Yield Potential?
Yield potential based on water supply (soil water + in_crop rain) and water use efficiency.
crop yield
Potential Yield? provides a progressive estimate of yield for the current season, based on rainfall to date and historic data.
Yield = (starting soil water + in_crop rainfall - threshold water) * WUE
Where:
- Starting soil water is an estimate of plant available soil water at planting;
- In_crop rainfall is calculated as rainfall from planting to the current date + expected rainfall until maturity;
- Threshold water - is subtracted from the above and represents water lost or needed before grain accumulates; and
- WUE (water use efficiency) has untis of kg/ha/mm and reprsents how water is converted to grain, lint or forage.
Crop yield is related to the amount of water stored in the soil at planting and in-crop rainfall, especially in water limiting environments. This simple estimate of crop yield is based on the Water Use Efficiency (WUE) model of French and Shultz (1984).
Stored soil water at planting or the start of the growing season is entered directly. This may be estimated from previous rainfall (a percentage stored), push probe observations, soil cores or soil water sensors. Current rainfall is charted against previous rainfall distributions.
A yield forecast is provided as the growing season progresses, using the most recent rainfall observations from the Bureau of Meteorology network of rainfall stations.
It allows decision-makers to answer questions such as:
Crop input decisions, at planting or early in the growing season can be supported by PY?.
For example, is early yield potential above average? If so, consider increasing fertiliser inputs. Or, given above average rainfall and soil water, we might increase area planted or plant more high value (and high input) crops.
Both the potential yield and water use efficiency estimates made at the end of the growing season provide benchmark values against which the success of the cropping enterprise can be assessed. If yield and water use efficiencies do not approach benchmark values, then attention can be focussed on what management changes might be needed to achieve better results.
Inputs
Potential Yield? asks the user for:
- A planting date and duration to maturity of a crop;
- A Water Use Efficiency (WUE) value (kg/ha/mm);
- A Threshold value (mm) representing water lost to evaporation or water that is not used by the plant;
- A location and soil type;
- Starting soil water (mm); and
- The duration of historic data (decadal to present) used to describe past outcomes and forward estimates.
Outputs
Potential Yield? provides output as answers in text and graphically as:
- A fire chart ranking the current yield estimate against historic yields as estimated with the WUE model
- Expected yield (kg/ha) and water supply for the current season
- A chart of historic and current seasons expected yields with a projection to the end of the current crop.
History
Potential Yield? is a re-enactment of the Potential Yield calculator (PYCAL), first developed in 1993 by Drs Shaun and David Tennant affiliated with the Western Australian Department of Agriculture. This program was originally written in GWBasic (MSDOS based) and was distributed on floppy discs. PYCAL was developed to estimate stored soil water at the start of the growing season or at planting and to forecast potential yield as the season progresses. PYCAL was rewritten for Windows in ~2000.
A web based version developed by the Department of Agriculture and Food, Western Australia (DAFWA), the Potential Yield Tool is available at
https://www.agric.wa.gov.au/climate-weather/potential-yield-tool
References
Tennant, D and S. Tennant. (2000) Potential Yield Calculator, software package. Department of Agriculture and Food, South Perth, WA.
Potential Yield Tool https://www.agric.wa.gov.au/climate-weather/potential-yield-tool
French RJ, Schultz JE. (1984) Water use efficiency of wheat in a Mediterranean-type environment. I. The relation between yield, water use and climate. Australian Journal of Agricultural Research 35(6) 743 – 764
