For the 2016 analysis GrassGro™ was used to calculate the financial performance of each bloodline.
GrassGro™ is a decision support tool that uses historical weather data to drive models of pasture growth and animal production, with changes in the water content of the soil, pasture growth and decay and responses to grazing.
The greasy fleece weight, yield, fibre diameter and liveweight for each of the 77 bloodlines provided the livestock production parameters.
Enterprise structure, prices and costs were held constant and were reflective of a wether enterprise, with wethers shorn three times and then sold.
Median wool and prices for the 5 years from 2011 to the end of 2015 were used, as well as high (70 percentile) and low (30 percentile) wool prices. The median mutton price used was 304c/kg carcass weight.
High | Median | Low | |
---|---|---|---|
Micron | 70% | 50% | 30% |
16 | 1,393 | 1,473 | 1,540 |
17 | 1,335 | 1,419 | 1,514 |
18 | 1,274 | 1,349 | 1,475 |
19 | 1,205 | 1,292 | 1,404 |
20 | 1,164 | 1,230 | 1,328 |
21 | 1,156 | 1,218 | 1,297 |
The stocking rate (wethers/ha) was chosen such that the bloodline with the median liveweight would achieve the rule of maintaining a minimum ground cover of 70% for any day in 71% of the years.
The GrassGro™ simulations used typical soil, pasture and weather conditions for three sites, representing three different environmental systems with typical pastures for each location:
The GrassGro™ simulations generates an annual profit for each bloodline during the simulation period, from 1962 to the end of 2015, which accounts for the full range of seasonal conditions from drought through to long wet years. From this information, two measures of financial performance are provided:
The 2016 analysis includes a measure of the variability in financial performance of the bloodlines - the standard deviation (St dev) of profit on both a $/hd and $/DSE basis.
The standard deviation of profit provides an indication of the variation around the average profit on both a $/hd and $/DSE basis. A large standard deviation indicates greater variation in profit compared with a smaller standard deviation.