| Name of supporting tool: |
|
| Developer(s): |
Mandy Curnow, Peter Robson, Sandra Brown, ASHEEP group (Esperance) |
| Aims/use: |
It sets out the key management operations in the sheep breeding year so that farmers can make informed choices on timing and activities to improve lambing percentages. |
| Key features: |
Provides the latest best practice advice regarding ewe and ram nutrition, condition score targets, reproductive management and lambing guidelines. |
| Audience: |
Farmers, extensionists, students. |
| Regions, scale, time of year: |
WA version and Eastern States versions available. |
| Types of decisions: |
Joining time, FWEC (faecal worm egg count) timing, teasing and nutritional decisions. |
| Strengths/limitations: |
NA |
| Inputs: |
Joining date or lambing date |
| Outputs: |
Dates of all important actions needed for improving lambing percentages. |
| Expertise/system r'quts: |
Basic hand held wheel device |
| Availability/status: |
Free to all growers and students. Further information is provided under "pasture management" at www.agric.wa.gov.au (pasture management) |
| Contact: |
Available from district offices or P. Fumagalli, Tel: (08) 98928444, Email: pfumagalli@agric.wa.gov.au |
| Name of supporting tool:
|
Green Feed Budget Calculator (sheep)
|
| Developer(s):
|
Mandy Curnow, David Weaver, Mike Hyder
|
| Aims/use:
|
To provide an electronic calculation of sheep feed budgets at a paddock scale during the 'green' season with a number of different scenarios.
|
| Key features:
|
1. Calculates stocking rates for a particular paddock. 2. Calculates sheep numbers for a range of paddock objectives. 3. Gives an estimate of deferment time during autumn. 4. Strip grazing stocking calculations. 5. Supplementary feed calculator during autumn.
|
| Audience:
|
Farmers using PGR (pasture growth rate) and FOO (feed on offer) estimates, agricultural college students, development officers, consultants giving feeding advice.
|
| Regions, scale, time of year:
|
Annual based pastures all year,
perennials during spring, sheep and grain belt in WA; paddock; pasture growing season (not dry feed season).
|
| Types of decisions:
|
Stocking rates, strip grazing, supplementary feeding
|
| Strengths/limitations:
|
Relies on accurate assessment of green feed in the paddock. Not suited to very grassy pastures in beef areas. Not for use during summer and dry pasture.
|
| Inputs:
|
Feed on Offer, PGRs, stock numbers and class, paddock area.
|
| Outputs:
|
Stocking rates for a particular paddock for a range of paddock objectives. Supplementary feed calculator during autumn.
|
| Expertise/system r'quts:
|
Basic computer skills; Windows 95 or better, CD-ROM, Mac version available.
|
| Availability/status:
|
Package of explanatory notes and computer disk available for $15 from Department of Agriculture, Albany,Ph: 98928422; Further information is provided under "pasture management" at www.agric.wa.gov.au ( pasture management) |
| Contact:
|
Mandy Curnow, Dept of Agriculture WA, 444 Albany Hwy, Albany 6325,
Email: mcurnow@agric.wa.gov.au
|
| Name of supporting tool:
|
MIDAS
|
| Developer(s):
|
David Morrison and Dr. Ross Kingwell, although valuable assistance was provided by a host of collaborators.
|
| Aims/use:
|
Further research, economic scenario planning.
|
| Key features:
|
The MIDAS computer models represent the economics and biology of farming in the grain and sheep belts of Western Australia.
|
| Audience:
|
Extensionists, researchers and consultants.
|
| Regions, scale, time of year:
|
There are versions of MIDAS in working order for the eastern wheatbelt, central wheatbelt, south coast and Great Southern.
|
| Types of decisions:
|
The model is run to try to identify robust results which can be extended to groups of farmers. For example, MIDAS has been used to assess optimal rotational changes in response to changes in the prices of commodities (such as sheep meat, wool and grains) and inputs (such as fertiliser, fuel and labour) taking account of the interactions between componentes of a farming system". |
| Strengths/limitations:
|
[Expired]
|
| Expertise/system r'quts:
|
For more detailed information is available under ‘MIDAS’ at www.agric.wa.gov.au
(MIDAS) |
| Availability/status:
|
Not for individual use
|
| Name of supporting tool:
|
|
| Developer(s):
|
Dr. Steve Gherardi , Department of Agriculture, G Mata, CSIRO and Fairport Technologies
|
| Aims/use:
|
To provide real time pasture information and a range of tools to make grazing decisions.
|
| Key features:
|
Pastures from Space web site– pasture growth rates at farm scale, Pasture Watch – decision tool for pasture budgeting, pasture grazing planner.
|
| Audience:
|
Any landholder
|
| Regions, scale, time of year: |
Southern Australia agricultural areas during the growing season. |
| Types of decisions:
|
Grazing pressure, stocking rate, deferment times.
|
| Strengths/limitations:
|
Weekly predictions of PGR (pasture growth rate) provided.
|
| Inputs:
|
Paddock names, animals class and number, FOO (feed on offer) estimates.
|
| Outputs:
|
Stocking rates etc.
|
| Expertise/system r'quts:
|
Digitised farm map, internet access.
|
| Availability/status:
|
$500 -$750 annually
|
| Contact:
|
Dr Steve Gherardi, Department of Agriculture, South Perth, Tel: (08) 9368 3333, Email: sgherardi@agric.wa.gov.au or Fairport Technologies 1800 500 195, Email: www.fairport.com.au/PastureWatch
|
| Name of supporting tool:
|
|
| Developer(s):
|
Andrew Peterson
|
| Aims/use:
|
To manage wool fibre profile throughout the growing season.
|
| Key features:
|
Pictorial representation of your wool fibre profile, calculations of fleece value and estimated clean fleece weight.
|
| Audience:
|
Wool producers
|
| Regions, scale, time of year:
|
Southern Australia agricultural areas during the growing season. |
| Types of decisions:
|
Adjustment of feed regimes to match fibre diameter targets. |
| Strengths/limitations:
|
Windows 98 or better, some glitches on some computers.
|
| Inputs:
|
Fibre diameter and length of wool profile throughout season.
|
| Outputs:
|
Fibre profile and predicted fleece value.
|
| Expertise/system r'quts:
|
Basic Computer skills
|
| Availability/status:
|
By request
|
| Contact:
|
Andrew Peterson, Department of Agriculture, South Perth, Tel: (08) 9368 3333, Email: apeterson@agric.wa.gov.au
|
| Name of supporting tool:
|
|
| Developer(s):
|
Johan Greeff
|
| Aims/use:
|
The is a decision support tool for Merino wool producers for measuring profitability of carrying out in-shed testing of fibre diameter.
|
| Key features:
|
This is based on the fact that sheep that produce more and finer wool than their contemporaries will tend to continue to produce more and finer wool during their lifetime in the flock.
|
| Audience:
|
Wool producers
|
| Regions, scale, time of year:
|
Anytime or region
|
| Types of decisions:
|
Whether to in-shed test ewe flock to achieve wool breeding objectives.
|
| Inputs:
|
The size of the breeding ewe flock, the number of replacement hogget ewes available, the average fleece weight, average fibre diameter and clean yield of hogget and mature ewes in the flock.
|
| Outputs:
|
Amount of profit due to testing ewe flock over 10 years.
|
| Expertise/system r'quts:
|
Access to the Department of Agriculture’s web site.
|
| Availability/status:
|
Further information is provided under "fleece calculator " at www.agric.wa.gov.au (fleece calculator ) |
| Contact:
|
Johan Reef, Tel: (08) 9821 3333, Email: greeff@agric.wa.gov.au
|
| Name of model:
|
Anthracnose Tracer
|
| Developer(s):
|
Dr. Moin Salam, Dr. Art Diggle, Mr. Geoff Thomas and Dr. Mark Sweetingham
|
| Aims/use:
|
To estimate spatio-temporal dispersion of anthracnose in lupins in a paddock from infected seeds.
|
| Key features:
|
Based on detected level of seed infection, the model shows the expected loss of crop population due to anthracnose.
|
| Audience:
|
Farmers, consultants, advisers
|
| Regions, scale, time of year:
|
Broadacre agriculture; Paddock; During seed selection
|
| Types of decisions:
|
Whether to use the seed for sowing; fungicide decisions
|
| Strengths/limitations:
|
Strength: Gives good prediction of anthracnose spread from infected seeds and also from infected blue lupins along the fence; gives a pictorial (spatial) view. Limitations: Users would require special skills and software to run this model.
|
| Inputs:
|
Weather/climate information of the concerned location (daily max and min temperature, hourly rainfall, wind speed and wind direction); level (%) of seed infection.
|
| Outputs:
|
Percent loss of lupin population due to anthracnose infection in a paddock.
|
| Expertise/system r'quts:
|
More than basic computer skills; requires Mathematica software and relatively large RAM.
|
| Availability/status:
|
On request; users can ask for an output from contact person; Released 2001. Development on-going.
|
| Contact:
|
Dr Moin Salam, Centre for Cropping Systems, Department of Agriculture, PO Box 483, Northam 6401. Tel: (08) 9690 2000, Fax (08) 9622 1902, Email: msalam@agric.wa.gov.au
|
| Name of model:
|
APSIM (Agricultural Production Systems Simulator)
|
| Developer(s):
|
APSRU (Agricultural Production Systems Research Unit)
|
| Aims/use:
|
Model of crop growth. Can be used for rotations, mixtures or weeds. Can be sued to produce outputs for any part of the system (e.g. soil water, breakdown of residues).
|
| Key features:
|
Daily time-step calculations of crop growth based on potential assimilate production modified by nitrogen or water stress.
|
| Audience:
|
Researchers and modellers (potential to produce secondary or tertiary products or outputs for farmers or advisers).
|
| Regions, scale, time of year:
|
International--has been validated for WA, eastern Australia and Africa; point, scale up to paddock; anytime as can generate outputs for any part of the system.
|
| Types of decisions:
|
Crop production under different seasons, environments and management.
|
| Strengths/limitations:
|
Flexible outputs from a detailed simulation model. Requires time to set up input files and expertise to run the model.
|
| Inputs:
|
Daily rainfall, radiation, max/min temp, soil parameters, crop parameters, residue parameters, management information.
|
| Outputs:
|
Almost unlimited. Any of the aspects that are modelled: crop growth, quality, soil water, nitrate leaching, residue breakdown, weather information.
|
| Expertise/system r'quts:
|
Need to be a licensed user and to have expertise/training to run the model; Windows-based PC.
|
| Availability/status:
|
Available from APSRU as licensed user; Version 2.1 released October 2001.
|
| Contact:
|
APSRU
|
| Name of model:
|
|
| Developer(s):
|
Drs. Moin Salam, Ravjit Khangura, Art Diggle and Martin Barbetti
|
| Aims/use:
|
To predict the time of onset of blackleg spore maturity.
|
| Key features:
|
Forecast status of the maturity of blackleg fruiting bodies on canola stubble; forecast onset of blackleg ascospore shower in the region.
|
| Audience:
|
Farmers, consultants, advisers
|
| Regions, scale, time of year:
|
Broadacre agriculture; district/region; 1 to 2 months before seeding time.
|
| Types of decisions:
|
Sowing, fungicide decision
|
| Strengths/limitations:
|
Good prediction of maturity of spores (fruiting bodies); not yet been related to yield loss.
|
| Inputs:
|
Daily weather data (max and min temperatures and rainfall).
|
| Outputs:
|
Status of maturity of spores and time of arrival of first ascospore showers (in relation to blackleg in canola) in the region.
|
| Expertise/system r'quts:
|
Basic computer skills; compatible with Excel 5 or better. |
| Availability/status:
|
Forecasts are provided in PestFax and on the Department of Agriculture website (www.agric.wa.gov.au); released 2002. Development on-going. Available on request. Search for "plant disease forecast 2006" on the Department of Agriculture or click the hyperlink www.agric.wa.gov.au/cropdisease |
| Contact:
|
Dr Moin Salam, Centre for Cropping Systems, Department of Agriculture, PO Box 483, Northam 6401. Tel: (08) 9690 2000, Fax (08) 9622 1902 Email: msalam@agric.wa.gov.au
|
| Name of model:
|
Blackspot Manager
|
| Developer(s):
|
Dr. Moin Salam, Ms Jean Galloway, Dr. Art Diggle and Mr. Bill MacLeod
|
| Aims/use:
|
Estimate development and spread of blackspot in field peas.
|
| Key features:
|
Taking history of field peas in a region, the model shows to what extent the blackspot may spread in the region.
|
| Audience:
|
Farmers, consultants, advisers |
| Regions, scale, time of year:
|
Broadacre agriculture; District/region; Any time, would be best
during paddock selection decision making.
|
| Types of decisions:
|
Paddock selection; enables management of blackspot through manipulating time of sowing.
|
| Strengths/limitations:
|
Strength: Gives good prediction of blackspot spread in fieldpeas. Limitations: Users would require special skills and software to run this model.
|
| Inputs:
|
Weather/climate information of the location (daily max and min temperature, hourly rainfall, wind speed and wind direction); paddock history (field peas only) in the region.
|
| Outputs:
|
Extent and intensity of blackspot spread.
|
| Expertise/system r'quts:
|
More than basic computer skills; requires Mathematica software and relatively large RAM.
|
| Availability/status:
|
On request; users can ask for an output from contact person; Released a preliminary version in 2002. Development on-going.
Available from the Department of Agriculture website(www.agric.wa.gov.au) and search for "plant disease forecast 2006" or click the hyperlink www.agric.wa.gov.au/cropdisease |
| Contact:
|
Dr Moin Salam, Centre for Cropping Systems, Department of Agriculture, PO Box 483, Northam 6401. Tel: (08) 9690 2000,
Fax (08) 9622 1902, Email: msalam@agric.wa.gov.au
|
| Name of model:
|
Blackleg Risk Appraisal Tool (BRAT)
|
| Developer(s):
|
Dr. Moin Salam, Dr. Ravjit Khangura, Mr. Paul Carmody, Dr. Art Diggle and Dr. Martin Barbetti
|
| Aims/use:
|
A tool for assessing the risk associated with the onset of ascospore showers coinciding with the most susceptible stage of canola.
|
| Key features:
|
Blackleg Risk Appraisal Tool. Tracks down the status of the maturation of blackleg fruiting bodies on canola stubble; forecast onset of blackleg ascospore shower in a selected district or region; guides sowing time and fungicide interactions.
|
| Audience:
|
Consultants and growers
|
| Regions, scale, time of year:
|
All; District/region; Preseason
|
| Types of decisions:
|
Sowing time vs blackleg risk
|
| Strengths/limitations:
|
Modification of Blackleg Sporacle into a user-friendly tool.
|
| Inputs:
|
Daily weather data (max and min temperatures and rainfall).
|
| Outputs:
|
Projected date on beginning of ascospore showers.
|
| Expertise/system r'quts:
|
Basic spreadsheet; MS Excel-based
|
| Availability/status:
|
Available from the Department of Agriculture website(www.agric.wa.gov.au) and search for BRAT or www.agric.wa.gov.au/cropdisease. |
| Contact: |
Dr Moin Salam, Centre for Cropping Systems, Department of Agriculture, PO Box 483, Northam 6401. Tel: (08) 9690 2000, Fax (08) 9622 1902 Email: msalam@agric.wa.gov.au |
| Name of model:
|
BYDV Risk Forecast
|
| Developer(s):
|
Debbie Thackray , Art Diggle and Roger Jones, with GRDC funding
|
| Aims/use:
|
To predict risk of yield loss from barley yellow dwarf virus (BYDV) spread in cereals in different areas of the WA grainbelt.
|
| Key features:
|
A computer simulation model predicts when aphids are expected to start arriving in cereal crops, incidence of BYDV spread by them and yield losses from BYDV damage. Maps on an internet site (www.agric.wa.gov.au/bydv) illustrate model predicted risk on a shire basis.
|
| Audience:
|
Farmers and advisers, researchers, students.
|
| Regions, scale, time of year:
|
Internet based forecasts are for each shire in the medium and high annual rainfall zones of WA. Forecasts are issued in late April each year.
Model can be run for any location in WA grainbelt with daily rainfall and temperature data available and anytime from mid-April onwards.
|
| Types of decisions:
|
Risk forecasts assist users in making their own decisions about the need for early-season insecticide spray applications to control the aphids spreading BYDV. Information on insecticides and spray timing is also provided on the internet site.
|
| Strengths/limitations:
|
The forecasts give a good indication of when aphids are first likely to be in the crop and whether or not control is worthwhile. This replaces the need for, or enhances, crop inspections for aphids early in the growing season. This is useful because considerable virus spread can occur when only a few aphids are visible in the crop and these aphids are hard to find unless searches are done very thoroughly.
A limitation is that currently inputting climate data to do model runs is time consuming, so for the internet forecasts they are only done for one location in a shire, although for different sowing dates. In the future we hope to automate model runs and perhaps make the model itself available over the internet.
|
| Inputs:
|
For the model: sowing date, and daily rainfall and temperature data.
For the internet forecasts: sowing date, then look for your location on the map.
|
| Outputs:
|
From the model: start of aphid immigration, BYDV incidence, yield loss from BYDV damage.
From the internet site: yield loss from BYDV damage for each shire, for a range of sowing dates.
|
| Expertise/system r'quts: |
Internet forecasts: Familiarity with internet navigation. Usual system requirements for internet use.
Model: Ability to follow simple instructions and a little familiarity with typing information into boxes. Model is built using “Stella” software, but user does not need to be familiar with it. |
| Availability/status: |
Forecasts available each growing season in late April through internet site: www.agric.wa.gov.au/bydv.
Model not currently available, except through direct contact with Debbie Thackray . In the future, we hope to automate climate data retrieval and make the model available on the internet or on a CD. |
| Contact: |
Debbie Thackray, Tel: (08) 6488 7574; Email: djthack@clima.uwa.edu.au |
| Name of model: |
CMV Risk Forecast
|
| Developer(s): |
Debbie Thackray , Art Diggle and Roger Jones, with GRDC funding. |
| Aims/use: |
To predict risk of yield loss from cucumber mosaic virus (BYDV) spread in lupins in different areas of the WA grainbelt.
|
| Key features: |
A computer simulation model predicts when aphids are expected to start arriving in lupin crops, incidence of CMV spread by them from infected seed and yield losses from CMV damage. Maps on an internet site illustrate model predicted risk on a shire basis. |
| Audience: |
Farmers and advisers, researchers, students. |
| Regions, scale, time of year: |
Internet based forecasts are for each shire in the medium and high annual rainfall zones of WA. Forecasts are issued in late April each year.
Model can be run for any location in the WA grainbelt with available daily rainfall and temperature data and anytime from mid-April onwards. |
| Types of decisions: |
Risk forecasts assist users in making their own decisions about the need for sourcing uninfected seed or using pre-sowing cultural control measures to decrease CMV spread by aphids. Information on these methods and how they work is also provided on the internet site. Knowing how much yield might be lost can also assist users in decisions about the economic benefit of other crop inputs. |
| Strengths/limitations: |
The forecasts give a good indication of when aphids are first likely to be in the crop and whether or not control is worthwhile. This replaces the need for, or enhances, crop inspections for aphids early in the growing season. This is useful because considerable virus spread can occur when only a few aphids are visible in the crop and these aphids are hard to find unless searches are done very thoroughly. The simulation model also makes it easier for users to understand the implications of sowing seed with a range of different infection levels and how altering sowing date can affect the risk of spread.
A limitation is that currently inputting climate data to do model runs is time consuming, so for the internet forecasts they are only done for one location in a shire, although for a range of sowing dates. In the future we hope to automate model runs and perhaps make the model itself available over the internet. |
| Inputs: |
For the model: level of seed infection, sowing date, and daily rainfall and temperature data.
For the internet forecasts: level of seed infection, sowing date, then look for your location on the map. |
| Outputs: |
From the model: start of aphid immigration, CMV incidence, yield loss from CMV damage, CMV infection in seed at harvest.
From the internet site: yield loss from CMV damage for each shire, for a range of sowing dates. |
| Expertise/system r'quts: |
Internet forecasts: Familiarity with internet navigation. Usual system requirements for internet use.
Model: Ability to follow simple instructions and a little familiarity with typing information into boxes. Model is built using “Stella” software, but user does not need to be familiar with it. |
| Availability/status: |
Forecasts available each growing season in late April through internet site: [Expired] www.agric.wa.gov.au/cmv.
Model not currently available, except through direct contact with Debbie Thackray . In future, we hope to automate climate data retrieval and make model available on the internet or on a CD. |
| Contact: |
Debbie Thackray, Tel: (08) 6488 7574; Email: djthack@clima.uwa.edu.au |
| Name of model: |
e-VarietyProfiler
|
| Developer(s): |
Dr. Moin Salam, Kawsar Salam, Blakely Paynter, Graham Walton, Geoff Thomas, Kedar Adhikari, Harmohinder Dhammu and Greg Shea |
| Aims/use: |
To assist growers with choosing a variety to suit their circumstances. |
| Key features: |
It collates scattered information from the Crop Variety Sowing Guide and other sources, such as agronomic trials, and arranges that information in profiles of physical characteristics, disease risk, abiotic stresses, herbicide tolerance and yield. It also provides and opportunity to obtain potential net return from a variety in a given location. Users can compare up to six varieties side by side at a time. |
| Audience: |
Growers, Consultants |
| Regions, scale, time of year: |
The current version of the profiler includes varieties of five crops for Western Australia- 53 wheat, 24 barley, 14 oats, 15 lupins and 37 canola. |
| Types of decisions: |
Variety selection/comparison |
| Strengths/limitations: |
Strength:A quick way to compare crop varieties. Limitation: Need MS-Excel software to run. |
| Inputs: |
Location, crop varieties |
| Outputs: |
Varietal characteristics and gross return. |
| Expertise/system r'quts: |
Windows 98, Windows XP, Microsoft 97 or onwards |
| Availability/status: |
Free cd, eVarietyProfiler can be downloaded from dept's web page: http://agric.wa.gov.au/ search for e-variety profiler |
| Contact: |
Dr Moin Salam, Centre for Cropping Systems, Department of Agriculture, PO Box 483, Northam 6401. Tel: (08) 9690 2000, Fax (08) 9622 1902, Email: msalam@agric.wa.gov.au |
| Name of model: |
e-Variety Guide for Stripe Rust
|
| Developer(s): |
Dr. Moin Salam, Ms Megan Collins, Dr. Art Diggle and Dr. Rob Loughman |
| Aims/use: |
To select right variety for stripe rust |
| Key features: |
This estimator compares the economic return of two varieties by Agzone. It takes account of potential yields and the risk of stripe rust in each Agzone, as well as the costs of chemical control, the cost of changing variety and wheat prices. |
| Audience: |
Consultants and advisers |
| Regions, scale, time of year: |
Wheat belt; AgZone/Independent; During seed selection (harvesting). |
| Types of decisions: |
What variety be used for next season |
| Strengths/limitations: |
Easy to use tool; it does not consider effect of stem and leaf rust; so care should be taken while using this. |
| Inputs: |
Virtually nothing; but user can change the default values. |
| Outputs: |
Net returns from variety A and B |
| Expertise/system r'quts: |
Basic computer skills; Compatible with Excel 5, 95, 97 & 98 on Windows and Macintosh systems (untested for later versions, but should work). |
| Availability/status: |
On diskette or electronically; Released 2002; updated Feb 2003 |
| Contact: |
Dr Moin Salam, Centre for Cropping Systems, Department of Agriculture, PO Box 483, Northam 6401. Tel: (08) 9690 2000, Fax (08) 9622 1902, Email: msalam@agric.wa.gov.au |
| Name of model: |
Resistance and Integrated Management model(RIM) |
| Developer(s): |
Dr David Pannell, Vanessa Stewart, Anne Bennett, Marta Monjardino, Carmel Schmidt and Professor Steven Powles. |
| Aims/use: |
A decision tool for investigating the biological and economic impacts of weed management options for annual ryegrass. |
| Key features: |
Allows the evaluation of different weed management technologies over a 10 year rotation. Through selecting different treatments can observe impact of weed numbers and $/ha returns over time. Simulation model incorporating biological and economic data on weed management. |
| Audience: |
Farmers, agronomists, researchers all agri industry |
| Regions, scale, time of year: |
NA |
| Types of decisions: |
Broadacre agriculture - standard/default assumptions set for Eastern wheatbelt, designed so that can easily adjust key parameters for different regions; weeds/m2; $/ha - extrapolate to paddock/farm implications; Can use at any time - run workshops in Autumn/spring |
| Strengths/limitations: |
Can readily observe the impact of incorporating or excluding various weed management techniques from integrated weed management strategies. Can see impact that these treatments have in year applied and is successive years of rotation. Easy to adjust parameters to "regionalise", Fantastic interactive workshop tool, Excellent for conducting sensitivity analysis. Weaknesses - assumptions based on "average expected outcome" - no year to year variation |
| Inputs: |
To select treatments user enters an x; Can alter most assumptions to allow sensitivity analysis or to regionalise |
| Outputs: |
Weeds/m2; Seed production/m2; $/ha; annualised $/ha over length of rotation and many more |
| Expertise/system r'quts: |
Basic computer skills, some understanding of farming systems, innovative thinking; Excel 97 or better |
| Availability/status: |
On request - Top Active Package or RIM package $55 inc GST; Released 1998; Updated Jan 2003 |
| Contact: |
Vanessa Stewart, Tel: (08) 9081 3111, Dept of Agriculture, Merredin; Dr Rick Llewellyn, WAHRI (08) 9380 3419 |
| Name of model: |
Flowering Calculator |
| Developer(s): |
Dr David Tennant |
| Aims/use: |
A model to calculate flowering time for a selection of crops and varieties to ensure optimum flowering time and ultimately grain yield. |
| Key features: |
Advanced graphical user interface makes it easy to show 'flowering window' limits for selected crops and varieties |
| Audience: |
Department researchers and advisers; consultants |
| Regions, scale, time of year: |
Grainbelt; Farm/shire; Start of season |
| Types of decisions: |
Which variety and when to sow it? |
| Strengths/limitations: |
Easy to use. Easy to understand outputs. At prototype stage. |
| Inputs: |
Rainfall, temperatures, phenological information |
| Outputs: |
Graphical displays of the flowering window with frost, temperature and flowering events; calculates and displays probabilities of temperature events and frost events. |
| Expertise/system r'quts: |
Basic computer skills; Minimum system requirements: IBM-compatible PC with minimum specifications of Pentium 90, 16 Mb RAM, CD-ROM, 800x600 display, Windows 95. |
| Availability/status: |
On request; on CD; Beta version available |
| Contact: |
Dr Meredith Fairbanks, Tel: (08) 9441 8112 , Email: mfairbanks@agric.wa.gov.au |
| Name of model: |
NP Decide
|
| Developer(s): |
Mr Steve Burgess, Drs Art Diggle and Bill Bowden |
| Aims/use: |
To address nitrogen and phosphorus fertiliser decisions
|
| Key features: |
Predicts fertiliser N P yield and dollar response surfaces for any yield potential and soil P and N status. Has a soil P calculator. Takes account of the effects of take-all on responses too different N sources. |
| Audience: |
Consultants, advisers and farmers |
| Regions, scale, time of year: |
Wheat growing areas; Paddock; Can be used both strategically and tactically (i.e. all year) |
| Types of decisions: |
Fertiliser (NP) type, rate and timing for cereal crops |
| Strengths/limitations: |
Handles N and P together, gives a two fertiliser matrix output. Has simple save and recall routines. Does not consider grain quality effects. |
| Inputs: |
Soil type, soil P test, cropping history, yield potential, take-all severity, rainfall zone, costs and prices. |
| Outputs: |
Two fertiliser rate matrix of yield, current returns and returns considering future value of phosphorus. |
| Expertise/system r'quts: |
Basic computer skills; PC running Windows operating system. |
| Availability/status: |
Available on floppy disk; Last update 1992 |
| Contact: |
Dr Bill Bowden, Centre for Cropping Systems,
Department of Agriculture, PO Box 483, Northam 6401. Tel: (08) 9690 2190, Fax:
(08) 9622 1902, Email: bbowden@agric.wa.gov.au |
| Name of model: |
OPTLIME |
| Developer(s): |
Mr Andrew Sandison, Mr Michael O'Connell |
| Aims/use: |
1. To explore the chemical/biological and financial responses to managing soil acidity using lime. 2. To assess the impact or relative differences between different management strategies eg increased tolerance to acidity in the rotation, vs. management with topsoil or subsurface liming and wider range of options in the rotation. |
| Key features: |
Allows input of soil parameters specific to situations. Allows wide range of options and the ability to change these options between two concurrent analyses. |
| Audience: |
Development Officers, advisers and consultants and leading farmers
|
| Regions, scale, time of year: |
Productive agriculture, excluding horticulture enterprises. Best calibrated to grainbelt but includes pasture options and higher rainfall zone capability; Paddock scale application; Any time, but if used in conjunction or as a decision aid for lime purchases best used following harvest to early May. |
| Types of decisions: |
Soil acidity management decisions including lime quantity and potentially crop decisions
|
| Strengths/limitations: |
Brings together a wealth of information that has been developed specifically for WA conditions. Outputs are dynamically linked and updated as factors in the scenario are altered. No viable competitor at present. Is not a lime recommendation tool but rather a decision aid. Calibrates to applications of lime within the "normal" range used under field conditions (i.e. 0-4 t/ha) per 5-10 years. |
| Inputs: |
Annual rainfall, Soil description, 7 choices from sand to heavy clay, for three layers, Starting soil pH profile, Starting Al toxicity profile, % Gravel, Bulk density, pH buffering capacity, Lime Quality and cost, Transport and spreading costs, Costs associated with deep banding of lime, Up to a 10 year crop rotation chosen from 16 enterprises (rotation then extended to 25 yr time frame for analysis), Yield potential of crops/product (acidity non-limiting), Crop tolerance to acidity, Fertiliser/rate applied (can enter two fertilisers per yr), Lime applications to surface or choice of depths in any of the 25 years. |
| Outputs: |
Results of analysis prepared for printing, Investment appraisal, Graphical representation of outputs as below, Limed soil pH profile (select up to 4 yrs from 25), Unlimed soil pH profile (select up to 4 yrs from 25), Effects of treatments on toxic Aluminium by soil layer, Relative yields with time. Annual and accumulated cash flow, Lime removal (separated into total, products, fertiliser and leached contributions), Fate of applied lime. |
| Expertise/system r'quts: |
Workshop training; PC computer with Microsoft Excel (Needs to be more fully tested to identify situations where it does not run) |
| Availability/status: |
Available on CD with pdf users manual after training in workshop; Released in October 2002, refinement continuing
Link: [Expired] |
| Contact: |
Mr Chris Gazey, Tel: (08) 9690 2000, Department of Agriculture, Northam.
|
| Name of model: |
Potential Yield Calculator (PYCAL) |
| Developer(s): |
Dr David Tennant |
| Aims/use: |
1. To estimate stored soil water at the start of the growing season or at planting. 2. To forecast potential yield for a range of cereal, legume and oilseed crops as the season progresses and calculate potential yield at end of season. |
| Key features: |
Estimates stored soil moisture at planting or at start of growing season; Charts rainfall received against expected decile rainfall totals or rainfall received in earlier years; Identifies planting opportunities using a planting rule that can be user modified to suit local conditions; Forecasts potential yield for crops as the season progresses; Calculates yield and water use efficiencies at the end of the growing season; Calculates likelihood of receiving rainfall to achieve target yields. |
| Audience: |
Farmers, consultants, advisers |
| Regions, scale, time of year: |
Grainbelt; Farm; At start of season and within season |
| Types of decisions: |
Sowing, crop nutrition, pest control |
| Strengths/limitations: |
Widely used through the Climate Risk and Yield Information Service and as a stand alone tool in SA, Vic and WA cropping districts. Decile data sets supplied though extensive are not exhaustive. While procedure is given for including data for new sites, data are not readily available and inclusion process is complex. Growing season is limited to April/may to Sept, Oct or Nov. No flexibility to include crops growing beyond Dec 31. Rainfall data files have to be created manually. |
| Inputs: |
Your summer rainfall and seasonal daily rainfall; your expected or observed final yields |
| Outputs: |
Potential yield; stored soil water; accumulated rainfall; current decile category; water use efficiency |
| Expertise/system r'quts: |
basic computer skills; Minimum system requirements: IBM-compatible PC with minimum specifications of Pentium 90, 16 Mb RAM, CD-ROM, 800x600 display, Windows 95. |
| Availability/status: |
Available on CD; Released: 1996. Updated: D. Tennant, Aug. 2002. Non-DAWA staff can purchase a copy of PYCAL from Dr Meredith Fairbanks, 9441 8112, Email: mfairbanks@agric.wa.gov.au |
| Relevant Links: |
Climate Calculator |
| Contact: |
Dr Meredith Fairbanks, Tel: (08) 9441 8112, Email: mfairbanks@agric.wa.gov.au |
| Name of model: |
ROOTMAP |
| Developer(s): |
Dr Vanessa Dunbabin and Dr Art Diggle |
| Aims/use: |
Simulates interactions between plant roots and the soil environment |
| Key features: |
Produces an animated pictorial representation of the root systems and soil conditions |
| Audience: |
Research workers performing detailed examinations of roots and their function |
| Regions, scale, time of year: |
Any; <1 square metre; growing season |
| Types of decisions: |
Choice of variety, any agronomic decision that affects soil conditions |
| Strengths/limitations: |
Requires programming skill and lots of time |
| Inputs: |
Detailed measurements of roots and soils |
| Outputs: |
Detailed prediction of root growth, function and effects |
| Expertise/system r'quts: |
C++ programming; Macintosh |
| Availability/status: |
By negotiation; details published in Plant and Soil 2002 |
| Contact: |
Dr Art Diggle, Tel: (08)9368 3669, Fax: (08)9374 3749, Email: adiggle@agric.wa.gov.au |
| Name of model: |
SPLAT |
| Developer(s): |
Dr Bill Bowden, Ms Alex Edward |
| Aims/use: |
To choose wheat cultivar and nitrogen rate within the context of seasonal variation |
| Key features: |
Estimates yield, protein and dollar responses to nitrogen for different environmental and management scenarios. Yield potential in SPLAT comes from 80 to 100 year runs of the WA version of the APSIM simulation model for a factorial of cultivar, sowing time, soil type and location. Allowance is made for disease and weed levels in the crop. A single figure soil nitrogen status is entered. |
| Audience: |
Consultants, advisers and farmers |
| Regions, scale, time of year: |
Wheat growing areas; paddock; can be used strategically |
| Types of decisions: |
Sowing date, cultivar choice and nitrogen level |
| Strengths/limitations: |
The determination of yield potential for different seasons, sowing dates, soil types and locations (superceded by WA Wheat) is interacted with nitrogen rate effects and dose response curves are given for dollars, yield, protein and screenings. A comparative output between species and a seasonal probability analysis is given. The nitrogen input is a single figure and only one fertiliser nitrogen availability is considered. |
| Inputs: |
Location, cultivar, sowing date, soil type, weed history |
| Outputs: |
Comparative gross margin graphs for different seasonal decile ratings. Yield, protein and screenings response curves |
| Expertise/system r'quts: |
Basic computer skills; Microsoft Excel operating under Macintosh of Windows system |
| Availability/status: |
Available on floppy disk or via email; released 2000 |
| Contact: |
Dr Bill Bowden, Centre for Cropping Systems, Department of Agriculture, PO Box 483, Northam 6401. Tel: (08) 9690 2190, Fax: (08) 9622 1902, Email: bbowden@agric.wa.gov.au |
| Name of model: |
Yield Calculator
|
| Developer(s): |
Dr David Tennant
|
| Aims/use: |
1. To estimate stored soil water at the start of the growing season or at planting. 2. To forecast yield for a range of cereal crops as the season progresses and calculate yield at the end of the season 3. Can be used to quantify a technology trend. |
| Key features: |
Estimates stored soil moisture at planting or at start of growing season; forecasts yield for crops as the season progresses based on a stress index and previous yields; calculates yield trends in terms of kg/ha/year.
|
| Audience: |
Farmers, consultants, advisers |
| Regions, scale, time of year: |
Calibrated for all Australian wheatbelt shires; can be calibrated using farm yields ( 10 years or more); at start of season and within season.
|
| Types of decisions: |
Provides information on yield probabilities. |
| Strengths/limitations: |
Strengths - widespread application; can be used across Australian grainbelt; predicts actual yields (if time series of yields and rainfall is available); works best in water-limiting regions. Limitations – requires a sequence of yields from which to derive the parameters. |
| Inputs: |
Daily rainfall, past yields, soil type, location-specific parameters.
|
| Outputs: |
Predicted yields through the season compared to yields from all other years of modelled runs, plant available soil moisture up to sowing.
|
| Expertise/system r'quts: |
Basic computer skills; Windows-compatible computer running Microsoft Excel. |
| Availability/status: |
Under development. Alpha version available on request |
| Contact: |
Dr David Tennant, Ph: 9368 3287, Email: dtennant@agric.wa.gov.au; or Dr Meredith Fairbanks, Ph: 9441 8112, Email: mfairbanks@agric.wa.gov.au |
| Name of model: |
Select Your Nitrogen(SYN)
|
| Developer(s): |
Drs Art Diggle and Bill Bowden |
| Aims/use: |
Select Your Nitrogen - a quantitative expert system to address soil nitrogen issues and their effects on yield, quality and dollars in broadscale cropping systems. |
| Key features: |
Major emphasis on effects of rotation, tillage, soil type and rainfall on soil nitrogen availability and it's impact on yield, quality (oil%, protein%) and dollars for non legume crops. It can handle segregations of cereals. Pulls together all previous WA nitrogen research and models (NAVAIL, RONSON, SPLAT). |
| Audience: |
Consultants, advisers and farmers |
| Regions, scale, time of year: |
Broadacre non-legume cropping systems; Paddock; Can be used both strategically and tactically (i.e. all year) |
| Types of decisions: |
Rotation, varietal choice, tillage and nitrogen fertiliser timing, sources and rates. |
| Strengths/limitations: |
Handles all crop nitrogen issues except foliar uptake. A comparative output format is used. Requires the input of a yield potential (SPLAT and WA Wheat do this better but are not as good on nitrogen availability issues) |
| Inputs: |
Soil, rainfall, cultivar and fertiliser menus can be adjusted by the user. Costs and prices can be adjusted. Rotation phases come in from menus and yields, harvest indices and pasture composition have to be estimated. |
| Outputs: |
Soil and nitrogen "availability", yield protein/oil and dollar returns. Sensitivity analyses on responses to rate of fertiliser, timing of fertiliser and yield potential. |
| Expertise/system r'quts: |
Basic computer skills; Microsoft Excel '97 or better |
| Availability/status: |
Available on a CD with users' manual as pdf; released October 2002. Updated May 2003 |
| Contact: |
Dr Bill Bowden, Centre for Cropping Systems,
Department of Agriculture, PO Box 483, Northam 6401. Tel: (08) 9690 2190,
Fax: (08) 9622 1902, Email: bbowden@agric.wa.gov.au |
Name of model: | TACT |
| Developer(s): |
Mr Steve Robinson and Dr Doug Abrecht |
| Aims/use: |
Critical information for assessing risks associated with sowing wheat |
| Key features: |
Climate analysis using heuristic rules and simulations of wheat yield and development |
| Audience: |
Agriculturalists with 'risky' questions |
| Regions, scale, time of year: |
All regions, but wheat simulation best in low rainfall eastern wheatbelt; point (scaled to paddock/lmu); anytime, strategic or tactical issues, depends on question and information required. |
| Types of decisions: |
Assessing rainfall and temperature dependant risks eg sowing opportunities/ rain during haymaking or shearing, frost risk, high temperature risk. Assessing impact of wheat sowing strategies on yield prospects given soil type and season to date rainfall. |
| Strengths/limitations: |
Easy to use. Season to date capability in yield simulation, distribution of differences compared to difference in distributions for assessing the impact of sowing decisions. Does not work well outside the eastern wheatbelt or on lighter soils. |
| Inputs: |
Current season (season to date) and historical daily weather data (max and min temperatures, rainfall, radiation) OR daily rainfall and average daily max min temperature and radiation. |
| Outputs: |
Graphs and tables of probability of outcomes/ yield distributions |
| Expertise/system r'quts: |
Basic computer skills; PC with MS DOS capability. |
| Availability/status: |
On request as foreign order; self expanding archive on 3.5 floppy or email; released 1992, updated 1996. |
| Contact: |
Dr Doug Abrecht, Tel: (08) 9081 3106, Mobile: 0427934648 Email: dabrecht@agric.wa.gov.au |
| Name of model: |
WA Wheat |
| Developer(s): |
Dr James Fisher and Mr Craig Scanlan |
| Aims/use: |
Enables users to predict the impact of particular combinations of season and management on wheat yield, protein content and the leakage of water and nitrate beyond the root zone for locations and soil types across the WA wheatbelt |
| Key features: |
We have used a validated simulation model, APSIM, to produce a database of information on wheat production in Western Australia for different combinations of season, soil type and management. The database has a powerful interface that enables data to be filtered and presented in a wide range of graphs. Data relating to production, quality, phenology, crop stresses, rainfall, water leakage and nitrate leaching can be displayed. Data can easily be exported to a spreadsheet for further analyses. |
| Audience: |
Farmers, consultants, advisers, researchers |
| Regions, scale, time of year: |
Wheatbelt; paddock; planning for the coming season. Regional/district analyses. Limited application within a season. |
| Types of decisions: |
Time of sowing, N fertiliser application (timing and rate), variety selection. Likely outcomes given historical seasons. |
| Strengths/limitations: |
Strengths: contains over 12 million datapoints, has broad application across the wheatbelt, has a wide range of outputs. Limitations: based on fixed runs of the model, limited flexibility to analyse a specific situation, data for wheat only. |
| Inputs: |
Select options from a fixed database. |
| Outputs: |
Wheat production, quality, phenology, crop stresses, rainfall, water leakage and nitrate leaching. Distributions, frequencies, time series, x-y plots. Data can be exported to a spreadsheet for further analyses. |
| Expertise/system r'quts: |
Familiarity with Windows-type of programs. Intermediate to high skill in creating and interpreting graphs; PC running Windows operating system with at least 64 MB RAM and a
Pentium processor. |
| Availability/status: |
To be distributed via CD-ROM.; Released May 2003. A second edition of the database is being developed as part of the "National Whopper Cropper" project. |
| Contact: |
Dr James Fisher, Centre for Cropping Systems,
Department of Agriculture, PO Box 483, Northam 6401. Tel: (08) 9690 2125,
Fax: (08) 9622 1902, Email: jsfisher@agric.wa.gov.au |
