelling suggests that adding measurement-based selection within the flock, rather than relying on visual classing of whole age groups, could capture a further and largely additive gain in profit. The practical levers identified are selecting replacement ewes and wethers on measured fibre diameter, fleece weight or body weight; adjusting the number of age groups kept in the flock to sharpen selection differentials; and using objective measurement to direct wool into better-paying lots or lambs into the right market specification.

The paper is explicit that the three identification and measurement options it costed, visual tags, RFID with on-farm drafting, and RFID with a contractor, differ mainly in how the cost is split between farm labour and capital or contractor services, rather than in total cost. It also flags that visual tagging carries an unquantified risk of recording errors of 5 to 10 percent, a practical detail that matters as much as the headline profit figures when a producer is choosing between measurement systems on a working property. This report sits in the Project 1.1 Matching genetics with production systems collection alongside other unpublished sheep CRC reports held in the index's unpublished reports community, and shares its focus on measurement-based flock decisions with the index's summary of labour efficiency in sheep enterprises.

Sources and further reading#

• Trove library search: find a library that holds the paper
• Meat & Livestock Australia: red meat industry research and marketing body
• Australian Wool Innovation: wool industry research and marketing body
• Sheep Genetics (LAMBPLAN and MERINOSELECT): which runs LAMBPLAN and MERINOSELECT

Questions#

— The Livestock Library team